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"Why Does AI Art Look Like a ’70s Prog-Rock Album Cover? | WIRED"

"https://www.wired.com/story/generative-ai-style-movement-throwback"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Kate Knibbs Culture Why Does AI Art Look Like a ’70s Prog-Rock Album Cover? ILLUSTRATION: ROSIE STRUVE/DALL- E 2 Save this story Save Save this story Save Sometimes we stumble upon insight in unexpected places. Late last year, for example, I read perhaps the most precise description ever written about AI-generated art in The New York Times comments section. The article described what happened when a man named Jason Allen submitted an image generated by the AI program Midjourney to an art contest and won. (Long story short: Artists got mad.) While the story focused on the debate over the ethics of AI image generators, the comment had nothing to do with thorny moral considerations. Instead, it described how the winning work looked. “Congratulations to Mr. Allen on coaxing an algorithm to spit out an image that looks like a 1970s prog rock album cover,” it read. The commenter’s handle? Cynical Observer. Copyfight Will Knight Ideas Nick Vincent and Hanlin Li Ideas Joshua Glick Cynical, maybe. Observant, definitely. “Like a 1970s prog rock album cover” is a perfectly pithy way to convey what this new generative AI art scene frequently mimics. Allen’s winning entry resembles a French neoclassical painting with a sci-fi twist. Womanly figures in flowy sienna and white robes stand in a vast ornate chamber with a vaguely alien cityscape in the background. It’s not offensive or anything—calling it “moderately groovy” is apt—but let’s just say the first-place award would make more sense if the judges of the art contest were, like, all the remaining living members of Jethro Tull. In the past year, a slew of AI image generators have whipped up a galactic amount of buzz. Trained on vast data sets containing billions of images hoovered up from across the internet—animated stills, iconic photographs, the work of artists living and dead, memes, screenshots, selfies, even porn—these programs produce images that can look disconcertingly close to what a human might make, give or take a glitchy hand or two. Midjourney (and similar programs like Stable Diffusion and Dall-E) has provoked awe, anxiety, anger, and questions: Will this AI take jobs from artists? Where does copyright law land? Can machines ever truly produce something original? Should I feel guilty for making a picture of Tony Soprano having a cappuccino with Shrek and sharing it with my group chat? All good questions, ones people will likely be vehemently debating for years. Lost amid the hype and hand-wringing, though, is another query: Why does so much AI art look like it could be on a ’70s prog-rock album cover? Image created by the author using DALL-E and the prompt “1970s prog-rock album cover.” OpenAI via Kate Knibbs Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The good news is, I’m a journalist, so I went ahead and asked some artists, researchers, and art critics what they made of the aesthetics of AI art. First up, I called Amelia Winger-Bearskin, an artist and professor at the University of Florida. Winger-Bearskin has been cataloging different visual trends she’s noticed in recent AI art. She calls one trend Nightmare Corp. —often exemplified by images conjured by Google’s Deep Dream, an older generator released in 2015. It specializes in swirling, psychedelic imagery, like memories from an especially harrowing acid trip. “Prog-rock influences, for sure,” she says. Another category Winger-Bearskin explores, which she calls Dada 3D, sounds a lot like the goofy scenes I prompt when I play around with these generators. She describes it as “something like a surrealist parlor game.” Aside from taxonomizing trends, Winger-Bearskin has noticed broader stylistic tics in these generators. She sees Disney-style Western animation and anime as obvious influences, as well as a tendency to treat whiteness as the default race—a result, she suspects, of training these generators on data sets that are heavy on Disney-style Western animation, anime, and images of white people. “The rhetoric from these companies is that you can make anything you can imagine. But, of course, popular culture follows particular stereotypes and tropes.” —Lev Manovich, professor at the City University of New York Lev Manovich is paying close attention, too. The cultural theorist and professor at the City University of New York has been lurking in Midjourney’s Discord server since last year, analyzing how people use the generator. After Midjourney released an update last fall, he saw some changes in what people were prompting the generator to make. After it got better at representing humans realistically, for instance, requests for portraits of both men and women went up. Digital artist Sam King first started closely following the AI art scene in 2021. Excited by what they saw, they started sharing their favorite images on social media, building a following as a curator just as the technology took off. They describe the earlier wave of generators as favoring “trippy, abstract stuff.” (These generators are known as generative adversarial networks, or GAN. I’ve seen a few people call this look, rather uncreatively, GANism.) King sees the newest wave of generators, called diffusion models, as stylistically distinct. Just as oil painting and watercolors produce recognizably different effects, GAN generators and diffusion generators produce recognizably different images. If you want a more realistic rendering of, say, Tony Soprano having a cappuccino with Shrek, the diffusion models are more likely to produce convincing results. “In theory, you can make all kinds of different aesthetics with these machines,” they say. More realistic doesn’t necessarily mean more stylistically varied, though. Like Winger-Bearskin, King sees Disney and anime influences cropping up frequently, as well as comic book art. “The rhetoric from these companies is that you can make anything you can imagine. It’s about this open frontier. But, of course, popular culture follows particular stereotypes and tropes,” Manovich says. He sees variations on several themes again and again: “​​Fantasy, fairytale, comic book, video game.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Image created by the author using DALL-E and the prompt “1970s prog-rock album cover.” OpenAI via Kate Knibbs Manovich pointed out that the type of people who gravitate toward these programs heavily shape what gets produced through their personal taste and preferences. Midjourney’s Discord, for example: “Very dominated by male users.” That tracks with how King described what they’ve seen coming out of Midjourney: “Loads of depictions of women with blank expressions on their faces, where they look kind of sexy.” I took a page from Manovich’s book and started lurking in the Midjourney Discord, to observe what people generated in real time. It was not exactly a journey into the avant-garde. Within the first two minutes, prompts included “woman looking at clouds renaissance style,” “little space princess, pretty face, crown, magic castle, dress, animated character, high definition, 8k,” “old guy smoking pipe, portraiture, hyper realistic, 4K,” and “male geisha.” Is every single piece of AI art inherently hokey or boring? No. But it is striking that we’ve developed these startlingly powerful tools for conjuring visual representations of our wildest dreams and we’re producing male geishas and space princesses. It can feel like watching people play “Chopsticks” over and over on a Steinway Model D grand piano. There are already stereotypes forming about what AI art looks like; an artist was recently banned from a Reddit forum because their work simply looked like it was AI-generated. (It was not.) “You need to find a different style,” the moderator said. It may not surprise you to hear that the image in question, showing a beautiful woman in a flowy robe surrounded by birds and red eyes in the sky, looks for all the world like it could be a prog-rock album cover. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg But here’s a nice thought: Although AI image generation may never move beyond the ersatz, it could still lead to actual artistic breakthroughs. Art critic Mike Pepi isn’t impressed by how people are using the current generators. “Right now, when you go on Midjourney or DALL-E and you type in something and it ends up looking really cool—and it was just you messing around on your computer—clearly, there’s not a lot of authorial intent there. That’s not a real reflection of you as an artist,” he says. Still, he doesn’t rule out the possibility that these generators can aid genuine artistry if used judiciously. “What could be interesting is an artist who is using these tools as one step in a grander assemblage, like a movie director or conceptual artist. That’s where you have the capacity for human creativity to best employ these tools,” he says. Meanwhile, Winger-Bearskin likes to imagine that generative AI’s greatest aesthetic achievement might be inadvertent. This moment reminds her of the advent of photography, when many painters feared the new technology would make them obsolete. “People said, OK, that’s the death of painting, because now people will just be able to reproduce portraits perfectly using this machine,” she says. “But that led to the explosion of impressionism and abstract expressionism and all of these other forms of painting, because we realized that painting didn’t have to represent something.” In the same vein, Winger-Bearskin thinks this moment could spur artists to react against generative AI—or use it subversively—to create genuinely original work. I love this idea. Imagine: After all this technological progress and hype, the most exciting achievement of these generators could be inspiring artists to react against them. It makes sense. After all, without prog rock, there would be no punk. You Might Also Like … 📧 Find the best bargains on quality gear with our Deals newsletter “ Someone is using photos of me to talk to men” First-gen social media users have nowhere to go The truth behind the biggest (and dumbest) battery myths We asked a Savile Row tailor to test all the “best” T-shirts you see in social media ads My kid wants to be an influencer. Is that bad? 🌞 See if you take a shine to our picks for the best sunglasses and sun protection Senior Writer X Topics art artificial intelligence Jason Parham Kate Knibbs Vauhini Vara Virginia Heffernan Kate Knibbs Gideon Lichfield Lindsay Jones Jason Parham Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. 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"The 27 Best Family Board Games (2023): Cascadia, Labyrinth, and More | WIRED"

"https://www.wired.com/gallery/best-family-board-games"

"Open Navigation Menu To revisit this article, visit My Profile, then View saved stories. Close Alert To revisit this article, select My Account, then View saved stories Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Simon Hill Gear The Best Family Board Games Facebook X Email Save Story Facebook X Email Save Story If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED A Simple Starter $30 at Amazon Cute, Dangerous Cats $20 at Amazon Trade and Build $48 at Amazon Cooperative Cards $15 at Amazon It’s good to take a break from screens every now and then. The great outdoors has plenty to offer, but there are times when you’re stuck inside for one reason or another. Board games are a fun way to gather everyone around the table to engage in some group escapism. My family has had a board game night most weeks for a couple of years now, and we’ve discovered some great games. These are our favorites, selected with the help of my two kids, ages 10 and 13. We didn’t include board game classics you probably know all about (or own), like Clue, Monopoly, Connect 4, Scrabble, Operation, Chutes and Ladders, Battleship, Jenga, Guess Who, Pictionary, and Risk. For more ideas, check out our list of the Best Board Games to Play Over Zoom. Updated May 2023: We added Catan and League of the Lexicon, and updated prices throughout. Special offer for Gear readers: Get a 1-year subscription to WIRED for $5 ($25 off). This includes unlimited access to WIRED. com and our print magazine (if you'd like). Subscriptions help fund the work we do every day. Photograph: Ravensburger A Simple Starter Labyrinth One of the first board games we played together as a family, Labyrinth is simple enough for anyone to grasp. The board is a maze, and you must collect a set of treasures based on the cards you’re dealt. The fun part of this game designed by a German psychologist, is how you can change the maze by pushing one tile onto the board and another off every turn. Carve out a route for yourself, but also consider how to block your opponents. $30 at Amazon $34 at Walmart Photograph: Exploding Kittens Cute, Dangerous Cats Exploding Kittens This deceptively simple card game is easy to pick up but has layers of strategy as you try to avoid exploding kitten cards. It combines fun elements from classic card games, like Old Maid, and adds a modern twist. There’s just enough complexity to make things fun, but never so much that it gets confusing. The card art features some cute, and not so cute, cats with all sorts of special powers to turn the tables on your opponents. When it starts to get old, the expansions do a great job of breathing new life into the game. $20 at Amazon $20 at Target $20 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Amazon Trade and Build Catan Formerly known as Settlers of Catan, this addictive strategy game challenges you to gather and trade resources to build and settle a randomly generated board of hexagonal tiles. Dominating the map and gaining enough points for a victory requires the right strategy and a bit of luck with dice rolls. My eldest (13) loves this game, especially the trading portion and the robber mechanic, which allows you to steal cards from your opponents and block their resources (though it can cause arguments). It works well with three or four players and is easy to grasp, and you can finish a game in an hour. There’s plenty of replay value and a wide range of expansions. For younger players, a junior version of Catan is suitable for kids starting in kindergarten. $48 at Amazon $48 at Target Photograph: Thames and Kosmos Cooperative Cards The Crew: Mission Deep Sea This clever card game is a cooperative trick-taking challenge for three to five players with tons of replay value. Each game of The Crew features an underwater mission with a brief background story, and they gradually grow in difficulty and complexity. For mission success, you have to complete a set of tasks, which requires some cooperation, but you aren’t allowed to discuss the cards in your hand. It’s easy to learn, quick to play, and highly addictive. $15 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Z Man Games For Working Together Pandemic It feels a little strange playing Pandemic after recent events, but the beauty of this game is that it’s cooperative. Each player has a role, and you work together to eradicate four deadly diseases before humanity’s fate is sealed. It’s often exciting, encouraging communication and group strategy. The key to success is taking advantage of each player’s unique abilities, and you can complete a game in less than an hour. There are also some deep expansions if your family likes it. $36 at Amazon $36 at Target $30 at Walmart Photograph: Pegasus Spiele For Detectives MicroMacro: Crime City Refreshing and unlike anything we’ve played before, MicroMacro: Crime City is a cooperative game about solving crimes for up to four players, but it also works as a solo game. Plenty of space is needed to unfurl the city map and move freely around it with the magnifying glass hunting for suspects and clues. There’s a Where’s Waldo element to the hunt, but it’s combined with loose narratives that take you through each crime scene, unraveling the mystery step-by-step as you work together to track down the culprit. Discussing theories is a big part of the fun here, and cases take anywhere from 10 minutes to an hour to solve. While younger kids will enjoy it, the game is recommended for ages 12 and up because some cases deal with adult topics. There isn’t much replay value here, but the sequel MicroMacro: Crime City - Full House ($28) offers fresh cases on a new map. $29 at Amazon $37 $25 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: The City of Games For Cat Lovers The Isle of Cats Beautifully designed and completely unique, Isle of Cats is an instant hit with cat lovers like my daughter. You must rescue cats and fit them onto your boat, Tetris style, to escape from the island before the baddie turns up. You need fish to tempt them aboard, and there are lots of cards to add layers of strategy. It can seem overwhelmingly complex in the beginning, but after a few rounds it all makes sense. We preferred the full game to the simplified rules, though scoring is quite complicated, and you’ll want to set aside a few hours. $36 at Amazon Photograph: Pegasus Spiele Push Your Luck Port Royal As merchants trying to build an influence in the Caribbean you must first amass a fortune, recruit a crew, complete expeditions, and capture ships. The base game features a 120-card deck with lovely artwork, and is easy to pick up. The big hook here is the gamble as you decide when to stop drawing cards. Push your luck too far, and you lose out on that round. The mix of cards allows for many strategies, but young kids (maybe 7 or 8 years and up) can grasp the gameplay and compete. It’s for two to five players (we found it perfect for four), and games come in under an hour. There are several expansion packs if you enjoy the base game. $27 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Blue Orange For Budding Strategists Kingdomino Build a 5 x 5 tile kingdom around your castle using randomly drawn tiles that connect just like dominoes in this light and speedy game. Each piece of matching terrain scores you a point, multiplied by the crowns on the tiles you chose. It is simple enough for younger kids to grasp but still offers some room to try different strategies. You can play with up to four players, but we like it best with two. $20 at Amazon $20 at Walmart Photograph: Exploding Kittens Caveman Chuckles Poetry for Neanderthals This daft party game from the makers of Exploding Kittens is fun for groups of all ages. Every card has a word on it, and your seemingly simple challenge is to get your team to correctly guess that word within the time limit by speaking in single syllables only. If you break the rules, the opposition can hit you with the inflatable “No” stick. It’s loud and silly and usually makes everyone laugh. $20 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Days of Wonder For Something More Complex Ticket to Ride With lovely steam engine styling and rules even young kids can quickly understand, Ticket to Ride is a wonderful introduction to more complex board games. The aim of this German-style game by beloved publisher Days of Wonder is to claim different railway routes across the US and Canada using your colorful plastic rail cars. You spend cards to claim routes, and there are bonus points for connecting certain destinations. The European version adds ferries and tunnels, and there are lots of other expansions. The only downside is that my wife always wins. (There's also a version called First Journey that shortens and simplifies the gameplay for younger kids.) $48 at Amazon $48 at Target $47 at Walmart Photograph: Big Potato Games For Big Bluffers The Chameleon There’s a topic card with 16 words, and a dice roll determines the chosen word. One player gets the Chameleon card. Their mission is to avoid detection, but the catch is that they don’t know which word was chosen. Each player says a related word then everyone votes to try and expose the bluffer. It is a quick and easy party game for up to eight players and always has our kids chortling with glee. While you can play with three, it’s best with more players (six or seven is perfect). Some topics can be tricky for younger kids, but you can write your own topic card. $20 at Target $17 at Amazon $17 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Spin Master Games Ask Your Questions Hedbanz My kids find this game hilarious, and we used to play it a lot when they were younger. It’s a simple idea: The other players choose a card and stick it into your headband facing out without letting you see it. You have a limited time to ask questions and figure who or what you are. We used to play an adult version of this in college by writing on cigarette papers and sticking them to each other’s heads, but this version is completely family-friendly. $14 at Amazon $14 at Target $14 at Walmart Photograph: Megacoprin Games Murder Mystery Awkward Guests When you have played Clue to death and crave a more challenging murder mystery game, try Awkward Guests. The aim is to solve the murder of the thoroughly unpleasant Mr. Walton by figuring out who killed him, where they did it, what they used, and whether they had an accomplice. But there’s more depth to this deductive game, as you must collect and swap clues. The information exchange is a tactical balance between amassing knowledge and hiding juicy clues from your competitors. Recommended for kids aged 12 years and up, but some younger children will enjoy this too. $42 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Ravensburger Monster Mash Horrified Can you save the town from classic movie monsters like Dracula, the Mummy, and the Bride of Frankenstein? This title pits up to five players against a revolving cast of monsters. Each villain behaves differently and can only be banished when you work together to defeat them. There's tons of replay value as you work out the best strategy to save the town, the villagers, and yourselves. Cooperative play like this can also help you avoid arguments on family board game night. If you enjoy Horrified, you should also try Horrified: American Monsters ($45) and Alien: Fate of the Nostromo ($30) , though both may prove a little too scary for younger kids. $40 at Amazon $40 at Barnes & Noble Photograph: USAopoly Sketch and Laugh Telestrations Loosely based on the classic Telephone game, Telestrations challenges you to draw words or phrases and identify sketches as you pass erasable books around the table. By the time they get back to their owner, signaling the end of the round, the original words have often morphed into something wildly different. This party game gets everyone involved, and going through the sketchbooks to follow the journey is often hilarious. It’s recommended for between four and eight players aged 12 years and up, but it works best with at least six players, and our 9-year-old daughter loved it. $18 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Next Move Games Soothing Patterns Azul Everyone loves the colorful, decorative tiles in this game, inspired by the Moorish designs in the Alhambra palace in Southern Spain. The goal is to decorate the royal palace for the King of Portugal. Each round, you pick tiles from the central discs and use them to fill your game board, paying attention to the points that different sets and patterns score. The description doesn’t do this justice—you must play it to see why it’s so appealing. Like many of the best games, it’s quick to learn but has real strategic depth. $32 at Amazon $32 at Target Photograph: Alderac Entertainment Group Wonderful Wildlife Cascadia Kids love animals, and this wildlife adventure into the Pacific Northwest focuses on laying terrain tiles and populating habitats with appropriate wildlife tokens. Match habitat tiles to form contiguous areas, like wetlands or forest, and complete wildlife goals, like amassing runs of salmon or pairs of bears. Special nature tokens allow for more strategic depth. This is a gentle game for one to four players aged 10 years and up, but there’s nothing to stop younger kids from playing if they can grasp the rules. $40 at Amazon Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Drumond Park For Good Laughs Articulate Trying to describe words to your team without saying them, using the first letter, or resorting to rhyming is the fun challenge at the heart of Articulate. There’s a kid’s version, and we use cards from that mixed with the original to get the right level of difficulty for adults and children. Fast and frenetic, this game often provokes the giggles, but can also cause frustration and the occasional huff. It works well with big groups because you can divide into teams and take turns to describe. $25 at Amazon Photograph: Funko Games Movie Magic E.T. The Extra-Terrestrial: Light Years From Home Game This cooperative game for two to four people is one of the best movie tie-ins we have ever played. Game designer, Prospero Hall, shows real reverence for the source material. And E.T. lends itself to coop gameplay, with players taking on the roles of Elliot, Gertie, Mike, or Greg to ferry E.T. around on their BMXs and keep him out of the clutches of the authorities until the mothership can rescue him. Solid mechanics, a balanced challenge, and a sprinkling of movie magic make for a fun hour of family gaming. $12 at Amazon $30 at Target Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Gamewright Card Combos Sushi Go Party! Collect sets of super cute sushi cards to match the menu and score points in this accessible card game. You select a card on each turn to build a delectable meal and pass on the rest of your hand to the next player. The gameplay is compelling and easy to grasp but allows for many different strategies. You can tailor it for your group by switching the menu, which provides enormous replay value. It works with two to eight people, but four is perfect. The only negative is that it leaves you craving sushi. $20 at Amazon $20 at Walmart Photograph: Roxley Games Best for Two People Santorini While you can play with three or four, this 3D game is best with two players. You move and build every turn, aiming to reach the third level with one of your builders to win. Santorini is basic but fun and quick to play; it's simple enough for young kids. When you’re ready to mix it up, introduce the Greek Gods cards to give players special powers. Start with the beginner set of 10 and eventually add the advanced cards, which takes the total number of Gods up to 30. The scalable nature makes this a great game to return to and tweak as your kids grow older. $40 at Amazon $30 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Two Brothers Games For Logophiles League of the Lexicon Anyone interested in linguistics, slang, grammar, or etymology will get a kick out of this beautifully crafted trivia game. Players roll a wooden dice that decides the category and win an artifact if they answer correctly. Questions in League of Lexicon range from fiendishly difficult to deceptively simple, and full answers add some educational value. With contributions from a brain trust of linguists, authors, and lexicographers, the 2,000 multiple-choice questions offer real depth, with cards divided into ticklish and tricksy difficulties. We’ve been enjoying this as a family of four, with the kids sticking to the easier questions, but you could also play in teams. It’s recommended for children aged 10 and up, but vocabulary level is more important than age. $40 at Amazon Photograph: Exploding Kittens For Chaotic Action Throw Throw Burrito This frenetic party game is a big hit with groups of kids, but it’s best played outdoors or in a room with plenty of space and no fragile ornaments. The card game portion is a race to find sets of three and pass along cards you don’t want, but some combinations trigger attacks that see everyone grasping for the squishy toy burritos in the center of the table and throwing them at each other. $25 at Amazon $25 at Target $25 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Big Potato Games For Large Groups Herd Mentality A great party game for up to 20 players, the aim of Herd Mentality is to write down the same answer as everyone else. Subjective questions like, “What’s the best pizza topping?” or “Would you rather have robot arms or robot legs?” provoke debate and laughter. When you’re in the majority you collect a cow token. The first player to amass eight cows wins. It’s simple, quick to play, and great for larger family gatherings. $25 at Amazon $19 at Target $39 at Walmart Photograph: Libellud For Ghost Hunters Mysterium This game is a little bit spooky and combines elements of Clue with deeper role-playing games. Set at a séance in 1920s Scotland, players are cast as mediums, with one person taking on the role of the ghost. The psychics work together to interpret vision cards from the ghost and work out who murdered them, where, and with which weapon before the break of dawn. It works best if an adult or older kid takes on the most challenging ghost role, and there’s quite a lot of setup, but this is engrossing once you get going. $44 at Amazon $44 at Walmart Gear The Best Home Depot Black Friday Deals Matt Jancer Gear Apple’s Pledge to Support RCS Messaging Could Finally Kill SMS Boone Ashworth Gear Wish List: 47 Awesome Gifts for All the Enthusiasts, Connoisseurs, and Fanatics in Your Circle WIRED Staff Gear The PlayStation Portal Turns Your PS5 Into a Handheld, Sorta Eric Ravenscraft Photograph: Ravensburger Dark Side Star Wars Villainous We played Disney Villainous a few times, but it failed to hook us, so I wasn’t expecting us to enjoy Star Wars Villainous as much as we did. This beautifully themed board game casts each player as a different villain from the Star Wars universe, from Darth Vader to Moff Gideon. Like other games in the Villainous series, every character has a unique set of victory conditions, and the other players get opportunities to meddle. It takes a few plays to get your head around and is best for four players aged 10 years and up. $35 at Amazon $35 at Target Photograph: Pegasus Spiele Other Great Family Board Games Honorable Mentions There are so many family board games. Here are a few we also like. Kitchen Rush for $51 : A truly unique title that proves too many cooks can spoil the broth; this game can get chaotic fast. You work together to cook dishes for customers within a strict time limit. It’s a little too complicated for young kids (I’d say 10-years and up is best). If you like this, try the videogame Overcooked. Sounds Fishy for $20 : Another fun group game from Big Potato, the challenge in Sounds Fishy is to spot fake answers. Each card poses a question, but only one of the answers you get is correct. It’s for four to 10 players, and we found it more fun but tougher with more people. Zillionaires Road Trip USA for $17 : Each of the 49 squares on the game board is a quirky roadside attraction, from Bubblegum Alley to the National Mustard Museum, and players bid to buy them with the aim of securing four in a row. My kids loved this, the adults not so much. Cards Against Humanity: Family Edition for $29 : You can play this party game with up to 30 players, and it will produce a fair bit of juvenile giggling and chortling. Like the adult version, there isn’t much strategy here, but finding the perfect combination to crack everyone up is satisfying. The Haunted Mansion – Call of the Spirits for $13 : Collect ghost cards as you explore the Gothic mansion via the rotating hallway and try to avoid picking up too many haunt cards. Disney park fans will get a nostalgic glow, and you can complete a game in just half an hour. Contributor X Topics buying guides Board Games Shopping Boone Ashworth Scott Gilbertson Virginia Heffernan Scott Gilbertson Reece Rogers Carlton Reid Matt Jancer Boone Ashworth WIRED COUPONS Dyson promo code Extra 20% off sitewide - Dyson promo code GoPro Promo Code GoPro Promo Code: save 15% on your next order Samsung Promo Code +30% Off with this Samsung promo code Dell Coupon Code American Express Dell Coupon Code: Score 10% off select purchases Best Buy Coupon Best Buy coupon: Score $300 off select laptops VistaPrint promo code 15% off VistaPrint promo code when you sign up for emails Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Google Warns That NSO Hacking Is On Par With Elite Nation-State Spies | WIRED"

"https://www.wired.com/story/nso-group-forcedentry-pegasus-spyware-analysis"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Lily Hay Newman Security Google Warns That NSO Hacking Is On Par With Elite Nation-State Spies Photograph: Amir Levy/Getty Images Save this story Save Save this story Save The Israeli spyware developer NSO Group has shocked the global security community for years with aggressive and effective hacking tools that can target both Android and iOS devices. The company's products have been so abused by its customers around the world that NSO Group now faces sanctions, high-profile lawsuits, and an uncertain future. But a new analysis of the spyware maker's ForcedEntry iOS exploit—deployed in a number of targeted attacks against activists, dissidents, and journalists this year—comes with an even more fundamental warning: Private businesses can produce hacking tools that have the technical ingenuity and sophistication of the most elite government-backed development groups. Google's Project Zero bug-hunting group analyzed ForcedEntry using a sample provided by researchers at the University of Toronto's Citizen Lab, which published extensively this year about targeted attacks utilizing the exploit. Researchers from Amnesty International also conducted important research about the hacking tool this year. The exploit mounts a zero-click, or interactionless, attack, meaning that victims don't need to click a link or grant a permission for the hack to move forward. Project Zero found that ForcedEntry used a series of shrewd tactics to target Apple's iMessage platform, bypass protections the company added in recent years to make such attacks more difficult, and adroitly take over devices to install NSO's flagship spyware implant Pegasus. Apple released a series of patches in September and October that mitigate the ForcedEntry attack and harden iMessage against future, similar attacks. But the Project Zero researchers write in their analysis that ForcedEntry is still “one of the most technically sophisticated exploits we've ever seen.” NSO Group has achieved a level of innovation and refinement, they say, that is generally assumed to be reserved for a small cadre of nation-state hackers. “We haven't seen an in-the-wild exploit build an equivalent capability from such a limited starting point, no interaction with the attacker's server possible, no JavaScript or similar scripting engine loaded, etc.,” Project Zero's Ian Beer and Samuel Groß wrote in an email to WIRED. “There are many within the security community who consider this type of exploitation—single-shot remote code execution—a solved problem. They believe that the sheer weight of mitigations provided by mobile devices is too high for a reliable single-shot exploit to be built. This demonstrates that not only is it possible, it's being used in the wild reliably against people.” Apple added an iMessage protection called BlastDoor in 2020’s iOS 14 on the heels of research from Project Zero about the threat of zero-click attacks. Beer and Groß say that BlastDoor does seem to have succeeded at making interactionless iMessage attacks much more difficult to deliver. “Making attackers work harder and take more risks is part of the plan to help make zero-day hard,” they told WIRED. But NSO Group ultimately found a way through. ForcedEntry takes advantage of weaknesses in how iMessage accepted and interpreted files like GIFs to trick the platform into opening a malicious PDF without a victim doing anything at all. The attack exploited a vulnerability in a legacy compression tool used to process text in images from a physical scanner, enabling NSO Group customers to take over an iPhone completely. Essentially, 1990's algorithms used in photocopying and scanning compression are still lurking in modern communication software, with all of the flaws and baggage that come with them. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The sophistication doesn't end there. While many attacks require a so-called command-and-control server to send instructions to successfully placed malware, ForcedEntry sets up its own virtualized environment. The entire infrastructure of the attack can establish itself and run within a strange backwater of iMessage, making the attack even harder to detect. “It's pretty incredible and, at the same time, pretty terrifying,” the Project Zero researchers concluded in their analysis. Project Zero's technical deep dive is significant not just because it explicates the details of how ForcedEntry works but because it reveals how impressive and dangerous privately developed malware can be, says John Scott-Railton, senior researcher at Citizen Lab. “This is on par with serious nation-state capabilities,” he says. “It's really sophisticated stuff, and when it's wielded by an all-gas, no-brakes autocrat, it's totally terrifying. And it just makes you wonder what else is out there being used right now that is just waiting to be discovered. If this is the kind of threat civil society is facing, it is truly an emergency.” After years of controversy, there may be growing political will to call out private spyware developers. For example, a group of 18 US congresspeople sent a letter to the Treasury and State Departments on Tuesday calling on the agencies to sanction NSO Group and three other international surveillance companies, as first reported by Reuters. “This isn’t ‘NSO exceptionalism.’ There are many companies that provide similar services that likely do similar things,” Beer and Groß told WIRED. “It was just, this time, NSO was the company that was caught in the act.” 📩 The latest on tech, science, and more: Get our newsletters ! The Twitter wildfire watcher who tracks California’s blazes The fall and rise of real-time strategy games A twist in the McDonald’s ice cream machine hacking saga The 9 best mobile game controllers I accidentally hacked a Peruvian crime ring 👁️ Explore AI like never before with our new database ✨ Optimize your home life with our Gear team’s best picks, from robot vacuums to affordable mattresses to smart speakers Senior Writer X Topics malware hacking vulnerabilities Google Andrew Couts Andy Greenberg Tom Bennett Matt Burgess Kate O'Flaherty Lily Hay Newman Dhruv Mehrotra Andy Greenberg Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Report: US and Israel Behind Flame Espionage Tool | WIRED"

"https://www.wired.com/2012/06/us-and-israel-behind-flame"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Kim Zetter Security Report: US and Israel Behind Flame Espionage Tool Save this story Save Save this story Save The United States and Israel are responsible for developing the sophisticated espionage rootkit known as Flame, according to anonymous Western sources quoted in a news report. The malware was designed to provide intelligence about Iran's computer networks and spy on Iranian officials through their computers as part of an ongoing cyberwarfare campaign, according to the Washington Post. The program was a joint effort of the National Security Agency, the CIA and Israel's military, which also produced the Stuxnet worm that is believed to have sabotaged centrifuges used for Iran's uranium enrichment program in 2009 and 2010. “This is about preparing the battlefield for another type of covert action,” a former high-ranking US intelligence official told the Post. “Cyber collection against the Iranian program is way further down the road than this.” Flame was discovered last month by Russia-based antivirus firm Kaspersky Lab, following reports in Iran that malware aimed at computers belonging to that country's oil industry had wiped data from the computers. In trying to investigate that issue, Kaspersky came across components of the Flame malware, which the researcher believed was not directly connected to the malware that wiped the Iranian computers clean but which they believed was created by the same nation states behind Stuxnet. Kaspersky disclosed last week that Flame in fact contained some of the same code as Stuxnet , directly tying the two pieces of malware together. According to the Post Flame was designed to infiltrate highly secure networks in order to siphon intelligence from them, including information that would help the attackers map a target network. Flame, as previously reported, can activate a computer's internal microphone to record conversations conducted via Skype or in the vicinity of the computer. It also contains modules that log keyboard strokes, take screen shots of what's occurring on a machine, extract geolocation data from images and turn an infected computer into a Bluetooth beacon to siphon information from Bluetooth-enabled phones that are near the computer. Flame exploited a vulnerability in Microsoft's terminal service system to allow the attackers to obtain a fraudulent Microsoft digital certificate to sign their code, so that it could masquerade as legitimate Microsoft code and be installed on a target machine via the Microsoft software update function. Flame was developed at least five years ago as part of a classified program code-named Olympic Games, the same program that produced Stuxnet. “It is far more difficult to penetrate a network, learn about it, reside on it forever and extract information from it without being detected than it is to go in and stomp around inside the network causing damage,” said Michael V. Hayden, a former NSA director and CIA director who left office in 2009, told the Post. It's still unclear whether the malware used to attack computers in Iran's oil ministry is the same malware now known as Flame. According to the Post , the attack on the oil ministry computers was directed by Israel alone, a matter which apparently caught US officials off guard, according to anonymous sources who spoke with the newspaper. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg X X Topics stuxnet Threat Level Lily Hay Newman Andy Greenberg Matt Burgess Lily Hay Newman Andy Greenberg Dhruv Mehrotra Matt Burgess Lily Hay Newman Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Did a U.S. Government Lab Help Israel Develop Stuxnet? | WIRED"

"https://www.wired.com/2011/01/inl-and-stuxnet"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Kim Zetter Security Did a U.S. Government Lab Help Israel Develop Stuxnet? Save this story Save Save this story Save Questions are being raised about the involvement of U.S. government researchers in the creation of a digital weapon that experts believe may have sabotaged centrifuges at a uranium-enrichment plant in Iran. Researchers at the Idaho National Laboratory, which is overseen by the U.S. Department of Energy, may have passed critical information to Israel about vulnerabilities in a system that controls Iran’s enrichment plant at Natanz. That information was then used to create and test the so-called Stuxnet worm that was unleashed in a joint cyberattack on Natanz, according to The New York Times. The report, based on anonymous sources, is sparse on detail but asserts that in 2008, INL worked with the German firm Siemens to uncover vulnerabilities in its industrial-control system. Stuxnet was then created to exploit those vulnerabilities and was lab-tested at Israel’s nuclear facility in Dimona. The Dimona facility, according to the Times , has been involved in a joint U.S.-Israel operation for the last two years to thwart Iran’s production of enriched uranium and forestall its development of a nuclear weapon. Researchers at Dimona set up a test bed composed of the Siemens system and the same IR-1 nuclear centrifuges (also known as P-1 centrifuges) used at Natanz to gauge Stuxnet’s effect on them. The malware was discovered in the wild last June infecting systems in Iran and elsewhere, and last November, Iran acknowledged that malicious software had sabotaged centrifuges at Natanz. Threat Level has already reported extensively on how Stuxnet worked and on clues that were previously uncovered that suggested Israel was behind the attack. Although it’s long been suspected that the United States played a key role, if not the lead role, in creating the malware, there’s been no definitive evidence. The Times story falls short of delivering that evidence, but Threat Level has been tracking the same story for months, and it’s worth fleshing out the report with additional details. To back claims that the Idaho National Laboratory likely played a role in Stuxnet, the Times reports that in early 2008, Siemens worked with INL to identify vulnerabilities in the specific control system that Stuxnet targeted – Siemens’ PCS 7, or Process Control System 7. The project was initiated by the Department of Homeland Security. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Siemens told the Times that the research was part of a routine program to identify vulnerabilities in various critical infrastructure systems and find ways to secure them. The INL also said the research was part of a larger project and would not comment on whether information it learned about the Siemens system during these tests was passed to intelligence services. But let’s look at the time frame and context of these tests. The INL began setting up a test lab to research industrial-control systems in 2002 after U.S. officials became concerned that al-Qaida might be investigating methods to conduct cyberattacks against critical infrastructure systems in the United States. In 2001, following the 9/11 terrorism attacks, a local police detective in California began investigating what appeared to be a series of cyber-reconnaissance operations against utility companies and government offices in the San Francisco Bay Area. The surveillance appeared to come from computers in the Middle East and South Asia. The FBI and Lawrence Livermore National Laboratory got involved and discovered a nationwide pattern of digital surveillance being conducted at nuclear power plants, gas and electric facilities, as well as water plants. The intruders were particularly focused on examining industrial-control devices that allowed for remote access to systems operating critical infrastructures. In January and March 2002, U.S. forces in Afghanistan and Pakistan conducting raids on al-Qaida offices and compounds seized computers that provided further evidence that al-Qaida was investigating means to conduct cyberattacks against dams and other critical infrastructures. Three months later, INL contacted Joe Weiss, a control-systems expert who worked at the time for KEMA, an energy consulting firm , to come to Idaho to discuss creating an industry test bed to uncover vulnerabilities in SCADA systems, also known as Supervisory Control and Data Acquisition systems. As a result of these discussions, Weiss began helping INL work with SCADA vendors to provide INL with equipment and knowledge for research and testing. The research paid off. In 2004, INL presented the first demonstration of a remote SCADA hack at the KEMA Control Systems Cyber Security Conference in Idaho Falls. The purpose of the demonstration was to show that recently identified vulnerabilities in Apache software could be used to compromise a control system remotely. The attack was conducted from Sandia National Laboratory against a system at INL in Idaho Falls. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The attack was designed to show how firewalls and other traditional security systems would fail to guard against a remote intrusion. But it also demonstrated a man-in-the-middle maneuver that would hide the attacker’s malicious activity from employees monitoring display screens at the targeted facility -- something that Stuxnet later accomplished remarkably well. A second remote SCADA hack was demonstrated at the KEMA Control System Cyber Security Conference in 2006 in Portland, Oregon. This one was conducted by a different DoE lab, the Pacific Northwest National Laboratory. The attack involved compromising a secure VPN to change voltages on a simulated Olympic Peninsula electric system while, again, altering operator displays to conceal the attack. Then in February 2007, DHS got word of a potential vulnerability in industrial-control systems. If the vulnerability -- dubbed "Aurora" -- were exploited, DHS learned, it could result in physical damage to equipment. It was something that Weiss and a handful of other security experts had long worried about, but no one had ever actually seen it done. A month later, INL conducted a private test, called the Aurora Generator Test, that successfully demonstrated the vulnerability. The test involved a remote attack using dial-up modem on an industrial-control-system generator, which left the generator a spinning mess of metal and smoke. The proof-of-concept demonstration showed that a remote digital attack could result in physical destruction of a system or components. The vulnerability, and measures to mitigate it, were discussed in closed sessions with the NERC Critical Infrastructure Protection Committee. Word about the test leaked out and in September that year, the Associated Press published a video of the demonstration showing a generator emitting smoke after being hacked. All of these demonstrations served to establish that a remote stealth attack on an industrial-control system was entirely feasible. The timing is important, because by early 2008, Iran was busy installing centrifuge cascades in module A26 at the Natanz enrichment plant -- the module that experts believe was later targeted by Stuxnet. At the same time, in early 2008, President George Bush authorized a covert program that was reportedly designed to subtly sabotage Iran’s nuclear weapons program. Details of the program were never disclosed, but the Times later reported that it was, in part, aimed at undermining the electrical and computer systems at Natanz. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Enter the Idaho National Laboratory. In March 2008, Siemens and INL researchers met to map out a vulnerability-test plan for the Siemens PCS7 system, the system that was targeted by Stuxnet. INL had tested Siemens SCADA systems previously but, according to Weiss, this is believed to be the first time INL was examining the Siemens PLC. In May, Siemens shipped a test system from Germany to the Idaho Falls lab. That same month, the DHS became aware of a vulnerability in the firmware upgrade process used in industrial-control systems. Firmware is the resident software, such as an operating system, that comes installed on a piece of hardware. In order to ease maintenance and troubleshooting of systems, vendors like to install patches or upgrades to software remotely, but this can expose the system to attack if the upgrade process has a vulnerability. A vulnerability was found, which DHS dubbed “Boreas.” DHS issued a private alert – which was later inadvertently made public -- saying that the vulnerability, if exploited, "could cause components within the control system to malfunction or shut down, potentially damaging the equipment and/or process." Stuxnet, it turns out, involved a type of remote firmware upgrade to the Siemens PLC, since it involved injecting malicious code into the ladder logic of a PLC. Boreas in retrospect, says Weiss, who is currently an independent consultant with Applied Control Systems and the author of Protecting Industrial Control Systems , showed that the concept of injecting code into the ladder logic was feasible. “The Boreas alert never specifically discussed ladder logic or PLCs,” says Weiss. “But it showed that if you can remotely change firmware, you can cause real problems.” Two months later, Siemens and INL began conducting research and tests on the Siemens PCS7 system to uncover and attack vulnerabilities in it. By November, the researchers had completed their work and delivered their final report to Siemens in Germany. They also created a PowerPoint presentation (.pdf) to deliver at a conference, which the Times mentions. What the Times doesn’t say is that German researcher Ralph Langner, who has done some of the best research on Stuxnet and was the first to suggest that Iran's nuclear program was Stuxnet's target, discovered the PowerPoint presentation on Siemens’ website last year. After Langner blogged about it in December suggesting the tests might have been connected to Stuxnet , Siemens removed the presentation from the web, but not before Langner downloaded it. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg In June 2009, seven months after INL and Siemens completed their report, the first sample of Stuxnet was found in the wild. The code was found by the Russian computer-security firm Kaspersky, although no one at Kaspersky knew at the time what they possessed. That sample, now known as “Stuxnet Version A,” was less sophisticated than Version B of Stuxnet, which was later discovered in June 2010 and made headlines. Version A was picked up through Kaspersky’s global filtering system and sat in obscurity in the company’s malware archive until Version B made headlines and Kaspersky decided to sift through its archive to see if any samples of Stuxnet had been vacuumed up earlier than 2010. Kaspersky researcher Roel Schouwenberg told Threat Level the company was never able to pinpoint geographically where the 2009 sample originated. At the time Version A was discovered in June 2009, there were 12 centrifuge cascades in module A26 at Natanz that were enriching uranium. Six others were under vacuum but not enriching. By August, the number of A26 cascades that were being fed uranium had dropped to 10, and eight were now under vacuum but not enriching. Was this the first indication that Stuxnet had reached its target and was beginning to sabotage centrifuges? No one knows for certain, but in July of that year, the BBC reported that Gholam Reza Aghazadeh, the long-time head of Iran’s Atomic Energy Organization, had resigned after 12 years on the job. The reason for his resignation was unknown. But around the same time that he resigned, the secret-spilling site WikiLeaks received an anonymous tip that a “serious” nuclear incident had recently occurred at Natanz. Over the next months, while the world was still ignorant of Stuxnet’s existence, the number of enriched centrifuges operational in Iran mysteriously declined from about 4,700 to about 3,900. The decline began around the time Version A of Stuxnet was captured by Kaspersky’s filter. By November 2009, the number of enriching cascades in module A26 specifically had dropped to six, with 12 cascades under vacuum, according to the International Atomic Energy Agency (IAEA), which issues quarterly reports on Iran’s nuclear programs. Between November 2009 and January 2010, module A26 suffered a major problem, with at least 11 cascades directly affected. During this period, Iran decommissioned or replaced 1,000 IR-1 centrifuges of the total 8,692 it had installed. Iranian officials have never explained to the IAEA what problem occurred with these 1,000 centrifuges. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Despite this apparent mishap, the rate of low enriched uranium (LEU) production in Iran increased significantly during this same period, and remained high for months afterward, though the rate was still far below what the IR-1 centrifuges are designed to produce, according to the Institute for Science and International Security (ISIS). In June 2010, an obscure security firm in Belarus discovered Stuxnet Version B on a system belonging to an unnamed client in Iran. Within a couple of months, Stuxnet had spread to more than 100,000 computers, most of them in Iran. It took weeks of research for experts to reverse-engineer the code and determine that it was targeting a very specific facility and that its primary aim was to subtly sabotage that facility by altering the frequency of something at the facility. The malware was designed to alter these frequencies over an extended period of time, suggesting the goal was to damage something but not completely destroy it in an obvious way that would draw attention. Last month, ISIS revealed that the frequencies programmed into Stuxnet’s code were the precise frequencies that would have been needed to sabotage the IR-1 centrifuges at Natanz. Photo: A security man stands next to an anti-aircraft gun as he scans Iran's nuclear enrichment facility in Natanz, 300 kilometers (186 miles) south of Tehran, Iran, in April 2007. Hasan Sarbakhshian/AP See also: Report Strengthens Suspicions That Stuxnet Sabotaged Iran's Nuclear Plant Iran: Computer Malware Sabotaged Uranium Centrifuges New Clues Point to Israel as Author of Blockbuster Worm, Or Not Clues Suggest Stuxnet Virus Was Built for Subtle Nuclear Sabotage Blockbuster Worm Aimed for Infrastructure, But No Proof Iran Nukes Were Target SCADA System's Hard-Coded Password Circulated Online for Years Simulated Cyberattack Shows Hackers Blasting Away at the Power Grid X X Topics cybersecurity hacks Israel malware stuxnet threats Threat Level Lily Hay Newman Andy Greenberg Matt Burgess Dhruv Mehrotra Lily Hay Newman Lily Hay Newman Justin Ling Andy Greenberg Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Why the Password Isn't Dead Quite Yet | WIRED"

"https://www.wired.com/story/passwords-not-dead-yet-authentication"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Lily Hay Newman Security Why the Password Isn't Dead Quite Yet The technology is in place. But the passwordless future isn't fairly distributed or easily embraced. Illustration: Elena Lacey Save this story Save Save this story Save There are certain sci-fi promises the future is supposed to hold: jetpacks , flying cars , a Mars colony. But there are also some seemingly more attainable goals that somehow also always feel just on the horizon. And one of the most tantalizing is the end of passwords. The good news is that the infrastructure—across all the major operating systems and browsers—is largely in place to support passwordless login. The less-good news? You're still plugging passwords into multiple sites and services every day, and will be for a while. There's no doubt that passwords are an absolute security nightmare. Creating and managing them is annoying, so people often reuse them or choose easily guessable logins—or both. Hackers are more than happy to take advantage. By contrast, passwordless logins authenticate with attributes that are innate and harder to steal, like biometrics. No one's going to guess your thumbprint. You likely already use some version of this when you unlock your phone, say, with a scan of your face or your finger rather than a passcode. Those mechanisms work locally on your phone and don't require that companies store a big trove of user passwords—or your sensitive biometric details—on a server to check logins. You can also now use stand-alone physical tokens in certain cases to log in wirelessly and without a password. The idea is that, eventually, you'll be able to do that for pretty much everything. “All the building blocks have reached a level of maturity where they can cross from early adopter technophiles to the mainstream,” says Mark Risher, Google's senior director of product management for identity and security platforms. “They have strong platform support, they work across all the different major providers, and they're becoming familiar to users. Before, we as an industry didn't even know how to get rid of passwords. Now it'll take some time, but we know how we're doing it.” “The problem is we have a dependance on a really poor foundation.” Andrew Shikiar, FIDO Alliance At the end of June, Microsoft's Windows 11 announcement included deeper integration of passwordless sign-ins, particularly for logging in to devices, using biometrics or a PIN. Similarly, Apple announced a few weeks earlier that its new iOS 15 and macOS Monterey operating systems will start to incorporate a new option called Passkeys in iCloud Keychain , a step toward using biometrics or device PINs to log in to more services. And in May, Google discussed its efforts to promote secure password management at the same time that it works to move customers away from passwords. Despite these and other industry efforts to get both developers and users on board with a passwordless world, though, two main challenges remain. One is that while passwords are universally despised, they're also deeply familiar and absurdly ubiquitous. It's not easy to break habits developed over decades. “It's a learned behavior—the first thing you do is set up a password,” says Andrew Shikiar, executive director of the FIDO Alliance, a longtime industry association that specifically works on secure authentication. “So then the problem is we have a dependance on a really poor foundation. What we need to do is to break that dependance.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It's been a painful detox. A FIDO task force has been studying user experience over the past year to make recommendations not just about passwordless technology itself but also about how to present it to regular people and provide them with a better understanding of the security benefits. FIDO says that organizations implementing its passwordless standards are having trouble getting users to actually adopt the feature, so the alliance has released user-experience guidelines that it thinks will help with framing and presentation. “‘If you build it they will come’ isn’t always sufficient,” Shikiar wrote last month. The second hurdle is even trickier. Even with all of those pieces in place, many passwordless schemes work only on newer devices and necessitate the ownership of a smartphone along with at least one other device. In practice, that's a fairly narrow use case. Many people around the world share devices and can't upgrade them frequently, or they use feature phones, if anything. And while passwordless implementations are increasingly standardized, account-recovery options are not. When security questions or a PIN serve as backup options, you're essentially still using passwords, just in a different format. So passwordless schemes are moving toward systems where one device you've previously authenticated can anoint a new one as trustworthy. “Let's say you leave your phone in a taxi, but you still have your laptop at home,” Google's Risher says. “You get a new phone and use the laptop to bless the phone and can kind of build yourself back up. And then when somebody finds your lost phone, it's still protected by the local device lock. We don't want to just shift the password problem onto account recovery.” It's certainly easier than keeping track of backup recovery codes on a slip of paper, but it again raises the issue of creating options for people who don't or can't maintain multiple personal devices. As passwordless adoption proliferates, these practical questions about the transition remain. The password manager 1Password, which naturally has a business interest in the continued reign of passwords, says it is happy to embrace passwordless authentication everywhere that it makes sense. On Apple's iOS and macOS, for example, you can unlock your 1Password vault with TouchID or FaceID instead of typing in your master password. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg There are some nuanced distinctions, though, between the master password that locks a password manager and the passwords stored inside of it. The trove of passwords in the vault are all used to authenticate to servers that also store a copy of the password. The master password that locks your vault is your secret alone; 1Password itself never knows it. This distinction makes passwordless login, at least in its current form, a better fit for some scenarios than others, says 1Password chief product officer Akshay Bhargava. He notes, too, that some long-standing concerns about password alternatives remain. For example, biometrics are ideal for authentication in many ways, because they literally convey your unique physical presence. But using biometrics widely opens up the question of what happens if data about, say, your fingerprints or face is stolen and can be manipulated by attackers to impersonate you. And while you can change your password on a whim—their single best quality as authenticators—your face, finger, voice, or heartbeat are immutable. It will take time and more experimentation to create a passwordless ecosystem that can replace all the functionality of passwords, especially one that doesn't leave behind the billions of people who don't own a smartphone or multiple devices. It's harder to share accounts with trusted people in a passwordless world, and tying everything to one device like your phone creates even more incentive for hackers to compromise that device. Until passwords are totally gone, you should still follow the advice WIRED has pushed for years about using strong, unique passwords, a password manager (there are lots of good options ), and two-factor authentication wherever you can. But as you see opportunities to go passwordless on some of your most sensitive accounts, like when setting up Windows 11 , give it a shot. You may feel a weight lifting that you didn't even know was there. 📩 The latest on tech, science, and more: Get our newsletters ! How to survive the worst tornado in US history This is what gaming does to your brain Windows 11's security push leaves scores of PCs behind Yes, you can edit sizzling special effects at home Reagan-Era Gen X dogma has no place in Silicon Valley 👁️ Explore AI like never before with our new database 🎮 WIRED Games: Get the latest tips, reviews, and more ✨ Optimize your home life with our Gear team’s best picks, from robot vacuums to affordable mattresses to smart speakers Senior Writer X Topics Passwords identity smartphones security Kate O'Flaherty Matt Burgess Lily Hay Newman Andy Greenberg Reece Rogers Andrew Couts Andy Greenberg Lily Hay Newman Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Bluetooth's Complexity Has Become a Security Risk | WIRED"

"https://www.wired.com/story/bluetooth-complex-security-risk"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Lily Hay Newman Security Bluetooth's Complexity Has Become a Security Risk Alyssa Foote Save this story Save Save this story Save Bluetooth is the invisible glue that binds devices together. Which means that when it has bugs, it affects everything from iPhones and Android devices to scooters and even physical authentication keys used to secure other accounts. The order of magnitude can be stunning: The BlueBorne flaw , first disclosed in September 2017, impacted 5 billion PCs, phones, and IoT units. As with any computing standard, there's always the possibility of vulnerabilities in the actual code of the Bluetooth protocol itself, or in its lighter-weight sibling Bluetooth Low Energy. But security researchers say that the big reason Bluetooth bugs come up has more to do with sheer scale of the written standard—development of which is facilitated by the consortium known as the Bluetooth Special Interest Group. Bluetooth offers so many options for deployment that developers don't necessarily have full mastery of the available choices, which can result in faulty implementations. "One major reason Bluetooth is involved in so many cases is just how complex this protocol is," says Ben Seri, one of the researchers who discovered BlueBorne and vice president of research at the embedded device security firm Armis. "When you look at the Bluetooth standard it’s like 3,000 pages long—if you compare that to other wireless protocols like Wi-Fi , for example, Bluetooth is like 10 times longer. The Bluetooth SIG tried to do something very comprehensive that fits to many various needs, but the complexity means it’s really hard to know how you should use it if you’re a manufacturer." Bluetooth, as you probably know from your portable speaker, wireless keyboard, or toothbrush, allows two proximal devices to connect to each other over the air. The pairing can last however long both devices are in use, as with a fitness tracker and smartphone. Or it can be temporary, a way of setting a device up or authenticating a user. Bluetooth Low Energy is a condensed version of the protocol for devices that have limited computing and power resources. "All of the details are buried in hundreds of pages of unreadable specifications." Matthew Green, Johns Hopkins University Fundamentally, both Bluetooth and BLE open up a channel for two devices to communicate—an extremely useful arrangement, but one that also opens the door for dangerous interactions. Without strong cryptographic authentication checks, malicious third parties can use Bluetooth and BLE to connect to a device they shouldn't have access to, or trick targets into thinking their rogue device is a trusted one. "The standard often describes a topic in a scattered way," says Syed Rafiul Hussain, a security engineering researcher at Purdue University. "And it often leaves the complex interactions of the protocol to the manufacturers, which is another source of vulnerability." Ken Kolderup, vice president of marketing at the Bluetooth SIG, says that the group is very aware of the challenge and importance of training developers to get a handle on Bluetooth's massive scope. He says the documentation is so extensive because the protocol doesn't only define a radio frequency layer for Bluetooth, but also has components at every layer of tech, from hardware up through applications, to guarantee interoperability between Bluetooth devices. "Bluetooth isn't just wireless audio streaming anymore. There's low power data transfer, mesh network; it’s a very broadened scope," Kolderup adds. "But security is obviously very important. The standard offers operational modes for everything from no security all the way up to 128 AES encryption or 'secure connections only' mode. We've put into it as much as the community has asked for." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg A recent example, though, helps illustrate how the process can break down. In February, researchers from the security firm McAfee reported Bluetooth Low Energy misconfiguration issues in a smart padlock known as BoxLock. The device had been designed to use a Bluetooth Low Energy configuration called "Just Works Mode," which lets devices pair without any passwords or other cryptographic protections. As a result, McAfee researchers could connect to any lock, analyze the device's BLE commands, and discern which gave the unlock order. Further, BoxLock had configured this command to be in read-write mode, so once the attackers knew what to target, they could initiate an unlock. BoxLock has since patched the vulnerabilities. BoxLock ran into two common Bluetooth issues. It deployed a relatively insecure version of it for a device—a lock—that demands heightened security. And it made life easier for hackers by leaving Bluetooth traffic out in the open. "The problem is that BoxLock used a very insecure implementation of BLE," says Steve Povolny, head of advanced threat research at McAfee. "I wouldn’t say that it's an insecure protocol by any means. Part of this is the fact that Bluetooth has not been as comprehensively studied by the security community as some things, and it's not as clear to vendors and manufacturers what the potential flaws are." Bluetooth has certainly been investigated to a degree, but researchers say that the lack of intense scrutiny historically stems again from just how involved it is to even read the standard, much less understand how it works and all the possible implementations. On the plus side, this has created a sort of security by obscurity, in which attackers have found it easier to develop attacks against other protocols and systems rather than taking the time to work out how to mess with Bluetooth. "I couldn't possibly give an informed opinion on the true security of Bluetooth, and I strongly suspect that the protocol designers couldn't either," says Matthew Green, a cryptographer at Johns Hopkins University. "That's because all of the details are buried in hundreds of pages of unreadable specifications. Many device manufacturers have engineered around this by designing their own security as a kind of 'add on' layer that they use over Bluetooth. This is probably wise, given what a mess the protocol itself has been." "We encourage people to use the max level of security your product can support." Ken Kolderup, Bluetooth SIG But in recent years, the Bluetooth standstill has begun to erode. After high-profile vulnerabilities like BlueBorne, researchers are increasingly focused on raising awareness about Bluetooth implementation and configuration issues. And attackers are starting to consider Bluetooth as a real option for launching attacks. On Monday, for example, the security firm Kaspersky Lab published findings about a Korean-speaking threat actor with potential state ties that has built a Bluetooth scanner into its Windows malware, seemingly to scan for potentially exposed Bluetooth devices. The Bluetooth SIG says it is considering a next generation of resources for developers, including the possibility of creating a security audit tool that coders can use to check their Bluetooth implementations. And the SIG's Kolderup says that the consortium encourages scrutiny of the specification and input about potential vulnerabilities and how to improve its overall security. The SIG is also working to do a better job publicizing existing resources on secure Bluetooth implementation, like the National Institute of Standards and Technology's guide. "More and more devices are becoming interconnected, and that all of a sudden brings a whole other set of challenges that you need to be aware of when you’re creating a product," he says. "We encourage people to use the max level of security your product can support. We encourage you to lock it down." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Researchers emphasize that the risks of Bluetooth security—and potential rewards for malicious hackers—are only growing as Bluetooth spreads from being used largely in consumer settings, like smart home devices and wearables, to being adopted more and more by enterprises and governments for large-scale deployment in corporate offices, hospitals, and industrial control environments. "Bluetooth is being used for smart keys, for sensitive encryption and authentication," Armis' Seri says. "and also just anything from connected medical devices to wireless infrastructure. All kinds of stuff in business environments where this is a way in and it isn’t monitored. It isn’t secured." Researchers say that more tools and training resources from the Bluetooth SIG would go a long way toward making Bluetooth implementation more manageable. In the meantime, whenever you're not using Bluetooth? Just turn it off. Thinking of buying a new camera? Go mirrorless The first Windows XP patch in years is a very bad sign The comedian is in the machine: AI is learning puns My search for a boyhood friend led to a dark discovery Kitty Hawk, flying cars, and the challenges of “going 3D” 📱 Torn between the latest phones? Never fear—check out our iPhone buying guide and favorite Android phones 📩 Hungry for even more deep dives on your next favorite topic? Sign up for the Backchannel newsletter Senior Writer X Topics Bluetooth cybersecurity Dell Cameron Kate O'Flaherty Dell Cameron Dell Cameron Dell Cameron Lily Hay Newman Matt Burgess Andy Greenberg Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"The Bruce Willis Deepfake Is Everyone’s Problem | WIRED"

"https://www.wired.com/story/bruce-willis-deepfake-rights-law"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Will Bedingfield Culture The Bruce Willis Deepfake Is Everyone’s Problem Photograph: yipengge/Getty Images Save this story Save Save this story Save Application Deepfakes Regulation End User Big company Small company Sector Entertainment Video Source Data Biometric Speech Video Technology Machine learning Machine vision Jean-Luc Godard once claimed, regarding cinema, “ When I die, it will be the end. ” Godard passed away last month; film perseveres. Yet artificial intelligence has raised a kindred specter: that humans may go obsolete long before their artistic mediums do. Novels scribed by GPT-3 ; art conjured by DALL·E —machines could be making art long after people are gone. Actors are not exempt. As deepfakes evolve, fears are mounting that future films, TV shows, and commercials may not need them at all. Not even Bruce Willis. Last month the actor had the strange experience of “appearing” in an ad where he was tied to a bomb on the back of a yacht, growling "Mississippi" in a Russian accent. The Telegraph reported the deepfake was possible because he sold his performance rights. That wasn't quite true—a representative for Willis later told reporters the actor had done no such thing. And as my colleague Steven Levy wrote a few days ago , the company who made the ad—the cheekily named Deepcake—never claimed to hold Willis' future rights, but had struck a deal that allowed the company to map a digital version of his appearance onto another actor in a commercial for the Russian cell network Megafon. Yet the question of “who owns Bruce Willis,” as Levy put it, isn’t only a concern for the Hollywood star and his representatives. It concerns actors unions across the world, fighting against contracts that exploit their members' naivety about AI. And, for some experts, it's a question that implicates everyone, portending a wilder, dystopian future—one in which identities are bought, sold, and seized. In America, explains Jennifer Rothman, author of The Right of Publicity: Privacy Reimagined for a Public World , people have a right under various state laws to limit unauthorized appropriation of their identities, particularly their names and likenesses. The scope of protection varies state by state. Some have statutes protecting the “right of publicity” (a law barring unauthorized use of a person’s name, likeness, voice, or other indicia of identity without permission, usually for a commercial purpose), while others offer these safeguards through common, or judge-made, laws. A few have both statutory and common law protections. The devil is in the details, though. "A private individual or company that simply creates a deepfake of a person, without more, does not obviously run afoul of the right of publicity," explains David A. Simon, a research fellow at Petrie-Flom Center at Harvard Law School. In other words, if a Willis deepfake appears in an American ad for potato chips, then a claim becomes viable; if someone deepfakes Willis’ yippie-ki-yay swagger into a home movie and throws it on YouTube, the actor may not have much of a case. Under certain circumstances, deepfake makers are protected by the First Amendment. As one Northwestern University paper put it last year, “the government cannot prohibit speech merely because the speech is false; there must be some additional problem,” like defamation. “The right of publicity requires the commercial appropriation of identity while tort law does not always require a commercial element,” explains Simon. “If an actor's deepfake is manipulated to portray someone in a defamatory manner, or used to defame someone else, the actor may have the ability to sue in tort." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Actors unions have been fretting over deepfakes for decades. The Screen Actors Guild—American Federation of Television and Radio Artists (SAG-AFTRA)’s interest began with sports video games, which started generating their own image rights controversies back in 2013. Even just looking at the rudimentary and blocky depictions of athletes in video games it was clear that the tech would develop in a way that would make it possible to drop actors into movies as easily as developers could drop quarterbacks into Madden. In a landscape of desperate actors, confusing contracts, and multivarious laws, it doesn't take an agile mind to grasp that SAG-AFTRA has its work cut out. The wrong consent given to the wrong company can lead to pretty much any nightmare the mind can weave. Remember that episode of Friends where Joey ended up in an STD advert after a spot of seemingly innocuous modeling? It’s like that, except, in some cases, Joey wouldn't have to model at all. In his (fictional) story, everything was fine at the end of the half-hour, but a different (real) actor could find it hard to get work after being deepfaked into an unflattering or controversial role. And it’s no longer just a problem of visual depiction: Deepfakes allow an actor to be “used,” in Simon’s words, with words quite literally put into their mouths. (TikTok had to settle a legal case recently around this very issue. ) “This is relevant not just to AI contracts [for synthetic performances], but any contract involving rights to one’s likeness and voice,” says Danielle S. Van Lier, assistant general counsel, intellectual property and contracts at SAG-AFTRA. “We have been seeing contracts that now include ‘simulation rights’ to performers’ images, voices, and performances. These contract terms are buried deep in the boilerplate of performance agreements in traditional media.” Yet, and here’s the rub, actors also see the rise of deepfakes as a chance to cash in. “While many never become ‘famous,’ their names, voices, images or likenesses still attain commercial value,” explains Van Lier. The commercial opportunities of synthetic performances–an actor’s voice used in an automated audiobook or appearance as a digital avatar, abound, hence why SAG-AFTRA is pushing away from the term deepfakes–and its association with porn–to terms like “digital double” or “AI-generated.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg This is where the importance of “transferability” of publicity rights comes in: A law passed in New York in 2020, for instance, allows postmortem rights to be transferred. “The ability to license and convey this property interest provides an important source of revenue to these professionals and their families,” says Van Lier. “Licensing allows creative professionals to work with entities and individuals with technological, financial and legal expertise, and to maximize the value of the asset.” It’s crucial to understand here that transferability isn’t about authorizing uses of your identity for money; it’s about ownership, your identity conceived of as a transferable property right, like patents or copyrights, able to be bought and sold. “It affects whether the right over a person's identity is transferred (and taken away) from them and owned by a third party,” says Rothman. For some experts, this transferability could lead to people losing control of their “personality” as firms take full ownership of their identity rather than just a licensed use for a particular purpose. In fact, the original calls for these kinds of transferability were made in the 1950s by studio lawyers who wanted to control the movies that actors appeared in and the products they endorsed. “One might (potentially) garner more money for such a total transfer, but the cost seems inconceivably great to the person and society,” Rothman says. Student athletes , for instance, risk agents, managers, companies, or even the NCAA hoovering up their identities in the hope of extracting any future profit if they find big-league success. Actors, athletes, and average citizens, Rothman argues , are in danger of losing control of their "own names, likenesses, and voices to creditors, ex-spouses, record producers, managers, and even Facebook." Many actors won’t be affected, simply because their identities won’t be valuable. But it is also true that celebrities like Kim Kardashian and Tom Cruise have bargaining power that others don’t: They can bullishly negotiate that the use of their image not extend beyond any particular show or film. Smaller actors, meanwhile, face the possibility of contracts that extract rights wholesale. "There is a real risk that new actors (i.e., just starting out and desperate for breakthrough work) would be especially vulnerable to signing away their publicity rights as a condition of their first contracts," says Johanna Gibson, a professor of intellectual property law at Queen Mary, University of London. "This power imbalance could be exploited by studios keen both to commercialize image and character and indeed to avoid libel (depending upon the nature of that commercialization), as the performer would no longer have rights to control how their image is used." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg This could leave actors in a position of either missing out on work, or signing a contract that would later allow them to be deepfaked into content they find demeaning without legal recourse. In the film franchise model, Gibson argues, the risk is even greater. SAG-AFTRA disagrees, explaining that reasonable minds will always differ, even when working toward the same stated goal. “While some prominent commentators have expressed fear that a transferable right of publicity could lead to involuntary transfers or forced commercialization, there is little basis to believe this fear would come to fruition,” says Van Lier. ”There are no instances, to our knowledge, of the right being involuntarily transferred during anyone’s lifetime or anyone being forced to exploit it. The most notable attempt involved OJ Simpson and the court expressly refused to transfer it to his victim’s family.” Eventually, AIs trained on Bruce Willis’ likeness won't need Bruce Willis at all. “If a company can train its AI algorithms to replicate the specific mannerisms, timing, tonality, etc. of a particular actor, it makes the AI-generated content more and more life-like,” says Van Lier. “This can have long-term implications.” In other words, actors—and everyone else—must learn how to protect their digital rights, or they could find themselves performing a role they did not expect. You Might Also Like … 📧 Find the best bargains on quality gear with our Deals newsletter “ Someone is using photos of me to talk to men” First-gen social media users have nowhere to go The truth behind the biggest (and dumbest) battery myths We asked a Savile Row tailor to test all the “best” T-shirts you see in social media ads My kid wants to be an influencer. Is that bad? 🌞 See if you take a shine to our picks for the best sunglasses and sun protection Staff writer X Topics hollywood ethics Deepfakes Kate Knibbs Reece Rogers Megan Farokhmanesh Geek's Guide to the Galaxy Simon Hill Elana Levin Jason Parham Megan Farokhmanesh Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"You Can Go Home, and This Time Be the Hero | WIRED"

"https://www.wired.com/story/you-can-go-home-this-time-you-can-be-the-hero"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Mike McClelland Culture You Can Go Home, and This Time Be the Hero Marvel's Spider-Man: Miles Morales Courtesy of Insomniac Games Save this story Save Save this story Save I’m weaving my way down the streets of Manhattan when I stumble upon it rather suddenly: my old apartment, right at the corner of 8th Avenue and 23rd street. I’m astonished at how similar it looks. Of course, the burger restaurant that was here 10 years ago isn’t here anymore, replaced by a foggy-windowed shop called White’s Bookshop Café. The movie theater next door, with those giant speakers that made our apartment shake every time a blockbuster reached its climax, is missing, too, replaced by Tom’s Cuts and Rapid’s Dry Cleaning. But the bricks are the same shade, the building the same height, the sunlight slanting down 8th Avenue the same sunlight that made me feel like a movie star every time I walked out our front door. I think back to who I was then, when I lived here: drinking too much, hating my job where I was always “the gay one” and where my clients–oil companies, pharmaceutical giants, chemical empires—were literal evildoers. This time, things are different. I’m here to fight the evildoers. I turn and run up the face of the building, only pausing when I reach the top, where I can peer down and search for signs of crime. Did I mention I’m Spider-Man? More specifically, I’m Miles Morales. I’m playing Spider-Man: Miles Morales , which builds on its predecessor’s legendary re-creation of Manhattan. Insomniac Games’ achievement is a true marvel; I truly feel like I’m in the game’s New York but also in my own New York. Being here (there, then) inside the game gives me a little twist, right in my chest. The ache of nostalgia. But there’s something else there too. The familiarity of it is, of course, exciting. When a video game world mimics our own, it becomes a kind of digital scrapbook. A more interactive version of Google Street View. When I played Sleeping Dogs , I ventured up to my old Hong Kong apartment. I did the same in Watch Dogs ’ Chicago, and it was such a vivid depiction that I had nightmares about my horrible Chicago boss. I used Assassin's Creed II to make my husband show me what part of Florence he'd lived in before we met. I've even lingered around in games that I didn't necessarily vibe with, just to let nostalgia waft over me. I couldn't quite get into Persona 5 (because thinking about high school gives me panic attacks), but simply lurking about Shibuya took me back to a Christmastime visit to Tokyo in 2006, and it made me remember how young and full of wonder I was back then. But this “something else” is more than that. Think about it: In almost every video game, what is the objective? With rare exceptions, the goal is to win. The goal is to be a hero. The hero. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Every time I visit a gaming world that is based on a “real-world” location, I get to feel what it’s like to be the hero there. The star. The winner. I spent much of the first 30 years of my life being bullied. I’m a loud, tall gay man from rural Pennsylvania. I was made fun of for being gay before I knew what being gay was. I survived that, but I didn’t realize the bullies would follow me into my twenties. I went to London for graduate school, and then, in my first job in advertising in Old Blighty, my team had their own “Mike Voice” they would use to mimic me, even when I was just a desk away. This voice came with a lisp and incredible wrist dexterity. It turns out that these creatives weren’t very creative at all. Cruelty about my sexuality, my background, my appearance, my sound, my choices, my everything followed me around the world, from my job in London to jobs in Johannesburg, Cape Town, Hong Kong, New York, Chicago, and Atlanta. I grew strong, but I certainly never felt like a hero. I didn’t feel like I was winning. Like many gamers, many who have it far worse, I escaped my bullies in video game worlds. But by turning the real world into levels, worlds, and playgrounds, game developers give players like me a chance to return to locations where we were the underdogs and give us the agency to finally win. There’s more to these new spins on real places than simply mimicking the real world. It’s not just a digital Madam Tussaud’s, and there’s more to it than simply reminiscence. I spoke with Gavin Goulden, an art director at Insomniac Games, who worked on Spider-Man and Spider-Man: Miles Morales. He said that one of their goals when creating their version of Manhattan was for it to feel familiar and relatable to those who live in the city, those who have visited, or even those who have seen it from afar. One thing that really struck me was how Goulden described his team’s goals for creating their version of Harlem, where Miles lives in the game. “We had also wanted to enforce a sense of home in our Harlem neighborhood, where Miles Morales now lives,” Goulden said. “This included spotlighting the rich culture in the area to ensure that it felt relatable and was a welcoming place to explore as a new hero.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg This care and relatability, the comfort of finding a “home” in a gaming world, is what gives players the wings to fly in these new versions of our own worlds. I love the idea of the developers creating a sense of home for us to feel comfortable in as we, as Miles, test out what it means to be a new hero. When I played Pilotwings 64 back in the late '90s, I would use my jetpack to fly to the small corner of the US where I grew up, right at the edge of Lake Erie, and I’d look down at the pixelated, camo-colored blob representing my hometown of Meadville, Pennsylvania. (To be honest, it was a pretty accurate representation.) And I remember being so boggled and so thankful that the game studio, Paradigm Simulation, had decided to include my little corner of the world in their game. I felt seen and included. I felt free, in a way, now that I was able to soar above a place that was holding me down. Of course, it was easy to imagine my version of Meadville there because console technology wasn’t advanced enough for the developers to even try. But now, there are games that can recreate our cities right down to the apartment. No matter where you live, you can find it in a game. For example, in Microsoft’s Flight Simulator, you can land anywhere in the world courtesy of Bing Maps and a fancy algorithm that makes everything 3D. I’d argue that even Flight Simulator offers gamers a level of control that they may not have in the “real” world. How wonderful to soar above your small town, how incredible to fly–direct–from Meadville to Buenos Aires, to Accra, to Tokyo? And, of course, the pandemic brought another angle to this situation. Even for the places that don’t quite traverse the uncanny valley, there is a uniquely satisfying sadness that comes from visiting a real-world place in a video game. If you've lived there, or visited there, or even wanted to visit these places in "real" life, you might have a longing for them that is simultaneously inflamed and eased by going to their video game versions. We are slowly emerging, perhaps, from a time when we couldn’t safely travel anywhere, let alone to cherished places. The pandemic certainly made this kind of armchair traveling more satisfying. It enabled us to visit places that were temporarily lost to us. How wonderful that games could give us this, the chance to visit places from our past and our future and to ache for them. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg All of this reminds me of a beloved film from my childhood, Labyrinth. In the film, Jennifer Connelly’s Sarah somehow ends up back in her bedroom, even though she was, just moments before, deep in the heart of the titular labyrinth. The Junk Lady shows up and starts offering her keepsakes from her childhood, reminding her of how much she loves the toys in her room. But Sarah has a nagging feeling that something is wrong, that it is impossible for her to be in her bedroom. Soon she realizes that she isn’t in her bedroom but rather in a pile of garbage spun into an illusion of her home. The walls crash down around her. She tears them down. Today, the quality of game worlds is so high and their evolution so rapid that it is a certainty that video games will soon allow us to more thoroughly traverse re-creations or reimaginings of our old haunts. We will be able to, like Sarah, visit an immaculate re-creation of our own bedrooms. This time, though, we won’t have to contend with bullies, with rules, with being trapped in small towns or disliked for who we are or how we like. We will be able to break down the walls of the past, we’ll be able to change what was unchangeable, we will be able to pick up our swords and venture out. And this time, we’ll be heroes. 📩 The latest on tech, science, and more: Get our newsletters ! The little-known genius who helped make Pixar possible Why Tesla is designing chips to train its self-driving tech Tips for learning to type with one hand What makes an artist in the age of algorithms? Pigeons, curves, and the traveling salesperson problem 👁️ Explore AI like never before with our new database 🎮 WIRED Games: Get the latest tips, reviews, and more 💻 Upgrade your work game with our Gear team’s favorite laptops , keyboards , typing alternatives , and noise-canceling headphones Contributor X Instagram Topics video games gaming culture nostalgia Megan Farokhmanesh Matt Kamen Reece Rogers Megan Farokhmanesh Megan Farokhmanesh Boone Ashworth Megan Farokhmanesh Geoffrey Bunting Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"'Ratchet & Clank: Rift Apart' Ups the Ante on Accessibility | WIRED"

"https://www.wired.com/story/ratchet-and-clank-insomniac-sony-accessibility"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Grant Stoner Culture Ratchet & Clank: Rift Apart Ups the Ante on Accessibility For Ratchet & Clank , Insomniac Games utilized techniques and tools from Marvel’s Spider-Man: Miles Morales as a starting point to create features that could benefit disabled individuals. Courtesy of Insomniac Games Save this story Save Save this story Save During a recent PlayStation State of Play broadcast, Insomniac Games’ Ratchet & Clank: Rift Apart took center stage, showcasing approximately 16 minutes of gameplay. While the presentation had the standard hallmarks of a game demo, highlighting graphical improvements, new mechanics, and a synopsis of the latest story, we also unexpectedly got a brief display of menus featuring a variety of accessibility options. That acknowledgment of those who will benefit from accessible features indicates that the industry is continuing to listen to disabled voices. Insomniac Games’ latest title is not the studio’s first foray into the field of game accessibility. In fact, numerous developers owned by Sony Interactive Entertainment (SIE) have dabbled in creating inclusive virtual environments for disabled players. As Sam Thompson, manager and senior producer at SIE notes, once development studios start the task of implementing accessibility into their games, future titles can focus on improving shortcomings. “Take Naughty Dog for example: Uncharted 4: A Thief’s End was the studio’s first title that contained formal accessibility features,” Thompson says. “The game shipped with 37 accessibility options in total, including a host of new features like a dedicated accessibility menu. If you fast-forward to The Last of Us Part II , Naughty Dog increased that to over 60.” Uncharted 4 , released in 2016, provided Naughty Dog with several years of experience to hone its skills in developing accessibility features. Rather than restart the arduous task of creating an accessible game, PlayStation studios continuously update portfolios with options that are proven to work. Not only does this create a relatively smooth transition between titles, it also ensures an ever growing list of development tools when mistakes inevitably happen. “There will always be challenges, and with each new product comes a host of new and unique bespoke features or gameplay elements that will require all-new accessibility features to support them. But this approach means we can focus on innovation rather than retreading old ground working with problems that we already solved,” Thompson says. For Ratchet & Clank , Insomniac Games utilized techniques and tools found in Marvel’s Spider-Man: Miles Morales as a starting point to create features that could benefit disabled individuals. One of the accessibility features in Spider-Man lets players reduce the number of button inputs required for specific moves. However, the latest Ratchet & Clank does not feature as many buttons as other titles within the studio’s catalog. Michelle Zorrilla, advanced senior user experience researcher at Insomniac Games, explains that the groundwork for accessibility was already there, but new features needed to be fine-tuned to fit this specific game. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “Instead, the team approached it from a gameplay perspective to see what situations or controls would benefit from a shortcut,” Zorrilla says. “Some situations could be addressed by offering toggles (like opening the Weapon Wheel or aiming), but successive presses like jumping and slamming your weapon or holds like gliding were good candidates to offer as a single press.” Aside from the challenge of implementing toggling versus holding on specific actions, developers were faced with the task of meeting each disabled individual’s specific needs. While more studios are adopting accessibility practices, features and settings can only accommodate so much. Each disability is unique, and people with the same disability may have big differences in strength, vision, or hearing. As a result, Insomniac Games devised a new feature specific to Ratchet & Clank that could help alleviate physical and cognitive exhaustion. “We were initially discussing how to handle each individual situation, which eventually turned into a global Game Speed option that could be used in any situation, and shortcuts seemed like the best way to allow for player control over speed and timing,” Zorrilla says. “This created a new challenge, as adding three different game speeds meant they all had to be tested, and both our Development Support team and PlayStation Studios QA were instrumental in making this happen.” These initiatives in accessibility are not exclusive to PlayStation. Both Microsoft and Nintendo have hardware, software, or documentation to help foster inclusivity amongst internal studios. For example, in 2020, Xbox launched the Xbox Accessibility Guidelines (XAGs) to encourage consistency across all platforms. While not necessarily a rigid checklist that must be strictly followed, this list allows developers to continuously track the accessibility performance of a game through each stage of development, ensuring that their games do not lack crucial features. For PlayStation, studios and developers have their own iteration of the guidelines, with the first version created in 2015. Mark Friend, lead user researcher at SIE, acknowledges that guidelines such as these not only raise awareness but allow for consistent accessibility. “The original document was an important moment, as it helped to put accessibility in front of people at a time when it was a much less common topic of conversation in game development, and it provided a great resource for developers who wanted to know more about the subject,” Friend says. “It’s also been important for us to work with developers across PlayStation Studios to inform newer iterations of the accessibility guidelines, to make sure that what we outline is achievable.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg And with Ratchet & Clank as proof, accessibility features can be incredibly unique to a specific game, despite coming from the same studio. “There’s more to accessibility in game development than just following suggested guidelines,” says Friend. “While there are general best practices that can carry over between games, every game released by PlayStation Studios is different, so our goal is always to ensure that we tailor our support to our studios and their games. Our suggested guidelines provide a great baseline of knowledge, but we also want to ensure that our studios are free to explore new and innovative ways of making their games more accessible.” The addition of accessibility features within a game does not require a AAA studio with hundreds of employees. And regardless of development size, accessibility is best tackled at the beginning of projects. Friend also advises developers to include disabled players as testers, to ensure that those features and options work for them. Aside from the logistical aspect of designing a game, the inclusion of accessibility features and options comes from a commitment to letting everybody play. No one should be excluded because of their abilities, and as Sam Thompson argues, hearing directly from disabled people how beneficial and important accessibility can be is not only rewarding but assuring as a developer. “Empathy is the most powerful tool in your arsenal. With it you can accomplish more than you ever thought possible. It’s absolutely astonishing how effective and motivating it can be when members of the A11Y community drop by the studio to share their perspectives and inspire your team to see things differently. You’ll be surprised at just how impactful this will be for your team.” 📩 The latest on tech, science, and more: Get our newsletters ! How Roblox became a playground for virtual fascists The US government is finally moving at the speed of tech You're probably not using the Web's best browser Let users own the tech companies they help build This robot spies on creatures in the ocean's "twilight zone" 👁️ Explore AI like never before with our new database 🎮 WIRED Games: Get the latest tips, reviews, and more 💻 Upgrade your work game with our Gear team’s favorite laptops , keyboards , typing alternatives , and noise-canceling headphones Contributor X Topics video games gaming culture accessibility developers Sony Geoffrey Bunting Boone Ashworth Simon Hill Geek's Guide to the Galaxy Reece Rogers Megan Farokhmanesh Elana Levin Jason Parham Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"This Marvel Game Soundtrack Has an Epic Origin Story | WIRED"

"https://www.wired.com/story/guardians-of-the-galaxy-marvel-game-soundtrack"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Mat Ombler Culture This Marvel Game Soundtrack Has an Epic Origin Story Photograph: Square Enix Save this story Save Save this story Save Richard Jacques says he had to pinch himself when he got the call to score Marvel's Guardians of the Galaxy game. Not least because way back in 2005, at a video game concert in Los Angeles, Jacques ended up meeting the man responsible for creating the characters and stories that have made such a lasting impression on him: Stan Lee. And in typical superhero style, it was there that Jacques made a wish that would become reality 12 years later. “I was introduced through a mutual friend and only had a brief chat with him, but [Lee] was explaining how music is a really important part of his stories,” Jacques tells WIRED with a massive smile on his face from his studio in the UK. Marvel encyclopedias, comics, and figurines make up just as much of the furniture here as the massive mixing desk, old-school synths, and score sheets from previous projects. “I jokingly said to him, ‘One day, I’m going to do a Marvel soundtrack!’ So when I got the call back in 2017 and signed the NDA, as soon as I found out what the project was I was just blown away. It’s the stuff that dreams are made of, but straight away I knew I’d be the right fit for the project.” The BAFTA-nominated video game composer lives and breathes comic books. If he ever found himself onboard Star-Lord’s ship, he’d be able to take the wheel and navigate the multiverse with his eyes closed. When it came to the pitching process for scoring Guardians , the game’s senior audio director, Steve Szczepkowski, says he didn’t need to any help seeing Jacques’ merits. “Just his presentation alone was enough,” Szczepkowski laughs over a video call. “[Richard] came in with this Guardians cassette side A and side B folder, so even though I hadn’t listened to anything yet, I’m already thinking this guy knows his stuff. These things don’t get unnoticed, and I couldn’t be happier with the result.” Jacques felt right at home with the rest of the team working on Guardians. The passion for the Marvel universe from the creative team shines through the game, but it’s the careful attention to detail that die-hard Marvel fans will appreciate most. The game is littered with Easter eggs, from the Dazzler poster in Star-Lord’s bedroom to Lady Hellbender’s treasured Ghilaron skull and the various rarities in the Collector’s emporium (poor Throg!). Szcepkowski wanted to ensure this same level of care and attention to detail was reflected in the game’s music. He also wanted to break away from the conventions of the Marvel Cinematic Universe in which the Guardians films are set. In the films, Quill’s mom gives him the nickname Star-Lord in homage to his dad, a celestial—but what if Quill took his name from a fictitious metal band instead? And what if, instead of Star-Lord blasting out some of the biggest tunes from the ’70s on his treasured Sony Walkman, his epic mixtape was crammed full of ’80s bangers? “We all knew we wanted to carve our own identity, and it was one of the things that Marvel encouraged—[they] were always saying to us ‘We want you to make this your own,’” Szczepkowski tells WIRED. “That became very exciting, and it opened up a whole new sandbox that wasn’t in the movies, which was great.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg We see and hear this in the game’s opening moments, as the camera slowly zooms in on the Quill farmhouse with an idyllic sunset painting the field and farm machinery around it in shades of orange and gold. It’s a stark contrast to the scene that follows, as raucous metal music rains out of the chaotically messy bedroom of a young Peter Quill. With your head nodding along to the sound of harmonized guitar riffs and heavy drum beats, you’d be forgiven for thinking the music you’re listening to is one of the 31 licensed tracks that appear in the game. A lesser-known track from the KISS back catalog, perhaps? But no. What you’re hearing is “ Zero to Hero ” by Star-Lord (the band) performed and recorded by Szczepkowski and his long-time collaborator Yohann Boudreault. When Montreal’s senior creative director, Jean-François Dugas, pitched the idea of Quill adopting the Star-Lord name from his favorite band, Szczepkowski relished the opportunity to deliver the riffs and live out a childhood dream. “Having played in the clubs since I was 16, it’s nice to have that opportunity just kinda fall into my lap,” Szczepkowski tells us. He ended up writing an entire metal album with Boudreault, much to the delight of his boss. “[Dugas] is probably one of the biggest metalheads I know. There was no having to explain the credibility we were going for!” As if an entire album wasn’t enough, the team went so far as to create the artwork for the band’s CD inlay, which you read in the opening scene, as well as an interview with Rolling Stone. “I never set out thinking, ‘I’m gonna write a concept album for the game,’” Szczepkowski explains. “But when you listen to it and you know the game, it is a concept album. And if you don’t know the game, it still stands on its own. It’s one of those fluky things that just came out that way.” A lot of work went into licensing the game’s soundtrack, which spans an eclectic mix of ’80s music covering heavy hitters from KISS and Europe and floor-fillers from Rick Astley and Blondie. Negotiating the licenses for bands of this caliber is just as complicated as you might imagine, especially since the game was still under its codename at the time, but things go smoothly when you’ve got an industry veteran whose credits include Guitar Hero , Dance Dance Revolution, and Crazy Taxi handling negotiations. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “We had a pretty ambitious list of bands for the game, but I’d say we hit around 85 percent of that,” music consultant Randy Eckhardt tells WIRED, while explaining that a lot of the bands and artists featured in the game were also open to additional marketing opportunities. Astley Rickrolling Guardians of the Galaxy players might be the most ambitious Marvel crossover yet, and Mötley Crüe lent a track for a launch trailer. “The game took long enough to develop that we kept coming up with more ideas, and the labels could have charged us more but they never did—which was awesome,” Eckhardt continues. “This was a once-in-a-career opportunity to take music and gaming to the next level.” Where, when, and how these licensed tracks appear in the game is just as important as the final lineup of tracks. I won’t give anything away, but the placement of Europe’s “Final Countdown” during the game’s pivotal end-moments is one of the best uses of a licensed track I’ve ever experienced. Similarly, nothing beats cranking up the jukebox and exploring the Milano as the cast rips into each other and dishes banter with playful jibes, or pulling up to a new planet with “Hot Chocolate” playing in the background. Courtesy of Square Enix Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg An area where the music really comes into its own is during combat. The game’s Huddle feature is essentially a quick-time event ability you can activate to give all of the Guardians a damage boost. True to its name, this involves the gang huddling up as you raise your Walkman into the air and choose one of two motivational dialogue options in response to what the other Guardians are saying. Get it right and the volume cranks to 11 as you open up a can of intergalactic whup-ass to a track on your Walkman. Get it wrong and it flops. All of the licensed tracks in the game had to have two separate Star-Lord speeches written for them, a winning version and a losing one. The music in Guardians of the Galaxy is a story in three parts, and the experience wouldn’t be the same if not for the epic orchestral score Jacques composed. The score also marked a return to the prestigious Abbey Road Studios, 20 years after he entered its doors as the first video game composer to record a score there (for 2001’s Headhunter. ) The logistics of recording a full orchestra in the middle of a global pandemic haven’t been easy to navigate; smaller and more frequent recording sessions were needed to account for social distancing measures, but the result has been worth it. “Steve [Szczepkowski] and I had the same shared vision that we wanted an epic, intergalactic symphony, and that would be one of the big elements of music in the game,” Jacques tells WIRED. “We wanted it recorded live with some of the best musicians on the planet, many of which have performed in the MCU films, in one of the most famous studios in the world.” Like Szczepkowski, Jacques didn’t want to emulate anything from the movies and instead set out to create something different that would still sound familiar to Guardians fans. “From a musical point of view, I knew I wasn’t tied to anything specific,” he says, “but I wanted it to feel like Guardians, to have that sense of trepidation and adventure. This bunch of misfits is constantly bickering, and there’s a huge element of fun in it. I wanted to make sure all of these elements were reflected in the score.” Soundtracks Will Bedingfield curtains up Mat Ombler rock on Dia Lacina The result is over six hours of original music and a score that, when printed, is thicker than many books. Recording live with such a large orchestra of talented musicians made a massive difference to the way players hear that music within the game, Jacques says. “It lifts the gaming experience tenfold,” he explains. Working with a large orchestra, you get so much more dynamic range, and that vital human input on the delivery of every note. When we go to the studio and the players look at the music and ask how we want it [played], we can still fine-tune things and make decisions right on the floor on the day. When [the musicians] give feedback about the writing, that’s something I take very seriously because I look up to those players so much.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg As well as creating an original score for the game, Jacques had to navigate the complexities of fitting his work around the mountains of character dialogue in the game while ensuring his pieces didn’t sound out of place alongside any licensed music or Star-Lord tracks. And moving tracks around meant Jacques might have to completely rework whatever he was composing. “I can give you the perfect example of where that happened and when,” Szczepkowski laughs. One of the Star-Lord tracks, “Space Riders With No Name,” was initially the choice for the game’s opening scene. It’s in the key of E, but after Szczepkowski wrote the final song for the Star-Lord album, “Zero to Hero” took its place. “For whatever reason, [the song] got everybody’s ear and attention. The creative director was like, ‘I really want it to be ‘Zero to Hero’ that plays in the bedroom. I said, ‘Well, I'm pretty sure that's in drop D so that's not gonna work, but let me ask Rich [Jacques] nicely if he’ll change the key of the opening … ’” “That’s the fun of making games!” Szczepkowski continues. “As Rich said, and I can’t underline the importance of this enough: Flexibility is key.” “If I remember rightly, it was pretty late when that change came in too,” Jacques jumps in. “But these little things make such a difference in terms of the flow of the game. All of these little things that take time and effort make a big difference in the way the game is presented and therefore the experience for the player. It was challenging but a fun challenge to have!” And of course, as a devout Marvel fan, Jacques has made sure he’s incorporated some Marvel Easter eggs into his music for good measure. The choral sections you can hear in the game’s music (from the Pinewood Singers choir) won’t be recognizable by most players, as they’re sung in an alien language–Kree. “It’s quite a guttural language with lots of consonants, which is good for this kind of writing,” he explains. “Great lengths were taken to make it very Guardians , very Marvel—it’s not just arbitrary syllables that are sometimes used in this kind of music for choral effect. If fans listen closely, they’ll be able to hear the names of certain characters.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It’s rare that music becomes a major talking point following a game’s release. These types of conversations are usually reserved for the mammoth soundtracks and scores we see in games like Tony Hawk’s Pro Skater , Grand Theft Auto, and Final Fantasy. But the Guardians ’ 31 licensed tracks, six-hour orchestral score, and 10 original hard-rock tracks are a reminder that it’s been a long time since a game has delivered this level of music. And with Star-Lord’s music racking up over 1 million plays and 75,000 listeners on Spotify, we wouldn’t be surprised to see the band on a stage in real life at some point, backed by Jacques’ orchestral music. “Maybe we could do Star-Lord live with the full Metallica-style orchestration behind it,” Szczepkowski laughs. “We could literally do a Guardians music tour! Where you get one hour or so of just the score and then the band comes out and then it’s a combination band score.” 📩 The latest on tech, science, and more: Get our newsletters ! Yahya Abdul-Mateen II is ready to blow your mind A new twist in the McDonald’s ice cream machine hacking saga Wish List 2021 : Gifts for all the best people in your life The most efficient way to debug the simulation What is the metaverse, exactly ? 👁️ Explore AI like never before with our new database ✨ Optimize your home life with our Gear team’s best picks, from robot vacuums to affordable mattresses to smart speakers Contributor Topics video games gaming culture Music Marvel Gideon Lichfield Virginia Heffernan Kate Knibbs Vauhini Vara Lindsay Jones Kate Knibbs Jason Parham Jason Parham Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"With 'Ragnarök,' 'God of War' Keeps Growing Up | WIRED"

"https://www.wired.com/story/god-of-war-ragnarok-review-games-grow-up"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Reid McCarter Culture With Ragnarök , God of War Keeps Growing Up The latest in the God of War franchise reveals how much video gameshave grown, alongside the game's central characters. Image courtesy of Santa Monica Studio Save this story Save Save this story Save Before the long-running God of War series was reestablished with a 2018 entry that moved the story from a mythological ancient Greece to a mythological ancient Scandinavia, its protagonist, Kratos, was an unparalleled jerk. Mouth fixed in a permanent sneer, hell-bent on revenge against the pantheon of gods who tricked him into murdering his family, the earlier Kratos roared, growled, and ripped apart every deity in his way until he’d toppled an entire civilization’s metaphysical framework. With God of War ’s Norse reimagining, though, Kratos started to grow up. In Santa Monica Studio’s new vision, he was depicted as a sullen widower now left to forge a relationship with his son, Atreus, after heading north to escape his past. Its being an action game starring a living god means it isn’t long, of course, before that past catches up to him and he’s forced to reckon with his child, learning the family history and protecting him from the unwanted attention of the Norse gods. Over the course of the story—which tones down much of the previously over-the-top gore and does away with the goofy, rhythm game sex scenes of the Greek series—Kratos eventually learned how to talk to his son in more than monosyllables and grunts, becoming something like a functional parent over the course of their journey to scatter his late wife’s ashes. The recently released Ragnarök is a direct sequel to that game, picking up after its predecessor revealed that Kratos’ son, Atreus, is actually the Norse god Loki, and that the mythological end times— Ragnarök—are upon them. With Odin hunting for Atreus/Loki, and Kratos now desperate to find a way to keep his son safe while allowing him to embrace his divine identity without helping bring the world to an end (typical parent stuff, really), the stakes are much higher for the protagonist on both a personal and existential level. Naturally, then, Kratos’ role as a father and a character in general continues to change too. Though the 2018 God of War had established him as a kinder, gentler sort of bloodthirsty musclebound warrior—one capable of forming a proper relationship with his son—the sequel poses a follow-up question: How does Kratos behave once that relationship is put to the test by his child growing into an adult and being brought into confrontation with the Norse gods? Santa Monica Studio, Ragnarök ’s creators, knew that their latest game would continue to show Kratos move further away from his original character. In an email interview with WIRED, narrative director Matt Sophos writes that his team “definitely knew we wanted Kratos to continue to evolve” in both big and small ways. He cites a line from the end of the previous game in which Kratos tells Atreus that the pair “must be better” as something that the character truly meant—a central philosophy guiding his further development. Ragnarök tests this sentiment by intensifying the interference of Odin and the Norse gods in their lives, and also by showing the strains in the father-son relationship when the adolescent Atreus goes against his father’s will in pursuit of his own identity. Sunny Suljic, the 17-year-old voice and motion-capture actor who portrayed Atreus in both God of War (2018) and Ragnarök , explained over email that this aspect of the character was relatable for him, especially since he and Atreus are “about the same age.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “Because I grew up playing Atreus, it was a little bit easier to embody and feel the role,” he says. “I think I resonated most with his eager desire for a sense of self-dependency.” That exploration of self, in Ragnarök , sees Atreus grappling with his own need to understand his place among the Norse gods and Kratos’ equally strong wish to keep his son from becoming embroiled in the kind of divine machinations that saw him leave the Greek pantheon a bloody ruin in the original series. The conflict between these two deeply felt desires is at the heart of the story, even as the plot deals with the Norse gods’ intrigues and Atreus’ role alongside them in embracing or thwarting the seemingly inevitable arrival of Ragnarök. With the stakes so high, Sophos says that Ragnarök ’s story needed to focus on “questions of motivation” in its continued exploration of more intimate character dynamics. He explains that the Norse God of War games are concerned with “smaller and more personal” stories where Kratos, haunted by his past, “ really doesn’t want to be involved in the affairs of the gods.” Regardless of the plot’s structure, the game’s writers worked to keep the story’s primary concern—a relationship between father and son—in focus. “Everything else has to fall in line with that approach, keeping the heart of the story about Kratos and Atreus’ evolving relationship,” says Sophos. Part of this involves Kratos being less centered in the story, allowing the rest of the cast to influence the plot as much (and sometimes more) than he does. Sophos says that this decision “was a part of Kratos’ growth arc” that saw him stop being “closed off to everyone except his immediate family” and trust more in others, like the beheaded god Mimir and the dwarven Huldra siblings, Brok and Sindri, whom he first met in God of War 2018. “He’s now trying to be more open, having a true friend in Mimir and allowing the Huldra brothers into his family,” says Sophos, explaining that Kratos’ deepening understanding of these characters and his own son means he stops referring to them with dismissive nicknames: “Head” for Mimir, say, or “Boy” for Atreus. Suljic, as Atreus, consequently had a more demanding role as the new game’s plot concentrated on his character’s growing independence. “The sole focus is no longer about Kratos the god,” Suljic says. “It’s about Kratos as a father and how he handles watching his son become a man.” Suljic continues, explaining that he “wanted to set the bar even higher for my performance this time around” and work “to understand Atreus on a deeper level than I had when shooting the last game.” He sees the last game’s Atreus as “more naive and dependent on Kratos” and the sequel’s maturing character as driven by a desire to “understand what and who he is becoming.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Both of the Norse God of War games function as a kind of belated coming-of-age story about a man whose past as an unthinking, rage-driven agent of violent death is put into a plot where he’s finally asked to think about people (and gods) other than himself. The distance between the original Kratos and the Norse Kratos is vast, and the games they appeared in are similarly disparate in tone. In earlier entries, players weren’t encouraged to view the protagonist as more than a vessel through which to pummel and slice apart mythological figures. Now, the audience is asked to accept that this same man is capable of regretting his selfishly motivated violence and thinking deeply about how his propensity for mindless rage affects those close to him. Sophos said that Kratos’ history as the Greek god of war and destroyer of its pantheon wasn’t something to be discarded or downplayed in writing the character’s evolution, but a built-in opportunity to demonstrate how much he’s changed over the series. “Without the original depiction of Kratos, we don’t get to this point,” Sophos says. “He certainly feels like a different person, but that’s largely because he is. ” The older games and the original Kratos were something to build from rather than dismiss as artifacts from a previous era. “I feel like it was a gift to be given a character with such a rich history to build off of, allowing us the opportunity to reflect on all the things Kratos regrets and can try to do better,” Sophos continued. That past also serves as a constant reminder, to both character and audience, that, as Sophos puts it, Kratos “knows the path that unbridled rage leads to,” and it provides context to his desire not to give into it again. Suljic sees the same qualities reflected in Atreus, too, calling him a character who “never lets failure or a mistake deter him from reaching his goals.” He writes, “It made me realize that our mistakes and problems will always play a part in our lives, but it’s up to us to learn and grow from them.” Neither God of War (2018) nor Ragnarök are the most emotionally complex games—both depict the challenges of repairing strained familial bonds a bit too neatly. But their writing shows a clear interest in the characters’ interiority, which makes them more engaging than the pulpy tales of the original series. That a mainstream game can transition from an adolescent fantasy about a god-killing lone wolf into one about how that same warrior struggles against the odds (and gods) to raise a son who’s better than him is a testament to developers’ interest in richer narratives. This approach has yielded—and will continue to provide—blockbuster games whose appeal doesn’t rely entirely on the quality of their action and audiovisual prowess alone. While there will always be a place for the straightforward pleasures of those games, the fact that a series once tied so strongly to its protagonist’s one-note anger can grow into one that looks deeper into his psychology is a telling sign of how the medium’s mainstream continues to grow and expand. You Might Also Like … 📨 Make the most of chatbots with our AI Unlocked newsletter Taylor Swift, Star Wars, Stranger Things , and Deadpool have one man in common Generative AI is playing a surprising role in Israel-Hamas disinformation The new era of social media looks as bad for privacy as the last one Johnny Cash’s Taylor Swift cover predicts the boring future of AI music Your internet browser does not belong to you 🔌 Charge right into summer with the best travel adapters , power banks , and USB hubs Reid McCarter X Topics video games game reviews Console Games PC Games Eric Ravenscraft Matt Kamen Elana Levin Matt Kamen Boone Ashworth Megan Farokhmanesh Saniya Ahmed Jennifer M. Wood Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"It Shouldn’t Be This Hard to Get a PlayStation 5 | WIRED"

"https://www.wired.com/story/gadget-lab-podcast-492"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter WIRED Staff Gear It Shouldn’t Be This Hard to Get a PlayStation 5 Photograph: Girts Ragelis/Getty Images Save this story Save Save this story Save Were you able to buy a PlayStation 5? If so, good for you. If not, well, join the club. Sony’s newest game console has been very difficult to purchase since it was released in November—so much so that folks have resorted to using sniper bots, inside sources, and other shady practices to sidestep the scrum and snag that PS5. This week, we’re joined by Alan Henry and Saira Mueller from the WIRED video games team and Jeffrey Van Camp from WIRED’s reviews team to talk about the issues keeping PS5 supplies low. They’ll also tell us about their own experiences trying to buy a console. At the end of the show, we share some shopping tips you can use on your own quest to get this year’s most scarce gaming gadget. Read some advice about how to (maybe) buy a PS5 here. Read more about the scalper bots buying up all the PS5s here. Saira’s recommendation is to try cryotherapy. Brrr! Alan recommends Discord, which is great for gaming parties. Jeff recommends that you get a snow shovel, because you never know when you might need it. Lauren recommends this CBS guide to how you can help people in Texas during this deadly cold weather. Mike recommends the Vice show Hamilton’s Pharmacopeia , now in its third season. Saira Mueller can be found on Twitter @ SairaMueller. Alan Henry is @ halophoenix. Jeff Van Camp is @ JeffreyVC. Lauren Goode is @ LaurenGoode. Michael Calore is @ snackfight. Bling the main hotline at @ GadgetLab. The show is produced by Boone Ashworth (@ booneashworth ). Our theme music is by Solar Keys. If you have feedback about the show, or just want to enter to win a $50 gift card, take our brief listener survey here. Advertising note: WIRED Brand Lab is a creative studio from the publisher of WIRED. The WIRED newsroom is not involved in the creation of Brand Lab content. You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link. You can also download an app like Overcast or Pocket Casts, and search for Gadget Lab. If you use Android, you can find us in the Google Podcasts app just by tapping here. We’re on Spotify too. And in case you really need it, here's the RSS feed. Michael Calore : Lauren. Lauren Goode : Mike. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So MC : Lauren, have you tried to get, well, have you tried to get one of those ? LG : Oh, one of those? Well, I would accept that I'm hearing it's limited to certain groups right now, and it's just really hard to go online and figure out how to get one. MC : Yeah, I know. I can't believe we waited this long and now there are supply and demand issues. LG : I know. MC : All right, well, let's get into this week's show, where we're going to talk about the PlayStation 5. [ Gadget Lab intro theme music ] MC : Hi, everyone. Welcome to Gadget Lab. I am Michael Calore, a senior editor at WIRED. LG : And I'm Lauren Goode, a senior writer at WIRED. MC : We have a full house here today. First, let's welcome WIRED's service editor, Alan Henry. Hello Alan. Alan Henry : Hi. Hello. MC : Welcome back to the show. We have you on because Sony's new game console is a big deal, and you know a lot about it. Even though it's only been out for a few months, it's still nearly impossible to get a PS5, and in a moment, we're going to bring in some of our own colleagues who have been trying to get their hands on one with mixed results. But first, Alan, if you would, please tell us what is new about this console and what makes it such a hot commodity? AH : Well, it's a really great new console in the first PlayStation for like, what? Seven years? I mean, 4K gaming is a thing. The controller is awesome. It has plenty of new titles—not as many as arguably it should have launched with, but there are some great new games for it—and in general, people just wanted a new PlayStation. There was a lot of hype and buildup prior to its launch that made people really, really line up and be like, "Oh, I got to preorder that thing." But as far as why it's such a hot commodity, it's kind of counterintuitive, right? The real reason it's a hot commodity is because it's so difficult to get, and the people who do seem to have them are scalpers who are selling them for above retail price. So there are all these convoluted systems and tools and things you can do to try and score one, or you can head over to Craigslist and spend a whole bunch of money to a shady guy who has like 20 in the back of a van. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So LG : So, the scarcity is real, but it's also the scarcity that's pushing demand. AH : Exactly. LG : Hmm. Interesting. MC : So, Alan, do you know anyone who's been able to get a PS5? AH : Yes. I do know a few people who have been able to get a PS5, and emphasis on the few. That is also not including me, but I haven't really been trying. I said to myself, “I'm not a jump-on-a-console-at-launch kind of person. I'm more like, “Hey, the PS5 is about to come out. Now's a good time for me to buy a PS4.” That's how I shop. So I haven't been part of the rat race, but I have been watching it from afar. MC : Speaking of the rat race, our very own Jeffrey Van Camp, who edits the WIRED reviews section, is one of those people who's been trying to get a PS5. Jeff, are you there? Jeffrey Van Camp : Yeah. Hello. Good to be here. MC : Jeff, please tell us, when did you first start trying to buy one of these things, and how did it go? JVC : I don't know. There's a good time to really start trying to buy one of these. At first I didn't want one. This kind of goes back to what Alan was saying. I have a 4K TV, but I can do almost everything on it that I can on my PS4. But some friends and family slowly started getting them, the preorders seem to sell out really quick, and I kind of began to get the FOMO. LG : And when was this Jeff? JVC : Somewhere around Black Friday, I think I started, which is probably the worst time to start trying to get a PlayStation or really anything. So yeah, I tried. The first place I tried was Best Buy, and of course, being in the pandemic, normally you might think about going to a store, but everything is online this year. So yeah, I tried that, and it was one of the worst buying experiences I've ever had. MC : How is that? JVC : The site completely froze. They make you wait, you don't know if you should be refreshing your browser or just waiting for it to pop up. They're like, “PlayStations will drop in a minute here.” There's some dots near where the Add to Cart button is, and then it just kind of stays gray, and you're waiting for it to turn yellow. And then eventually it does, and it says, “Oh, sorry, it's already sold out.” Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So MC : Did you try any other stores? JVC : Yeah. So I tried that. I got the app, did a few more drops. Then I began learning more, started going to GameStop, Walmart. Sony does these online queues, so I tried there. The more I tried, the more I failed quicker it seemed, and it just kind of made me want it more. So I don't know if this is planned. I kind of figured it was all due to Christmas, but January has rolled around and it's still insanely difficult to get. Even after the holiday buzz wore off, by the middle of January, I have multiple Twitter alerts going, I've got Chrome extensions dinging, like during meetings, we could be filming this, and it might go off saying there's a drop coming in 10 minutes. Yeah. It's like failing to get a PlayStation 5 is a regular part of my workweek now. LG : So, what you're saying is that you started getting dings and alerts on your phone, and you look at it really excited and then say, oh, it's just a vaccine appointment. It's not the PS5. JVC : Yeah. LG : Right, right. JVC : It's not what I want. MC : All right. Well that all sounds like a nightmare for you, Jeff, and as we know, you're not alone. You're not even alone on our staff, because WIRED's own games editor, Saira Mueller, has also been trying to procure a PS5. Welcome to the show Saira. Saira Mueller : Hi, happy to be here. MC : Well, thank you for being on the show. Walk us through this. Why is it so hard to get a PS5 right now, and what has your experience been? SM : Yeah, it's really hard, I think, for a few reasons, and PlayStation hasn't really exactly said why. There are a lot of theories running rampant on the internet, as you can imagine, and as is kind of typical. A lot of people are saying that Sony is purposely doing this. They are selling every single PlayStation that goes out to market, and that's great for them. There's a lot of PR buzz about the PlayStation right now, which is also good for them. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So I think part of it could be pandemic related. There is very much a shortage on a lot of things to do with tech right now, if you think about graphics cards for PCs, so it could be related to that. It could be just a distribution issue. If some of these parts are getting made in parts of the world where factories have shut down right now, maybe they can't make as many as they would have otherwise. So there's not one good answer for that question, unfortunately, and Sony's not speaking to it—and probably smartly so on their part, because they're getting everything they want out of this, I would say. LG : So what has your personal experience been like in trying to get one of these? SM : So my personal experience actually started with JVC here. Seeing JVC struggle to get a PS5 was kind of what got me to start trying to get my own PS5. LG : And JVC, just to be clear for our listeners. That is Jeff Van Camp, who you heard from just a moment ago. OK, continue Saira. MC : Not the TV brand of yesteryear. SM : I think it was also a little bit of the social media hype. Around Christmas you would see all these people unboxing PlayStations, and they were just so excited, and it was like this huge thing. Similar to Alan, I wasn't planning on getting one straight away. I was thinking maybe towards the end of the year when Horizon Forbidden West comes out, maybe that's when I'll give it a go and I'll get one. But watching JVC struggle, I was like, you know what, I'm going to try and do this too. Maybe I can get him one, and then he doesn't have to keep trying anymore. So I didn't start early. I started, I think, around mid-January, and I believe it was because Jeff posted that there was a drop about to happen. So I was like, all right, let's go in this, let's do this, and I made it all the way to the cart. I had it in my cart. I was trying to pay, and it failed because it was like, oh, this one store no longer has any, try this other store. So I tried that store, and it was like, this store no longer has any, try this third store. By the time I tried the third store, it was sold out. So I almost, I was so very close. I almost got one that first try, but I just, just missed out. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So JVC : It will even say that there's stock in those stores, but you click and it's just a false alarm. Yeah, I like to complain. Apparently I had been complaining a little too loudly to everybody about my quest. SM : And it is a quest. It is very much a quest. LG : Is this the kind of thing where you have to wake up in the middle of the night and have your cursor poised and ready to go on the inventory, or there're back channels of tips about when the next drop is going to happen? How nutty is this getting? SM : I would say a lot of people did stay up overnight when it first dropped to get in line and to wait, but that's no longer really a thing. Most of the drops tend to happen in the middle of the day, but there are definitely some secret back channels and things, and we can get into that a little bit more later if you would like, but I do have some tips and insights into secret ways people are getting these PlayStations. One of the big problems I'll tease out now is that there are a lot of scalpers and bots, and they're just scooping them all up and then reselling them at much higher prices. LG : Now, Saira, did you consider temporarily going back to Australia so you could be ahead of the curve from a time zone perspective and getting one that way? SM : Yeah. I mean, with Covid unfortunately it is very hard to travel back to Australia right now. As many people probably know Australia and New Zealand did Covid very well, and I'm not even worried about my parents. No one wears masks, all restaurants and bars are open, because they're only letting in Australian citizens or permanent residents, and they're limiting the amount of people that can come in every week. I had actually looked at going back to Australia for the holidays, because it's summer over there, and in Seattle it's rainy and cold. It would have cost me $10,000 to go back. LG : Oh my goodness. That's an expensive PS5. SM : Exactly. So I don't know. I might as well just buy a bunch of scalped ones for that amount and then resell them at a higher price. So yeah. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So MC : All right. Well, let's take a quick break, and when we come back we're going to get to some of those tips that we've been talking about. [ Break ] MC : OK. So scoring a new console is incredibly difficult, but some people are actually getting them. Maybe they're just lucky. Maybe they know somebody, maybe they know something that we don't, but there have to be ways to tip the odds in one's favor. So, Alan, we'd like to go back to you first, please share with us all of your golden tips on how to score a PS5. AH : Well, considering I don't have one, my golden tips might be a little bronze, but I'll try anyway. I mean, honestly my best suggestion is to have an inside source. Not somebody inside, like at Sony, obviously, but like a friend who I don't know, works at Walmart or has a friend who works at GameStop or something like that. They will obviously be the first people to know when there's going to be a drop and exactly how many are going to be available at X store or Y location, and maybe if you're really lucky and have a little extra cash, you can convince them to put one aside for you or let you know when they're going to be available so you can actually go get one. Ideally make a network of friends who are all looking for PlayStation's, like Saira and Jeff here. I guarantee you that unbeknownst to the rest of us, they probably have some kind of suicide pact in which one of them will buy two PlayStation 5, and if the other one didn't get in on it, then they'll just sell the spare to their friend and try and find people that you can do that with. That's my best, best, best advice. Especially if these drops are happening at like 3:00 p.m. Eastern or 9:00 a.m. Eastern, and you have to work like a normal human, then they might have time to sit and refresh something while you don't. That's all I got though. Saira, I'm sure you have tips though. What are your tips? SM : Yeah, so this is actually quite funny because I remember there was another drop at the start of February and I tried really hard to get one. I think I made it all the way through to the cart again, but I didn't manage to snag one. So I tweeted out this meme about the Walmart site showing that a bunch of PlayStation's will become available at X time, and it's that meme of that guy staring at the computer screen, like avidly just waiting. One of my friends, one of my former coworkers, I'm not going to mention who, and you'll see why in a second but he slid into those DMs and he was like, brah, you should have told me you were looking for a PlayStation 5. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Then he sent me a screenshot of an order that he had, where there were like three PlayStation's that he'd grabbed, and I was like, "Oh my gosh, what is this? Also, did you not buy this for yourself and your friends?" He's like, "No, I've been purchasing like a bunch of them. I purchased like 20 in the past couple of months to flip. Don't hate me." I was just like, mind blown. I can't get one, JVC can't get one. Everyone's struggling. How have you managed to get 20 PlayStation's in the last few months? MC : Listener, we hate him. JVC : I am so upset right now. LG : Was he selling them at a mark-up? JVC : My face is all red. SM : He was selling them at a mark-up, yes. LG : What was the mark-up? SM : I didn't actually ask him. AH : Because you didn't want to know. LG : I was just going to say, either way. I'm seconding what Alan said. OK, please continue. SM : So he was like, "Well, let me tell you my secrets, little padawan." And I was like, "All right, hit me. I want to hear how you are doing this." He was like, "There are Discord servers, secret Discord servers of insiders who let you know when a drop is about to happen and sometimes they give you these secret links that will put the item directly into your cart. So you don't even have to sit in the line and then you can just check out immediately." So he then sent me these two links, one for the disk version one for the digital edition and was like, give this a go, there's going to be another drop in like five minutes. So I gave it a go, like you said, went straight into my cart. Unfortunately I was like a little bit late to it because I wasn't checking my messages because it was the middle of the workday so I was working, and by the time I went to do it, it was sold out. But I can confirm that it does work and as he said, he's had 20, so, secrets, secrets, secrets. Yeah. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So LG : Is the Discord actually you just tipping people off to the timing or is it sort of coded in such a way that it gives you the advantage because of you're skipping the step of putting it in your cart? SM : Yeah. So it's a link directly to whichever site it is, and it's just a way to completely skip and have it automatically in your cart. LG : Got it. OK. SM : Yeah. MC : Jeff, did you come across any tips that you felt were worthy enough to be able to pass on to our listeners? JVC : I didn't have one of those links, that would have been great tip, but I would say if you're going to try it the old fashioned way, the honest way, I guess my tips would be, and again, I've failed to get one for months. So these aren't really worth too much, but signing up for Chrome extension alerts. I got a thing called OctoShop, which let me get things from Best Buy or Walmart, GameStop, whenever they're about to drop some PlayStation's. Wario64, some different PS5 stock alerts on Twitter. You can set those to auto send you notifications. Usually these happen somewhere between Wednesday and Friday each week, middle of the day, 2:00, 3:00 p.m.. Not that I would know, I'm very busy working, but I would say the best tip I would have would be apparently to complain a lot or show your frustration to your friends because I just noticed the other day, my wife was even, I got a ding for a PS5 drop, and I heard a ding from across the room where my wife was working and she had felt so bad for me she was trying to get a PlayStation as well. Had some friends apparently trying as well. So just use your network, whatever network you happen to have. LG : That's a really heartwarming love story, Jeff. Love in the time of Corona. JVC : It was very, very sweet. I've I hate bothering, it's already interrupting maybe my day a little bit, opening a tab and clicking refresh a couple times at 2:00 p.m. or whenever it is, but it was very nice of her to do that. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So LG : Just to be clear, when we say we're using our networks, we as journalists are not using our networks within the tech industry to get these consoles. I think Jeff and Saira are both talking about their friends networks and people who are just generally hovering on the internet and hanging out on the internet and are able to set up alerts for buying things and that kind of thing. SM : Yeah, exactly. AH : So what you're saying is I should not DM the PR lead at Sony and ask him to send me a PlayStation 5? LG : That is correct. Although, I mean, we do sometimes take loaners, but then we return them in short order. MC : But at this point, Alan, I would say that probably the best thing to do is delete that DM that you sent a few weeks ago. AH : I'm going to go unsend that. MC : We should note that we have a story on WIRED that offers tips about how to snag a PlayStation 5. It's called how to snag a PlayStation 5, good luck, and you can read about it on WIRED and we'll put a link to that story in the show notes for this episode. LG : OK, so what was actually the result of all of your efforts? Did anyone here on the pod ended up with a PS5? AH : I'll start because I already alluded to the answer. I do not have a PlayStation 5. I haven't even really been trying because I feel like it's hopeless. Saira, what about you? Did you get one? SM : Yeah. So this same friend I was talking about actually got a disk edition, which is the edition that I want and it is arriving in a few weeks. So he is shipping it to me and selling it to me at cost. He is not upcharging me for it. So thank you to said friend who I will not name for very obvious reasons. AH : Very obvious reasons. MC : And what about you, Jeff? JVC : I'm actually happy to report a friend who I believe went through standard channels in another state, managed to get one just a couple days ago. At the same time I failed to get one. So I should be getting one this weekend, which is exciting. I don't know if I even want it anymore. It was more fun when I was searching. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So SM : I feel you actually, I feel like it was more fun to be part of the game. This became the IRL game of 2021. Now that I've got it locked in, I'm almost like a little bit, I don't know, disappointed. I don't know if that's the right word. MC : Is there strong replay value on this game? AH : Absolutely not. JVC : Yeah. I mean the good news is it should last for seven years. LG : Right, great. I feel like if you are one of those people who came to the system, and managed to get a PS5 or multiple PS5, as is the case with Saira's friend, that you should now be obligated to put the same effort into getting your elderly or vulnerable neighbor a vaccine shot. You just have to focus. You're like, OK, I have the 20 PS5's stacked up here that I'm selling at a markup. I need to now put some good into the world. AH : I honestly thought you were about to say, you should put that effort into getting your elderly neighbors a PS5. LG : I would say that the vaccine is slightly more important than the PS5. JVC : I would say your skills, the skills I've learned in trying to get a PS5 and it's mostly failing myself, but getting vaccine, at least here in Oklahoma, has been a remarkably similar process, at least in the early stages. Go to a site, wait for a drop, try and schedule an appointment. It's all the same these days. SM : But the question is, are their alerts that you can set up to be notified when a vaccine drop is about to happen. I feel like the answer to this is no. LG : And whose grandma has set up the bot? That's what I want to know. MC : Got to get in those vaccine discords. AH : Yes, absolutely. MC : All right. Well, thank you, all three of you for joining us this week. Let's take a quick break and when we come back, we'll do our recommendations. [Break] MC : All right. So now is the portion of the show where we each tell our listeners about a thing that we like, that we think that they would like too. Saira, let's start with you. What is your recommendation? Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So SM : OK. So my recommendation this week is a little bit off the wall. I tried something yesterday for the first time that I've never done before, and to say it was an experience is an understatement. Obviously given safety guidelines right now, that's most important, but I did cryotherapy yesterday, in which you stand in this, I don't know, box tube thing. This is one of the ones where your head is outside of said box tube thing, but it sprays you with hydrogen. I actually don't remember the specifics of how this works, but it basically cools down your body temperature, like ridiculously, like it can get down to minus 150 degrees, I believe, when I was reading the thing, but you're in there for three minutes and it's supposed to have all of these various health benefits, but even just as an experience, it was very interesting, and I would recommend it just purely for the experience. MC : How did it make you feel? Like physically. SM : Cold. Very, very cold, MC : But was it invigorating? SM : Yeah, so it was actually funny. So I get like restless leg syndrome sometimes, and I haven't had it for a really long time, but about half an hour after this, I was sitting on the couch watching the Great British Bake-Off actually, and my legs started to feel really like tingly. They were clearly getting worked up or like working through something and it was just interesting to see the effects that it kept having down the road, but coming straight out of it, you feel super tingly, a little bit numb. It's really weird putting on like your clothes because you can't feel anything basically. But yeah, I don't know what the long-term benefits are. I'm going to give it a go again, but it was definitely something. Yes cold, is the short answer to that question. MC : Nice. LG : I'm glad that you had a positive experience so far. I will say that one of my favorite Outside magazine profiles in recent years was a profile of Dave Asprey, the person who created Bulletproof Coffee and like the whole Bulletproof brand and the writer went to go visit Bulletproof labs, which is basically this whole bio hacking facility in Santa Monica. While the writer was there, there's a whole section of the labs that's like cryotherapy spa area, and so, they're walking around the labs and Asprey's talking about how great this is, and the writer is there when this 30 something year old guy emerges from the cryotherapy booth and just like boom passes out and face plants. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So They literally write, "I'm standing near Bulletproof's cryo chamber when a client, a man in his late thirties passes out during a session, he tumbles out of the booth, torso frosted, face ashen, eyes rolling up into his head." This is not funny. Ultimately the person was OK. From a writing perspective, it's like just imagine being that writer there at that moment when that happens. I'd like to imagine the public relations team behind the scenes just losing their minds, freaking out that this is happening. But yeah, it's totally interesting stuff. Once again, I'm going to come back to Saira, I'm glad that you were OK. You did not tumble out of the cryotherapy booth having passed out from the experience. SM : Thank you. Yes. No, thankfully that did not happen to me. I actually, I did it at the lowest setting to start off with, since it was my first time and not to brag or anything, but she said I did really well and that maybe I should go up another level next time. So maybe, fingers crossed it won't happen, but maybe that'll happen to me next time. LG : Let's hope not. SM : Let's hope not, yeah. MC : Level up the chill. Alan, what is your recommendation? AH : Well, I swear I didn't come up with this because we were talking about it, but my recommendation is Discord. I have actually been having way more fun in Discord, joining various Discords based on different interests recently than I could ever have hoped. I joined a Discord a long, long time ago because it was just a cute little way to keep track of friends and chat with them from time to time. For those people who aren't familiar with Discord, but are, for example, maybe familiar with Slack, it's Slack for gamers, but Discord also comes with a bunch of additional features that are focused, not on collaborating on work, but instead having fun together. So there are voice channels that you dip in and your mic is automatically on and you just chat with somebody. It's kind of like having an actual phone call without the anxiety. Then you can host watch parties, you can share your screen, you can stream whatever video game you're playing or whatever you're doing on your computer to other people who can then jump in and keep it and watch and hang out with you. I've seen people stream games. I've seen people stream art. I've seen people just stream like their writing process. It's a lot of fun and there are Discords for lots of different interests, entertainment properties, whatever you might be into. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So MC : Nice, and is there a client? AH : Oh yes. Yes. I mean, you can use it on the web for sure, but it is also available Mac, Windows, iOS, Android, free, free, super free. Although they will nag you to buy Nitro, which gives you some extra perks depending on the servers that you join. But give it a try first before you decide you want to spend $100 a year on the freemium stuff. MC : OK. All right. Well thank you. Jeff, what is your recommendation? JVC : Yeah, I thought I would have a, I was thinking of some fun tech I could do, but really the only thing I've wanted and desired this whole past week has been a snow shovel. So I've decided that no matter where you live, whether you're in California, the desert, Texas, anywhere, I'm in Oklahoma, you need a snow shovel. So we've gotten about close to a foot of snow in the last few days or last week or so, and all I've had is a rake. So I've literally had to rake parts of my front porch and a portion of my driveway, which is a particularly futile way to get rid of snow. So they're all sold out here during this snow storm, but with the climate the way it is going, I recommend everybody get whatever the first snow shovel you see is. Make sure it has a good lip at the top. SM : IS this going to be the new game of 2021, snow shovel buying? JVC : Getting a snow shovel. 2020 was great. Get the toilet paper, get the Clorox, everything. AH : The masks. JVC : Yeah. Get the masks. Now we're into snow shovels. LG : Yeah. We need the secret Discord links to snow shovels. JVC : That would be great. Do you have those, Saira? SM : I don't, unfortunately, maybe I need to do some searching on Discord and find those servers to join. I'll pass on the secret links to you JVC. MC : Lauren, what would you like to share with us? LG : Well, to Jeff's note, I know that we've had a lot of fun talking about getting expensive gadgets, like the PS5 during this show, but there is deadly frigid weather in the Southern half of the United States this week, and in particular, it's hitting Texas really hard. People are freezing and it has led to people dying. The electricity is out, it's incredibly challenging. So I am going to link to a list from CBS in the show notes of different ways that you can help Texas residents right now, whether that's donating to mutual aid funds or other national aid organizations, food banks, different disaster relief organizations, even helping animals in need, as well as journalists, go check out papers like the Texas Tribune, which is a nonprofit newspaper. Journalists are also working through really challenging conditions to tell some of the stories of what's going on right now. So we'll link to that in the show notes and that is my recommendation for this week. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So MC : Nice. LG : Mike, what's your recommendation this week? MC : I'm going to recommend a television show. It's a show that we have been enjoying over the last couple of weeks. It's called Hamilton's Pharmacopeia , it originally aired on Vice for the first two seasons. The third season is out now, just dropped earlier this year. So you can find the first two seasons on Hulu and the third season is available on Amazon Prime video. So it's a show about drugs. Basically the host Hamilton Morris is a chemist. He's a working chemist who has been obsessed with psychoactive substances his whole career. So he spends each episode diving into the history and the culture around a specific substance. He also tries to synthesize it. So he gets together with people who make things like DMT, LSD, PCP, ketamine, you name it, he's done a show on it. He gets together with somebody who makes it, usually these people are working outside of a law and they talk about how hard it is to synthesize it and they also talk about some of the effects. In some cases, he actually adjusts the drug on camera. It's a fun show. It's also a very serious show. It's also a very nerdy show. I was really surprised at how much you learn about organic chemistry watching this show, and also how much you learn about drug policy around the world, because he travels to different countries to talk about some of the substances. So I can highly recommend it. Highly recommend it. Hamilton's Pharmacopeia , streaming near you. LG : Excellent. MC : Yeah. All right. Well that was a fun show. Thank you to Saira, to Alan and to Jeff for joining us and talking about your PS5 experiences. JVC : Thanks for having me. AH : Thank you. SM : Thanks for having me. MC : Of course, and thank you all for listening. If you have feedback for us, you can find all of us on Twitter. Just check the show notes. This show is produced by Boone Ashworth, and we will be back next week. Goodbye. [Gadget Lab outro theme music] 📩 The latest on tech, science, and more: Get our newsletters ! 2034 , Part I: Peril in the South China Sea The digital divide is giving American churches hell The Sims made me realize I'm ready for more in life Here’s what learning to juggle does to your brain A case against the Peeping Tom theory of privacy 🎮 WIRED Games: Get the latest tips, reviews, and more 📱 Torn between the latest phones? 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"Hideo Kojima's 'Death Stranding' Is Beautiful, Smart—and Kinda Boring | WIRED"

"https://www.wired.com/story/death-stranding-observations"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Julie Muncy Culture Hideo Kojima's Death Stranding Is Beautiful, Smart—and Kinda Boring Courtesy of Playstation Save this story Save Save this story Save Death Stranding is the latest game by acclaimed videogame director Hideo Kojima and his studio, Kojima Productions. It's his first released work since his unceremonious departure from Konami and the Metal Gear Solid franchise. It's a big, bizarre, and difficult-to-explain exercise. So in lieu of a traditional game review, we put together some thoughts and pointers for you to take along as you begin the game—and to help you decide if you want to. Fog and moss stretch out before me in all directions. Rocks peek up out of the thin layer of green, peppered with impossible fungi and bits of trash. There's rain on the horizon. There's always rain on the horizon. The rain is a collapsing effect in action; it is part of a phenomenon, unique to the world of Death Stranding , called timefall. Timefall is rainfall by way of chronological acceleration. In other words, everything the water hits ages. The boxes on my back corrode and start to collapse. When a drop hits my skin, it weathers. In Death Stranding , everything is already dying or dead. The future, whether it's accelerated or not, always feels like a threat. Death Stranding , presently exclusive to the PlayStation 4 but coming to PC next summer, is as sprawling as the horizon that stretches before my player character, a man named Sam, played via motion capture by Norman Reedus ( The Walking Dead ). Sam's journey is mostly walking—he's a porter, a deliveryman who has to deliver his packages on foot. By hand. With timefall and worse horrors in the wilderness that used to be America, no other delivery service can function. Every package that needs to be moved between the disparate outposts civilization has left has to be delivered this way. Sam, and by extension the player, spends most of his time walking from place to place. And the journey is long. A dizzying array of mechanics accompany Sam's walking. He can grip the straps of his backpack for balance—one input for each side—and each bump, rock, or invisible hole in the path is a threat to that balance that needs to be vigilantly avoided or accounted for. Your cargo—as much as Sam can carry—can be rearranged freely on Sam's backpack and tied to straps on his shoulders and hips, the better to balance him this way or that. You can also switch cargo to his hands, holding down a button to grip it tight. One of the adjectives that comes to mind to best express the moment-to-moment play of Death Stranding is "fiddly." Getting through this journey takes time. I can't offer you a definitive take on its expanse. Consider these notes from the road. The apocalypse undergirding the world of Death Stranding is complicated. It's a game exceptionally concerned with connections—the writing is particularly unsubtle on this point. When the world ended, then, it ended via connection. Boundaries between death and life broke down, as did the border between past, present, and future. Some dead people come back to life, now, while others fade away and turn into wandering spirits that are toxic to the people they encounter, like magnets of opposite polarities that can only push each other away. Except, when these spirits, BTs, encounter people, the result is a good deal more violent. Explosive, even. Many people sense a mysterious connection to the afterlife, dramatized here in a striking image, as a beach full of fish washed up on an inky black shore. Which, of course, is another form of stranding. Everything is connected in the world of Death Stranding , except people. The horrors of this new, incomprehensible world have led most of civilization to collapse into itself, and isolated communities are all that's left. Sam is commissioned to take new technology to these isolated settlements in order to connect them to a new, futuristic type of internet, one with a mysterious technological connection to reality's broken-down cycle of mortality. Via connection—a "strand" of boundless data—Sam's America can be reconnected. Again, it's not subtle. Growing up, my family knew some long-haul truck drivers. It's brutal, dull work. You can't maintain a normal life schedule, or a normal suite of connections, if this is your full-time work. One friend of my parents' would spend several days at a time on the road, commuting across state lines with his cargo, before spending a few days at home. He kept strange hours, only coming home as a waypoint during the busiest times of the year. Sometimes, his schedule was so off that he would sleep somewhere else even when he was home, so as to not disturb his wife and kids in the middle of the night. Doing work like that requires a high tolerance for boredom. You have to be able to stay awake for hours upon hours of work that requires just enough attention to focus, but not enough to demand interest. Sam's work in Death Stranding is a lo-fi version of the same series of tasks. Go here, go there, don't fall asleep. Try not to fall off a cliff. Make sure to stop and rest now and then, or you'll regret it. Is boredom a productive emotion for art to produce? In my time with Death Stranding , it's one of the primary emotions I've felt. For lengthy, fascinating stretches, nothing will happen except one leg after another. It is at times excrutiatingly dull. Boredom is an unusual goal for a work of art to aim for. Boredom compels people to turn off the television, to walk out of the theater. To many perspectives, "It's boring!" is the most glaring sin a work can produce. Even among critics, we often talk about good art being art that engages us. It provokes us. It demands our attention. Death Stranding seems, so far, at least, largely uninterested in doing most of those things. There are periods of high activity, stretched across the pockets of civilization you find as you walk from coast to coast. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It's worth noting that, even among people who know truckers, they often have a (likely unfair) stereotype of being slightly unhinged. The assumption is understandable, even if it's uncharitable. To take on that level of tedium, that sort of boredom, willingly? Maybe something's wrong with you. Death Stranding didn't invent games about walking, of course. Indie titles like Proteus and Dear Esther are about walking as a means of exploring a beautiful environment, or as an interactive focal point to experience a narrative. But Death Stranding seems uniquely interested in the mechanical complexity of traversal across open spaces. Part of this is simply a difference in scale. Death Stranding has the budget and programming backend to code specific, odd moments that add layers of interaction to simple movement. Drinking water, eating food, stopping to use the restroom. These are all things you can do in Death Stranding , and to get the most out of the game you have to do them. It pulls you into the small, careful maintenances that are always a necessary part of travel. It's not surprising. Hideo Kojima, as a creator, has always been interested in bodies. In the Metal Gear games, people are regularly losing limbs, having their body parts replaced by machines or grafts. His heroes in Metal Gear are soldiers, their bodies themselves literal tools of war. In Death Stranding , Sam's body is an equivalent sort of tool. I spent a lot of time while playing Death Stranding imagining how much Sam's back must hurt. Have I mentioned the baby yet? There's a baby in Death Stranding , BB, a so-called "bridge baby." It's kept in artificial gestation and used as a crude means of further bridging the boundary between life and death, allowing people to perceive the usually invisible BTs and avoid them. Sam carries BB in a mechanical womb on his chest. It's another type of collapsing, of the cisgendered stereotypes that suggest that only women ever gestate children, and also between the boundaries of different stages of existence. There are, naturally, interactions baked into the game to visit with and soothe the baby. It's a lonely trip, but you aren't entirely alone. BB is always with you. Boredom isn't a wall. It's a window. Boredom is a way of paying attention. Boredom doesn't necessarily dull. Sometimes, it heightens. It's a restlessness in your arms. A tension in your fingers. A working, busy glance around the room looking for something to do. Sometimes, boredom can put us to sleep. But it also has a way of waking people up. Boredom primes you to notice. Death Stranding has a star-studded soundtrack. There is music here from bands like CHVRCHES and Low Roar, peppered throughout the game the way celebrities regularly make cameos as in-game characters. It feels, on one hand, like another entry in Hideo Kojima's ongoing middle-school crush on cinema. Films have recognizable faces and hot mixtapes of original tracks from big names. So, too, does Death Stranding. But also. Sometimes the songs will start up in the middle of a journey, a cry in the wilderness. These songs light up the open frontier. In these moments, the game feels like a masterful mood piece or some scenic music video. The spaces in Death Stranding are often, so far, functionally empty. Uneventful, save for occasional run-ins with BTs and ever-present minor obstacles to adjust for. But that makes them open canvases for this sort of experience. A great song can make a world of difference. If boredom is a window, here's what I see. The greenery is vivid against the gray of the sky. Sam wobbles slightly as he walks, and I have to carefully keep him from picking up too much momentum as he stumbles slightly over a small rock. He's bowled over a bit by the weight on his back, a little over a hundred kilograms. The rain passes fast. I stop, letting Sam catch his breath. I drink something, and grab the BB's artificial womb. I tap and shake it, soothing the child. He laughs and presses his face to the glass. I look forward to the horizon. It's beautiful, and still. I'm bored. I'm fascinated. I keep going. YouTubers must unionize, no matter what Google says Paid political ads are not the problem. Our perceptions are Could an astronaut lost in space use gravity to get around ? WIRED25: Stories of people who are racing to save us The plan to boost drone batteries with a teensy jet engine 👁 Prepare for the deepfake era of video ; plus, check out the latest news on AI 📱 Torn between the latest phones? Never fear—check out our iPhone buying guide and favorite Android phones Contributor X Topics video games Matt Kamen Boone Ashworth Reece Rogers Eric Ravenscraft Megan Farokhmanesh Reece Rogers Megan Farokhmanesh Saniya Ahmed Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. 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"Crispr Scandal: How Do You Publish a Scientific Villain's Data? | WIRED"

"https://www.wired.com/story/how-do-you-publish-the-work-of-a-scientific-villain"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Megan Molteni Science How Do You Publish the Work of a Scientific Villain? Hotlittlepotato Save this story Save Save this story Save How do you handle the data of a scientist who violates all the norms of his field? Who breaches the trust of a community that spans the entire globe ? Who shows a casual disregard for the fate of the whole human species? On the one hand, you might want to learn from such a person’s work; to have a full and open dissection of everything that went wrong. Because, spoiler, there was a lot that went wrong in the case in question. But rewarding such “abhorrent” behavior, as one scientist put it , with a publication—the currency of the scientific world—would send a message that ethical rules only exist to be broken. This is the precarious situation in which we find ourselves today, as scientists hash out the next chapter of the human gene-editing scandal that erupted two weeks ago, when the Chinese scientist He Jiankui revealed that for the last two years he has been working in secret to produce the world’s first Crispr-edited babies. Scientists denounced the work with near-unanimous condemnation, citing its technical failures as well as its deep breaches of ethical (and possibly legal) lines. What’s much less certain is what should happen to the work, now that it’s been done. Hours after He presented data on the twin girls at an international genome editing summit in Hong Kong, copies of his slides were already circulating in email inboxes and on Twitter. Scientists scrutinized the work, 280 characters at a time, and pointed out all the questions that remained unanswered. It was the kind of conversation that normally would take place under the auspices of a journal. But He, who made his announcement over YouTube, has so far produced no manuscript for public consumption. A paper describing this work is reportedly under peer review, and a second one about additional Crispr experiments in human embryos was rejected by an international journal over ethical and scientific concerns, STAT reported Monday morning. Scientists are beginning to grapple with the very real possibility that He’s work may never be awarded publication status, along with its attendant sheen of legitimacy. And that may be the academic justice he deserves. But it also highlights an intractable tension embedded in scientific publishing: policing bad actors comes at the cost of scientific censorship. “It’s a very dicey issue,” says Michael Eisen, a molecular biologist at University of California, Berkeley, and a staunch advocate of open-access publishing. “There need to be consequences for people who do things that are deemed to be unethical. You don’t want to have a system that gives people reasons to just randomly experiment on people.” The scientific publishing system, imperfect as it may be, has remained relevant in an era where anyone can buy a URL, self-publish a paper, and push it out to social media platforms reaching millions of people all in the span of an afternoon. The reason is that data wants to be seen in context, in conversation with other data. Through the connective tissue of citations, scientific journals establish a common set of vetted facts to debate, challenge, and be inspired by. They ensure some modicum of permanence to those facts; so that people today, tomorrow, and 100 years into the future can all point to the same digital object identifier assigned at publication and know that they’re all talking about the same thing. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg What then are the scientific costs to building a foundation for the field of human germline editing with one very consequential brick conspicuously missing? Disappearing the data down a memory hole presents logistical challenges as well as philosophical ones. Does the original sin of He Who Must Not Be Named preclude society from studying these twin babies as they grow up and maybe have children of their own? Addressing these questions will require decoupling the knowledge-building purpose of scientific publishing from the career-building one. Now, lest you think these are just #ivorytowerproblems, let’s be real for a second. There are going to be more Crispr babies. Maybe not next year or the year after that. But they’re coming, and not just in China. Last week, Harvard researchers announced that they plan to edit the DNA of human sperm to see if it’s possible to create IVF babies with lower risks of developing Alzheimer’s later in life. All around the world, researchers are doing studies in mice and monkeys, filing patents, and starting companies, all with an eye toward a future where germline editing becomes a legal, socially acceptable technology. How the scientific community responds in the present moment will have huge consequences for how, and how fast, that happens. “You would hate for some future experiment to fail or have some problem that could be avoided had people studied what happened here,” says Eisen. “In some sense there might even be an ethical duty for people to consider what was done.” Despite the uproar among scientists, they have not backed a moratorium, and embryo editing is ongoing. During the Hong Kong summit, an audience member asked He if he would be willing to post his work to a public forum, such as the biology preprint server bioRxiv, so the scientific community could have access to the data. He said that the journal considering his manuscript had advised against posting anything to bioRxiv until the paper had passed peer review. He did not specify which journal. Nor did He return WIRED’s requests for comment. But scientists who have seen the manuscript doubt it will pass peer review any time soon, if ever. “It was a very shoddy paper, very incomplete. What I saw wouldn’t pass any journal,” says Eric Topol, a cardiologist and director of the Scripps Research Translational Institute who reviewed He’s manuscript for the Associated Press. Other scientists have also denounced the experiment as a technical failure , based on the slides He presented in Hong Kong. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The edit He was trying to mimic was a 32-base pair deletion to the CCR5 gene that occurs naturally in some people with Northern European ancestry. Having two copies of that specific mutation leads to zero production of the CCR5 receptor, which HIV uses to access human immune cells. Instead, He introduced two new, unstudied mutations in one twin, Nana. In the other, Lulu, Crispr only managed to edit one copy of the CCR5 gene, again with a novel alteration. That means her healthy copy will still make CCR5 and she will likely still be susceptible to HIV. No one knows if the random mutations will provide a protective effect. They might even be harmful. Not only that, but early data suggests that both girls have a patchwork of edited and non-edited cells; a phenomenon known as mosaicism. The work’s moral failings are equally numerous. Besides choosing to cripple a normal gene to reduce the risk of a preventable, controllable disease neither child had, He personally took study participants through the informed consent process, in which he had no training, and during which he falsely described his work as an “AIDS-vaccine development project.” The consent documents made no mention of the risks involved in disabling the CCR5 gene—including the potential for increased susceptibility to other viruses like West Nile and influenza. And the hospital where He claimed to have ethical approval denied knowledge of any such project and said in a statement that the signatures on the approval form are suspected to be forgeries. The dilemma now, Topol says, is whether any publication or preprint server should be party to something so deeply sunk in a moral morass. “This hasn’t come up before because nothing has breached the ethics of human research like this,” says Topol. “ It’s highly problematic to publish it anywhere.” That includes bioRxiv, which was launched in 2013 by scientists at Cold Spring Harbor Laboratory to make scientific information available faster. Submissions to bioRxiv go through a quick (24-48 hour) screening process that filters out obviously non-scientific material, plagiarism, and any thinly veiled submissions by activists or AI. Scientists wanting to upload human studies have to list registered clinical trial IDs, meaning the studies have passed some form of ethical review. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg He’s Crispr baby work was technically listed with China’s clinical trial registry, but it does not appear he sought prior approval from federal regulators. According to the AP , the study was listed on November 8, 2018, long after it began. Richard Sever, a molecular biologist and bioRxiv co-founder declined to comment on He’s work specifically, but he did say that the preprint server would exercise its right to turn away any papers with known ethical or legal violations. “Our intention is not to provide a platform that seems to endorse or encourage unethical work,” says Sever. “That would be a very dangerous precedent for bioRxiv.” All this hand-wringing over the moral complicity of publishing platforms raises a tree-falling-in-the-forest line of existential questioning: If no one will publish what He did, does that mean it’s not science? Depends on what you mean by that. Science with a small “s” is a human enterprise as old as humanity itself. Nibbling on that tasty-looking mushroom and waiting a few hours to see if you get sick? That’s hypothesis testing. Try it a few more times with successively bigger bites, maybe add a bit of open-fire cooking; you’ve got a scientific method going. He’s human experiment is clearly science in this sense. Whether it will become Science with a big “S” remains to be seen. This more rigorous meaning of Science—which seeks to accrue knowledge by progressively, and systematically, reducing uncertainty—has only been around a few hundred years. Its arrival was marked by the development of the scientific paper, published in the pages of peer-reviewed journals. Before the 1600s, scientists communicated over private correspondence or in lectures. The scientific paper then became, and still is, the enabling unit of Science as a progressive, global enterprise. So what then, is to be done with the work of researchers like He, who step outside the bounds of acceptable Science? It’s a question that has mostly only come up in a backward-looking way, to studies that might have met the ethical standards of the day but have since been roundly denounced. The Tuskegee study—which denied African-American men syphilis treatment—comes to mind, as does Operation Sea-Spray, the US Navy’s fatal release of pathogenic bacteria over San Francisco. Then you have the case of Edward Jenner, who in the 1790s began experimenting on people with cowpox, injecting them with material taken from diseased dairy cows to see if it would protect them against smallpox. The Royal Society rejected his paper on the topic. Feeling it was an important public health contribution, Jenner published his case studies privately. The account led to the formation of mass vaccination campaigns and the eventual eradication of smallpox from the face of the Earth. He’s few public statements have hinted at his ambitions to be a modern-day Jenner, ambitions that may have blinded him to his transgressions. Now the scientific establishment will have to decide if it too will wear blinders. Never before has the academic publishing world had to contend in real time with research that nearly everyone agrees was profoundly wrong. And if anything, the last two weeks have made it all too clear just how unprepared anyone is to do that. What causes hangovers, and how can I avoid them ? A civilian's guide to Fortnite , just in time for season 7 The promise—and heartbreak— of cancer genomics Waymo's so-called robo-taxi launch reveals a brutal truth PHOTOS: Dress rehearsal for a mission to Mars 👀 Looking for the latest gadgets? Check out our picks , gift guides , and best deals all year round 📩 Want more? Sign up for our daily newsletter and never miss our latest and greatest stories X Topics crispr ethics scientific publishing Emily Mullin Emily Mullin Maryn McKenna Erica Kasper Lux Alptraum Max G. Levy Grace Browne Ben Brubaker Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Scientist Who Crispr’d Babies Bucked His Own Ethics Policy | WIRED"

"https://www.wired.com/story/he-jiankui-crispr-babies-bucked-own-ethics-policy"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Megan Molteni Science Scientist Who Crispr’d Babies Bucked His Own Ethics Policy Hotlittlepotato Save this story Save Save this story Save We said “ don’t freak out ,” when scientists first used Crispr to edit DNA in non-viable human embryos. When they tried it in embryos that could theoretically produce babies, we said “ don’t panic. ” Many years and years of boring bench science remain before anyone could even think about putting it near a woman’s uterus. Well, we might have been wrong. Permission to push the panic button granted. Late Sunday night, a Chinese researcher stunned the world by claiming to have created the first human babies, a set of twins, with Crispr-edited DNA. “Two beautiful little Chinese girls, Lulu and Nana, came crying into the world as healthy as any other babies a few weeks ago,” the scientist, He Jiankui, said in the first of five promotional videos posted to YouTube hours after MIT Technology Review broke the news. Lulu and Nana are reported to have a genetic mutation, courtesy of Crispr, that makes it harder for HIV to invade and infect their white blood cells. The claim, which has yet to be independently verified or backed up by published data, has ignited furious criticism , international outrage, and multiple investigations. The scientific outcry has been so swift because He’s purported work, conducted in secret, bulldozes past existing ethical guidance on so-called “germline editing,” in which alterations to an embryo’s DNA will be passed down to subsequent generations. What’s perhaps most strange is not that He ignored global recommendations on conducting responsible Crispr research in humans. He also ignored his own advice to the world—guidelines that were published within hours of his transgression becoming public. On Monday, He and his colleagues at Southern University of Science and Technology, in Shenzhen, published a set of draft ethical principles “to frame, guide, and restrict clinical applications that communities around the world can share and localize based on religious beliefs, culture, and public-health challenges.” Those principles included transparency and only performing the procedure when the risks are outweighed by serious medical need. The piece appeared in the The Crispr Journal , a young publication dedicated to Crispr research, commentary, and debate. Rodolphe Barrangou, the journal’s editor in chief, where the peer-reviewed perspective appeared, says that the article was one of two that it had published recently addressing the ethical concerns of human germline editing, the other by a bioethicist at the University of North Carolina. Both papers’ authors had requested that their writing come out ahead of a major gene editing summit taking place this week in Hong Kong. When half-rumors of He’s covert work reached Barrangou over the weekend, his team discussed pulling the paper, but ultimately decided that there was nothing too solid to discredit it, based on the information available at the time. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Now Barrangou and his team are rethinking that decision. For one thing, He did not disclose any conflicts of interest, which is standard practice among respectable journals. It’s since become clear that not only is He at the helm of several genetics companies in China, He was actively pursuing controversial human research long before writing up a scientific and moral code to guide it.“We’re currently assessing whether the omission was a matter of ill-management or ill-intent,” says Barrangou, who added that the journal is now conducting an audit to see if a retraction might be warranted. “It’s perplexing to see authors submit an ethical framework under which work should be done on the one hand, and then concurrently do something that directly contravenes at least two of five of their stated principles.” One is transparency. Reporting by Tech Review and The Associated Press has raised questions about whether He misled trial participants and Chinese regulators in his ambitions to make the first Crispr’d baby. Two is medical necessity. Take the gene He’s group chose to edit: CCR5. It codes for a receptor that HIV uses to infiltrate white blood cells, like a key to a locked door. No key, no access. Other controversial Crispr firsts have attempted to correct faulty versions of genes responsible for inherited, often incurable disorders, reverting them back to the healthy version. In contrast, He’s group crippled normal copies of CCR5 to lower the risk of future possible infection with HIV—a disease that is easily prevented, treated, and controlled by means that don’t involve forever changing someone’s DNA. Drugs, condoms, needle-exchange programs are all reasonable alternatives. “There are all sorts of questions these issues raise, but the most fundamental is the risk-benefit ratio for the babies who are going to be born,” says Hank Greely, an ethicist at Stanford University. “And the risk-benefit ratio on this stinks. Any institutional review board that approved it should be disbanded if not jailed.” Reporting by Stat indicates that He may have just gotten in over his head and tried to cram a self-guided ethics education into a few short months. The young scientist—records indicate He is just 34—has a background in biophysics, with stints studying in the US at Rice University and in bioengineer Stephen Quake’s lab at Stanford. His resume doesn’t read like someone steeped deeply in the nuances and ethics of human research. Barrangou says that came across in the many rounds of edits He’s framework went through. “The editorial team did spend a significant amount of time improving both the language and the content,” he says. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It’s too soon to say whether He’s stunt will bring him fame or just infamy. He’s still scheduled to speak at the human genome editing summit on Wednesday and Thursday. And China’s central government in Beijing has yet to come down one way or another. Condemnation would make He a rogue and a scientific outcast. Anything else opens the door for a Crispr IVF cottage industry to emerge in China and potentially elsewhere. “It’s hard to imagine this was the only group in the world doing this,” says Paul Knoepfler, a stem cell researcher at UC Davis who wrote a book on the future of designer babies called GMO Sapiens. “Some might say this broke the ice. Will others forge ahead and go public with their results or stop what they’re doing and see how this plays out?” What happens next makes all the difference. The fact that two babies now exist with one gene changed by Crispr to a less common form doesn’t change the world overnight. What changes the world is how society reacts, and whether it decides to let such DNA-altering procedures become common. A government climate study contradicts the president How much weed should you try your first time ? You can pry my air fryer out of my cold, greasy hands Inside the pricey war to influence your Instagram feed Airports cracked Uber and Lyft— cities should take note Looking for more? Sign up for our daily newsletter and never miss our latest and greatest stories X Topics crispr gene editing medicine ethics Amit Katwala Matt Simon Ramin Skibba Grace Browne Matt Simon Ramin Skibba Jim Robbins Matt Simon Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Chinese Scientists Try to Cure One Man's HIV With Crispr | WIRED"

"https://www.wired.com/story/chinese-scientists-try-to-cure-one-mans-hiv-with-crispr"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Megan Molteni Science Chinese Scientists Try to Cure One Man's HIV With Crispr HIV invades human immune cells using a protein known as CCR5, which acts like a door to let the virus in. Without it, the virus can't spread and reproduce. Photo: NIBSC/Science Source Save this story Save Save this story Save Imagine you’re 27 years old and you start feeling ill. Ill enough that you go to the hospital, and after much poking and prodding and waiting for lab results you learn you’re HIV positive. Two weeks later you find out that’s not even the worst of it. You’ve got leukemia too. Under any circumstances it would be a lot to take in. Especially in China, where HIV/AIDS is highly stigmatized. But for one young man living there, who this happened to in the late spring of 2016, there was one small but significant silver lining to this double whammy of a diagnosis. He would be eligible to participate in the first-ever clinical trial to assess the safety of trying to cure both the cancer and the infection in a single procedure using the gene-editing tool called Crispr. In July of 2017, doctors in Beijing blasted the patient with chemicals and radiation to wipe out his bone marrow, making space for millions of stem cells they then pumped into his body through an IV. These new stem cells, donated by a healthy fellow countryman, would replace the patient’s unhealthy ones, hopefully resolving his cancer. But unlike any other routine bone marrow transplant, this time researchers edited those stem cells with Crispr to cripple a gene called CCR5 , without which HIV can’t infiltrate immune cells. Now, more than two years later, the patient is in good health, his cancer in full remission, as researchers report today in the New England Journal of Medicine. The edited stem cells survived and are still keeping his body supplied with all the necessary blood and immune cells, and a small percentage of them continue to carry the protective CCR5 mutation. Not enough to have cured him of HIV, though—he remains infected and on antiretroviral drugs to keep the virus in check. Still, experts say the new case study shows this use of Crispr appears to be safe in humans and moves the field one step closer toward creating drug-free HIV treatments. “The safety profile appears to be acceptable,” pioneering cancer researcher Carl June wrote in an accompanying editorial , noting that the editing appeared to be precise, and that the engineered stem cells didn’t provoke an immune response in the patient. June did offer a caveat that the study’s single patient offered only limited data to draw on. What he found more striking was how quickly the science has moved from the first reports of using Crispr to treat HIV infection in mice to trying it in humans: only two years. At the University of Pennsylvania, June has led work in a groundbreaking cancer treatment called CAR-T , which involves genetically reprogramming immune cells into a clone army of tumor-targeting assassins. But it took him five years to go from studies in animals to trials involving humans. In this case, China’s more permissive biomedical research regulations might have expedited the work, or it could be that genetic engineering is lending new momentum to the race for an HIV/AIDS cure, he wrote. “In any case, the genie is out of the bottle with genome editing.” This is the first time an HIV-positive patient has been treated with Crispr-edited cells. But scientists have been trying to find ways to genetically disable CCR5 for more than a decade now. It all started in 2007, when a German doctor took a 41-year-old man with HIV/AIDS and leukemia off of his antiretroviral drugs and hooked a thin tube up to a vein in his chest. Through it, the so-called Berlin Patient received blood cells from a bone marrow donor who had a naturally occurring mutation called CCR5 Δ32. He was missing a chunk of DNA that ultimately allows an HIV virus to enter immune cells. The patient survived his cancer and became the first (though no longer the only ) person considered to be fully cured of HIV/AIDS. Until that moment, scientists had only hoped to control the insidious disease, through drugs like PrEP that cut down on transmission or antiretroviral treatments that prop up patients’ immune systems. The Berlin Patient made them believe total virus annihilation was, in fact, possible. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg His story galvanized labs and companies across the world to do it using genetic engineering. In 2009, California-based Sangamo Therapeutics launched the first human trials of gene-editing to treat HIV, using an older technology called zinc-finger nucleases. Those trials, which edit a person’s T cells, have produced some limited successes. A better approach, many contend, is to instead edit the cells that make T cells (and all the other blood and immune cells) deep inside a person’s bones. Known as hematopoietic stem cells, they tend to be more resistant to editing, and require more risk and discomfort to deliver. But if you succeed, you can provide a patient with a lifetime supply of HIV-immune blood and immune cells. That’s what Crispr seems to offer. The Chinese research team that conducted the latest study had previously transplanted Crispr-edited CCR5 mutant human cells into mice, making them resistant to HIV infection. In the spring of 2017 they registered a small human trial , to be conducted at the 307 Hospital of the People’s Liberation Army in Beijing. So far, the researchers have only enrolled and treated the single patient, according to Hongkui Deng, director of Peking University’s Stem Cell Research Center and one of the study’s coauthors. But Deng expects the trial to expand once they improve the efficiency of their technique. To edit the donor stem cells, Deng’s team put them into a machine that applies a mild electrical shock. This allows the Crispr components—a DNA-chopping enzyme and GPS guides that tell it where to cut—to slip through the cell membrane and get to work. This approach minimizes potential mistakes, known as off-target effects, because Crispr is only in the cells for a short period of time, meaning they aren’t as likely to go rogue and break DNA they’re not supposed to. But it also means not all the cells get edited. In an ideal world, both copies of the CCR5 gene would get snipped in all of the 163 million or so stem cells they isolated from the donor’s bone marrow. That would replicate what the Berlin Patient received from his donor. What the researchers got instead was much lower. After transplantation, only between 5.2 and 8.3 percent of the patient’s bone marrow cells carried at least one copy of the CCR5 edit. (The study authors didn’t report how many cells had both copies versus one copy edited.) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg That number stayed more or less stable over the 19 months that researchers have so far tracked the patient. But the more telling question is whether T cells in the patient’s blood also retain the edit. In the specific kind of T cells that HIV uses to infiltrate the immune system, the broken version of CCR5 was present in only about 2 percent of them. “That leaves a lot of room for improvement,” says Paula Cannon, a molecular microbiologist who studies HIV and gene-editing at the University of Southern California’s Keck School of Medicine. “At those levels, the cells would not be expected to have much of an effect against the virus.” Another clinical trial , run by the City of Hope in Los Angeles, is investigating using zinc-finger nucleases to edit the hematopoietic stem cells of HIV-positive people, with a less aggressive bone-marrow-clearing-out step, what you might call “chemo-lite.” So far six patients have been treated, and again, after 500 days only about 2 to 4 percent of cells carried the mutation, according to data presented at an HIV/AIDS conference last month in Seattle. “Ultimately, it comes down to the editing efficiency. That’s the biggest challenge right now,” says Rowena Johnston, vice president and director of research for amfAR, the Foundation for AIDS Research. Since 2010, the organization has awarded nearly $65 million to researchers working on HIV/AIDS cure strategies, including gene editing. “Crispr is certainly looking like the future right now, so I’m very interested these researchers decided to go in this direction.” China has been pushing the boundaries of Crispr in humans since the tool arrived in bioengineers’ toolboxes. Last year, a scientist named Jiankui He scandalized the scientific world by using Crispr to edit CCR5 in human embryos, in an attempt to make children immune to HIV. The experiments crossed a plethora of ethical lines , in addition to not working that well. In response to the global outcry, China proposed new, stricter, regulations on gene-editing in humans. Deng wouldn’t say whether the incident has made his own work more difficult, only that he has to be extra careful in how he explains it to the public. “Specifically, that in our study, gene-editing was applied to adult cells,” he wrote. Importantly, that means the CCR5 gene will remain unaltered in non-blood cell tissues. Studies have found that people lacking a functional CCR5 gene in all their cells are more susceptible to influenza and West Nile virus, and might even experience shortened lifespans. The unbuilt streets of California's ghost metropolis Computer scientists really need to take ethics classes London is changing its skyscraper designs— to favor cyclists Jeffrey Epstein and the power of networks A history of plans to nuke hurricanes (and other stuff too) 👁 How do machines learn ? Plus, read the latest news on artificial intelligence ✨ Optimize your home life with our Gear team’s best picks, from robot vacuums to affordable mattresses to smart speakers. X Topics crispr CRISPR/Cas9 HIV AIDS medicine Emily Mullin Emily Mullin Emily Mullin Emily Mullin Erica Kasper Celia Ford Max G. Levy Maryn McKenna Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. 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"Russia Is Taking Over Ukraine’s Internet | WIRED"

"https://www.wired.com/story/ukraine-russia-internet-takeover"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Matt Burgess Security Russia Is Taking Over Ukraine’s Internet Photograph: Alexey Furman/Getty Images Save this story Save Save this story Save Web pages in the city of Kherson in south Ukraine stopped loading on people’s devices at 2:43 pm on May 30. For the next 59 minutes, anyone connecting to the internet with KhersonTelecom, known locally as SkyNet, couldn’t call loved ones, find out the latest news, or upload images to Instagram. They were stuck in a communications blackout. When web pages started stuttering back to life at 3:42 pm, everything appeared to be normal. But behind the scenes everything had changed: Now all internet traffic was passing through a Russian provider and Vladimir Putin’s powerful online censorship machine. Since the end of May, the 280,000 people living in the occupied port city and its surrounding areas have faced constant online disruptions as internet service providers are forced to reroute their connections through Russian infrastructure. Multiple Ukrainian ISPs are now forced to switch their services to Russian providers and expose their customers to the country’s vast surveillance and censorship network, according to senior Ukrainian officials and technical analysis viewed by WIRED. The internet companies have been told to reroute connections under the watchful eye of Russian occupying forces or shut down their connections entirely, officials say. In addition, new unbranded mobile phone SIM cards using Russian numbers are being circulated in the region, further pushing people towards Russian networks. Grabbing control of the servers, cables, and cell phone towers—all classed as critical infrastructure—which allow people to freely access the web is considered one of the first steps in the “Russification” of occupied areas. “We understand this is a gross violation of human rights,” Victor Zhora, the deputy head of Ukraine’s cybersecurity agency, known as the State Services for Special Communication and Information Protection (SSSCIP), tells WIRED. “Since all traffic will be controlled by Russian special services, it will be monitored, and Russian invaders will restrict the access to information resources that share true information.” KhersonTelecom first switched its internet traffic to a Russian network on April 30, before flipping back to Ukrainian connections for the majority of May. However, things appear to have shifted permanently since May 30. All of KhersonTelecom’s traffic is now being routed through Miranda Media, a Crimea-based company that’s itself connected to Russian national telecom provider Rostelecom. (Miranda Media was set up after Putin annexed Crimea in 2014 ). The day after KhersonTelecom made its latest switch, state-controlled Russian media outlet RIA Novosti claimed the Kherson and Zaporizhzhia areas were officially being moved to Russian internet connections—days earlier, the outlet said the regions were also going to start using the Russian telephone code +7. Zhora says that across occupied regions of Ukraine—including Kherson, Luhansk, Donetsk, and Zaporizhzhia—there is a patchwork of around 1,200 different ISPs. “We understand that most of them are forced to connect to Russian telecom infrastructure and reroute traffic,” Zhora tells WIRED. “Unfortunately, there are cases of massive routing of traffic of Ukrainian operators across Russian channels,” says Liliia Malon, the commissioner of Ukraine’s telecom regulator, the National Commission for the State Regulation of Electronic Communications. “Ukrainian networks are partially blocked or completely disconnected.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Technical analysis confirms that the connections are switching. Internet monitoring company Cloudflare has observed KhersonTelecom’s traffic passing through Miranda Media for more than two weeks in June. Doug Madory, director of internet analysis at monitoring firm Kentik, has observed around half a dozen networks in Kherson connecting to the provider. “It's not a one-time thing,” Madory says. “Every couple of days, there's another company getting switched over to Russian transit from Ukraine.” Since the start of Putin’s war in February, disrupting or disabling internet infrastructure has been a common tactic—controlling the flow of information is a powerful weapon. Russian missiles have destroyed TV towers , a cyberattack against a satellite system had knock-on impacts across Europe , and disinformation has tried to break Ukrainian spirits. Despite frequent internet blackouts, Ukraine’s rich ecosystem of internet companies has rallied to keep people online. While Ukrainian troops are successfully launching counterattacks against Russian occupation in the south of the country, Kherson remains controlled by invading forces. (In March, it became the first major city to fall into Russian hands, and its residents have lived under occupation for around 100 days, reporting numerous incidents of torture. ) “It's one thing to take over a city and to control the supply lines into the city, the flow of food or fuel,” says David Belson, head of data insight at Cloudflare, who has written about internet control in Kherson. But, he says, “controlling internet access and being able to manipulate the internet access into an occupied area” is a “new front” in the conflict. There are multiple ways Russian forces are taking over internet systems. First, there is physical access—troops are seizing equipment. Spokespeople for two of Ukraine’s biggest internet providers, Kyivstar and Lifecell, say their equipment in Kherson was switched off by Russian occupying forces, and they don’t have any access to restore or repair equipment. (Throughout the war, internet engineers have been working amid shelling and attacks to repair damaged equipment ). The SSSCIP says 20 percent of telecommunications infrastructure across the whole of Ukraine has been damaged or destroyed, and tens of thousands of kilometers of fiber networks are not functioning. Once Russian forces have control of the equipment, they tell Ukrainian staff to reconfigure the networks to Miranda Media, Zhora says. “In case the local employees of these ISPs are not willing to help them with the reconfiguration, they are able to do it by themselves,” Zhora says. The SSSCIP, he adds, has advised staff not to risk their own lives or the lives of their families. “We hope that we are able to liberate these lands soon and this temporary period of blackmailing of these operators will pass off,” Zhora says, adding it is unlikely that communications in the region can be restored before the areas are liberated. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg For the time being, at the very least, this means connections will be routed through Russia. When Gudz Dmitry Alexandrovich, the owner of KhersonTelecom, switched his connection to Miranda Media for the first time at the start of May, he claims some customers thanked him because he was getting people online, while others chastised him for connecting to the Russian service. “On May 30 again, like on April 30, everything absolutely everything fell and only Miranda's channels work,” Alexandrovich says in a translated online chat. In a long Facebook post published on the company’s page at the start of May, he claimed he wanted to help people and shared photos of crowds gathering outside KhersonTelecom’s office to connect to the Wi-Fi. Russia is also trying to control mobile connections. In recent weeks, a mysterious new mobile company has popped up in Kherson. Images show blank SIM cards—totally white with no branding —being sold. Little is known about the SIM cards; however, the mobile network appears to use the Russian +7 prefix at the start of a number. Videos reportedly show crowds of citizens gathering to collect the SIM cards. “The Russian forces realize they're at a disadvantage if they keep using Ukrainian mobile networks,” says Cathal Mc Daid, the chief technology officer at mobile security company Enea AdaptiveMobile Security. The company has seen two separatist mobile operators in Donetsk and Luhansk expanding the territory they are covering to newly occupied areas. Who controls the internet matters. While most countries place only limited restrictions on the websites people can view, a handful of authoritarian nations—including China , North Korea , and Russia, severely limit what people can access. Russia has a vast system of internet censorship and surveillance , which has been growing in recent years as the country tries to implement a sovereign internet project that cuts it off from the rest of the world. The country’s System for Operative Investigative Activities, or SORM , can be used to read people’s emails, intercept text messages, and surveil other communications. “Russian networks are fully controlled by the Russian authorities,” Malon, the Ukrainian telecom regulator, says. The rerouting of the internet in occupied Ukrainian areas, Malon says, has the goal of spreading “Kremlin propaganda” and making people believe Ukrainian forces have abandoned them. “They are afraid that the news about the progress of the Ukrainian army will encourage resistance in the Kherson region and facilitate real activities,” Zhora says. WIRED Q&A Geoffrey Cain War of Words Morgan Meaker Ideas Lukasz Olejnik At the heart of the rerouting is Miranda Media, the operator in Crimea that appeared following the region’s annexation in 2014. Among “partners” listed on its website are the Russian security service known as the FSB and the Russian Ministry of Defense. The company did not respond to a request for comment. In many ways, Crimea may act as an example of what happens next in newly occupied areas. “Only in 2017, Crimea was completely disconnected from Ukrainian traffic. And now, as far as I know, it's only Russian traffic there,” says Ksenia Ermoshina, an assistant research professor at the Center for Internet and Society and an affiliated researcher at the Citizen Lab. In January last year, Ermoshina and colleagues published research on how Russia has taken control of Crimea’s internet infrastructure. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg After it annexed Crimea in 2014, Russian authorities created two new internet cables running along the Kerch Strait, where they connect with Russia. This process took three years to complete—something Ermoshina calls a “soft substitution model,” with connections transferring slowly over time. Since then, Russia has developed more advanced internet control systems. “The power of the Russian censorship machine changed in between [2014 and 2022],” Ermoshina says. “What I'm afraid of is the strength of Russian propaganda.” It’s likely that rerouting the internet in Kherson and the surrounding areas is seen by Russian authorities as a key step in trying to legitimize the occupation, says Olena Lennon, a Ukrainian political science and national security adjunct professor at the University of New Haven. The moves could also be a blueprint for future conflicts. Alongside internet rerouting in Kherson and other regions, Russian officials have started handing out Russian passports. Officials claim a Russian bank will soon open in Kherson. And the region has been moved to Moscow’s time zone by occupying forces. Many of the steps echo what previously happened in Crimea, Donetsk, and Luhansk. “Russia is making it clear that they're there for a long haul,” Lennon says, and controlling the internet is core to that. “They're making plans for a long-term occupation.” You Might Also Like … 📨 Make the most of chatbots with our AI Unlocked newsletter Taylor Swift, Star Wars, Stranger Things , and Deadpool have one man in common Generative AI is playing a surprising role in Israel-Hamas disinformation The new era of social media looks as bad for privacy as the last one Johnny Cash’s Taylor Swift cover predicts the boring future of AI music Your internet browser does not belong to you 🔌 Charge right into summer with the best travel adapters , power banks , and USB hubs Senior writer X Topics Ukraine Russia Internet cybersecurity censorship Andrew Couts Lily Hay Newman David Gilbert Andy Greenberg David Gilbert Andy Greenberg Justin Ling David Gilbert Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Google I/O 2022 Hardware: Pixel Watch, Pixel 6A, Pixel Tablet, Pixel 7, and Pixel Buds Pro | WIRED"

"https://www.wired.com/story/google-io-2022-pixel-6a-pixel-watch-pixel-buds-pro-pixel-7-pixel-tablet"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Julian Chokkattu Gear All the Hardware Google Announced at I/O 2022 Photograph: Google Save this story Save Save this story Save Every spring, Google has shown off some hardware at its annual software event, Google I/O. A gift-wrapped box in a sea of virtual gift cards, if you will. But at this year's developer's conference, hardware is stealing the show thanks to a number of long-anticipated product launches, from the Pixel 6A and Pixel Buds Pro to the Pixel Watch, Pixel 7, and Pixel 7 Pro, and even a glimpse at a Pixel Tablet—there are a lot of goodies. None of these devices are launching immediately, but you won't have to wait long to get your hands on them. Here's everything you need to know. Courtesy of Google The Pixel Watch has been rumored since Google started making Pixel phones in 2016—likely even before that when Google initially launched its specialized operating system for smartwatches. Well, Google's wearable is finally arriving, though details are slim. Unlike the Apple Watch, it's round! There's a tactile crown, and it uses recycled stainless steel for the frame. It also features swappable bands, though these appear to be a proprietary strap system, much like Apple's smartwatch. Rick Osterloh, Google's hardware chief, says the Pixel Watch has fluid animations and an improved user interface that's “tappable, voice-enabled, and glanceable.” You'll see more Google first-party apps on the watch, including a Google Home app that'll let you control your smart home devices just by tapping the screen on your wrist. Now that Fitbit is a Google-owned company, there's deep integration and plenty of shared fitness-monitoring expertise, with continuous heart-rate tracking, sleep tracking, and the ability to record personal fitness goals. However, when Google acquired Fitbit, it agreed to keep users' Fitbit and Google data separate —that's the case here, and so the Fitbit body data collected by the Pixel Watch will be isolated from Google. There are two fitness platforms on the watch though: Google Fit and Fitbit. Osterloh says they'll work together but that Fitbit is “imbued throughout” the watch's experience. He didn't share more about the integration. Unfortunately, Google says the Pixel Watch will not work with iOS devices—just Android phones. Wear OS has long supported iPhones, but last year's Samsung Galaxy Watch4 was among the first to be Android-only. It's unclear whether this is a theme for the platform in general, or if Google and Samsung are outliers in the overall Wear OS market. We don't have any pricing details, but Google is touting the Pixel Watch as a premium smartwatch, so expect a price similar to the Apple Watch. It launches in the fall. Google Pixel 6a Photograph: Google Google's latest A-series phone—the budget alternative to its flagship Pixel —will be called the Pixel 6A and it will cost $449 when it goes on sale in July. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Unlike its predecessors , which use a midrange Qualcomm processor to hold down costs, the Pixel 6A is powered by Google's Tensor chip , the same processor inside the high-end Pixel 6 and Pixel 6 Pro. It's an Apple-like move, echoing how the $429 iPhone SE is powered by the same chip that's in the iPhone 13. It also makes the Pixel 6A one of the most powerful Android phones for the money. The use of the same chip means Google's bringing every software feature you'll find on its flagships down to this phone, including Night Sight for better low-light photography, Real Tone for improved skin tones in photos, and Assistant Voice Typing for faster and more natural dictation. There are even some new perks, like how you'll be able to change the color of distracting objects in your photos instead of simply erasing them via Magic Eraser. The Pixel 6A looks almost the same as its pricier Pixel 6 siblings, with a thick camera bumper spanning the back and a two-tone design on the recycled aluminum frame, but it has a smaller 6.1-inch 60-Hz OLED screen. That's one way for the company to keep its cost down. The other? Lesser camera sensors. You get a 12-megapixel main sensor and an ultrawide, but the sensors aren't the same as what you'll find on the Pixel 6 series, so don't expect the same fidelity. Still, the Pixel A-series remains unrivaled in its photography prowess compared to other midrange and budget phones , and that is likely to stay the same here. It has robust 5G connectivity options like most flagship Android phones ( sub-6 and millimeter wave ), 6 GB of RAM, 128 GB of storage, and IP67 water resistance. It will get three Android upgrades and five years of security updates. While there is an under-display fingerprint sensor, the headphone jack isn't making a comeback here. The 4,400-mAh battery is also smaller than the one in the Pixel 5A, which means the new phone likely won't last two days on a single charge anymore. The Pixel 6A will be available for preorder on July 21 in Sage, Chalk, and Charcoal colors, and it goes on sale on July 28. Osterloh says the company is still dealing with supply chain woes, but the Pixel 6A should be in a better place than its predecessor; the Pixel 5A was sold only at the Google Store in the US and Japan , but the Pixel 6A will be available at various retailers in 13 countries, including the US, UK, and Australia, as well as India later this year. (Google also says it will continue selling the Pixel 5A.) Photograph: Google Coming on the heels of last year's Pixel Buds A-Series are another pair of wireless earbuds : the Pixel Buds Pro. These $199 buds have the same design as the A-Series, but Google has added active noise cancellation, to tune out your surroundings, and a transparency mode to let ambient sounds in, both of which are powered by a new custom six-core audio chip tuned by the company's in-house audio engineers. (Google claims it's the best noise-cancellation performance in wireless earbuds. We'll see.) Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Google's algorithms can tune out wind, traffic, and other background noise so that you sound clear when you're speaking on audio and video calls. The earbuds will also support Multipoint Connectivity, a feature which enables them to seamlessly switch their connection from your laptop to your phone when a mobile call comes in, then back to your laptop when you hang up. You never need to tap on any Bluetooth settings; the switch happens automatically. The Pixel Buds Pro are equipped with touch controls, a case with wireless charging support, and an IPX4 rating for water and sweat resistance. Google says they'll last for 11 hours per charge, or seven hours with active noise canceling turned on. All of these features are bang on the money at this price. Spatial audio support is coming later this year. They go on preorder July 21 and hit store shelves July 28, and come in four colors: Charcoal, Fog, Coral, and Lemongrass. Photograph: Google Paired with the Pixel Watch launch this fall are the Pixel 7 and Pixel 7 Pro. This news was expected, since Google tends to launch its flagship mobile phones in October. But rather than let rumors and leaks steal the thunder ahead of the fall debut, Google chose to show off what these devices look like. The black camera bar now has a recycled aluminum finish. The only other detail we know about the Pixel 7 is that it'll be powered by the “next-gen Tensor” chip, which will add improvements to speech processing, photography, videography, and security. When these phones arrive, they will come with Android 13 pre-installed. Photograph: Google Finally, perhaps unexpectedly, Google is making a Pixel Tablet. It's not the first Android-powered Pixel tablet—that'd be 2015's poorly-received Pixel C —but it's the first one to arrive since Google started paying serious attention to the Android tablet experience. The company has been making strides in optimizing the operating system for larger screens in Android 11, 12L, and the upcoming Android 13. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft All we know so far is that it looks somewhat like a Nest Hub without the base, and it'll be powered by a Tensor chip. Osterloh says it's designed to be “a perfect companion to your Pixel phone” and it will work “seamlessly with all your Pixel devices." It's a premium, larger-style tablet, though Google didn't share any other specifics. Expect it to arrive in 2023. At the end of the presentation, Google showed off a prototype set of augmented reality glasses that offer real-time language translation of whatever the person standing across from you is saying. The glasses look completely normal, with slightly thicker arms, and in the video Google showed off, the wearer is able to see a live translation from a foreign language show up in the upper corner of their vision as the person across from them was speaking. It's unclear at what stage these AR glasses are at or whether they'll ever materialize into an actual product. (Also, this is not the first time Google has teased rosy visions of smart glasses' future.) Why tease the Pixel Tablet, Pixel 7 series, and Pixel Watch so early? Google hasn't been shy about showing off its hardware months before the actual release dates, but the Pixel Tablet sneak peek comes a full year before it arrives. “Users are thinking of an ecosystem and an [manufacturer] as someone that they want to invest in for the long term, and we wanted to show people where we’re headed,” Osterloh says. "They can make an informed decision about where we're going as an organization for the next couple of years." You Might Also Like … 📨 Make the most of chatbots with our AI Unlocked newsletter Taylor Swift, Star Wars, Stranger Things , and Deadpool have one man in common Generative AI is playing a surprising role in Israel-Hamas disinformation The new era of social media looks as bad for privacy as the last one Johnny Cash’s Taylor Swift cover predicts the boring future of AI music Your internet browser does not belong to you 🔌 Charge right into summer with the best travel adapters , power banks , and USB hubs Reviews Editor X Topics Google Pixel smartwatches phones tablets wireless earbuds io Wear OS Julian Chokkattu Louryn Strampe Nena Farrell Nena Farrell Matt Jancer Matt Jancer Julian Chokkattu Simon Hill WIRED COUPONS Dyson promo code Extra 20% off sitewide - Dyson promo code GoPro Promo Code GoPro Promo Code: save 15% on your next order Samsung Promo Code +30% Off with this Samsung promo code Dell Coupon Code American Express Dell Coupon Code: Score 10% off select purchases Best Buy Coupon Best Buy coupon: Score $300 off select laptops VistaPrint promo code 15% off VistaPrint promo code when you sign up for emails Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"What is Virtual Reality (VR)? The Complete WIRED Guide | WIRED"

"https://www.wired.com/story/wired-guide-to-virtual-reality"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Peter Rubin Jaina Grey Culture The WIRED Guide to Virtual Reality Play/Pause Button Pause Illustrations by Radio Save this story Save Save this story Save All hail the headset. Or, alternatively, all ignore the headset, because it’s gonna be a dismal failure anyway. That’s pretty much the conversation around virtual reality (VR), a technology by which computer-aided stimuli create the immersive illusion of being somewhere else—and a topic on which middle ground is about as scarce as affordable housing in Silicon Valley. VR is either going to upend our lives in a way nothing has since the smartphone, or it’s the technological equivalent of trying to make “fetch” happen. The poles of that debate were established in 2012, when VR first reemerged from obscurity at a videogame trade show; they’ve persisted through Facebook’s $3 billion acquisition of headset maker Oculus in 2014, through years of refinement and improvement, and well into the first and a half generation of consumer hardware. The truth is likely somewhere in between. But either way, virtual reality represents an extraordinary shift in the way humans experience the digital realm. Computing has always been a mediated experience: People pass information back and forth through screens and keyboards. VR promises to do away with that pesky middle layer altogether. As does VR's cousin augmented reality (AR), which is sometimes called mixed reality (MR)—not to mention that VR, AR, and MR can all be lumped into the umbrella term XR, for "extended reality." VR depends on headsets, while AR is (for now, at least) more commonly experienced through your phone. Got all that? Don't worry, we're generally just going to stick with VR for the purposes of this guide. By enveloping you in an artificial world, or bringing virtual objects into your real-world environment, "spatial computing" allows you to interact more intuitively with those objects and information. Now VR is finally beginning to come of age, having survived the troublesome stages of the famous "hype cycle"—the Peak of Inflated Expectation, even the so-called Trough of Disillusionment. But it's doing so at a time when people are warier about technology than they've ever been. Privacy breaches, internet addiction, toxic online behavior: These ills are all at the forefront of the cultural conversation, and they all have the potential to be amplified many times over by VR and AR. As with the technology itself, "potential" is only one road of many. But, since VR and AR are poised to make significant leaps in the next two years (for real this time!), there's no better time to engage with their promise and their pitfalls. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The current life cycle of virtual reality may have begun when the earliest prototypes of the Oculus Rift showed up at the E3 videogame trade show in 2012, but it’s been licking at the edges of our collective consciousness for more than a century. The idea of immersing ourselves in 3D environments dates all the way back to the stereoscopes that captivated people's imaginations in the 19th century. If you present an almost identical image to each eye, your brain will combine them and find depth in their discrepancies; it's the same mechanism View-Masters used to become a childhood staple. When actual VR took root in our minds as an all-encompassing simulacrum is a little fuzzier. As with most technological breakthroughs, the vision likely began with science fiction—specifically Stanley G. Weinbaum’s 1935 short story “ Pygmalion’s Spectacles ,” in which a scientist devises a pair of glasses that can "make it so that you are in the story, you speak to the shadows, and the shadows reply, and instead of being on a screen, the story is all about you, and you are in it." What does IMU mean? Inertial measurement unit, the accelerometer/gyroscope combo that allows a headset to track a user's head movements. What are degrees of freedom? Your power of in-VR movement. Mobile headsets like the Google Daydream View or Gear VR can only track your head along the three rotational axes. That lets you look freely around a space, but it doesn't let you move. For the full six degrees of freedom, or "6DOF," you need either external sensors that track your headset in space via infrared (as with the Oculus Rift and HTC Vive) or a headset with outward-facing visual sensors that allow it to extrapolate its own position. What's latency? The time it takes for your head movement to be reflected by the headset's display: If you turn your head quickly, how long does it take for your perspective to change in accordance? High latency (upwards of 20 milliseconds or so) is the foremost cause of simulator sickness in VR. Lower latency is what you want. What's VR presence? The phenomenon that occurs when VR is good enough to trick your senses into believing that you are really experiencing the thing you're virtually experiencing, and your body responds in kind. Have you ever stood on a ledge or a high building in VR and refused to step off, even though your rational brain knew you'd just find more carpet? That's because of presence. What is the screen door effect? No matter how good a display's resolution, having it 2 inches in front of your eyes means you're gonna see pixels—and what's even more distracting for some people is the dark space between pixels, which can give the effect of peering through a fine mesh. On newer headsets, it’s less pronounced than it used to be but it’s still an issue. What's simulator sickness? When what you're seeing doesn't match up with what your inner ears are feeling—often due to latency, or when rotation makes the virtual world appear to smear, judder, or blur—your brain assumes you've been poisoned, and reacts by making you feel queasy. Moving beyond stereoscopes and toward those magical glasses took a little more time, however. In the late 1960s, a University of Utah computer science professor named Ivan Sutherland—who had invented Sketchpad, the predecessor of the first graphic computer interface, as an MIT student—created a contraption called the Sword of Damocles. The name was fitting: The Sword of Damocles was so large it had to be suspended from the ceiling. Nonetheless, it was the first "head-mounted display"; users who had its twin screens attached to their head could look around the room and see a virtual 3D cube hovering in midair. (Because you could also see your real-world surroundings, this was more like AR than VR, but it remains the inspiration for both technologies.) Sutherland and his colleague David Evans eventually joined the private sector, adapting their work to flight simulator products. The Air Force and NASA were both actively researching head-mounted displays as well, leading to massive helmets that could envelop pilots and astronauts in the illusion of 360-degree space. Inside the helmets, pilots could see a digital simulation of the world outside their plane, with their instruments superimposed in 3D over the display; when they moved their heads the display would shift, reflecting whatever part of the world they were "looking" at. None of this technology had a true name, though—at least not until the 1980s, when a twenty-something college dropout named Jaron Lanier dubbed it "virtual reality." (The phrase was first used by French playwright Antonio Artaud in a 1933 essay.) The company Lanier cofounded, VPL Research, created the first official products that could deliver VR: the EyePhone (yup), the DataGlove, and the DataSuit. They delivered a compelling, if graphically primitive, experience, but they were slow, uncomfortable, and—at more than $350,000 for a full setup for two people, including the computer to run it all—prohibitively expensive. Yet, led by VPL’s promise and fueled by sci-fi writers, VR captured the popular imagination in the first half of the 1990s. If you didn't read Neal Stephenson's 1992 novel Snow Crash , you may have seen the movie Lawnmower Man that same year—a divine piece of schlock that featured VPL's gear (and was so far removed from the Stephen King short story it purported to adapt that King sued to have his name removed from the poster). It wasn't just colonizing genre movies or speculative fiction: VR figured prominently in syndicated live-action kiddie fare like VR Troopers , and even popped up in episodes of Murder She Wrote and Mad About You. In the real world, virtual reality was promised to gamers everywhere. In arcades and malls, Virtuality pods let people play short VR games (remember Dactyl Nightmare ?); in living rooms, Nintendo called its 3D videogame system "Virtual Boy," conveniently ignoring the fact that the headsets delivered headaches rather than actual VR. (The Virtual Boy was discontinued six months after release.) VR proved unable to deliver on its promise, and its cultural presence eventually dried up. Research continued in academia and private-sector labs, but VR simply ceased to exist as a viable consumer technology. Then the smartphone came along. Phones featured compact high-resolution displays; they contained tiny gyroscopes and accelerometers; they boasted mobile processors that could handle 3D graphics. And all of a sudden, the hardware limitations that stood in the way of VR weren't a problem anymore. In 2012, id Software cofounder and virtual-reality aficionado, John Carmack, came to the E3 videogame trade show with a special surprise: He had borrowed a prototype of a headset created by a 19-year-old VR enthusiast named Palmer Luckey and hacked it to run a VR version of the game Doom. Its face was covered with duct tape, and a strap ripped from a pair of Oakley ski goggles was all that held it to your head, but it worked. When people put on the headset, they found themselves surrounded by the 3D graphics they'd normally see on a TV or monitor. They weren't just playing Doom —they were inside it. Things happened fast after that. Luckey's company, Oculus, raised more than $2 million on Kickstarter to produce the headset, which he called the Oculus Rift. In 2014, Facebook purchased Oculus for nearly $3 billion. ("Oculus has the chance to create the most social platform ever, and change the way we work, play and communicate," Mark Zuckerberg said at the time.) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg In 2016, the first wave of dedicated consumer VR headsets arrived, though all three were effectively peripherals rather than full systems: The Oculus Rift and the HTC Vive each connected to high-powered PCs, and the PlayStation VR system ran off a PlayStation 4 game console. In 2018, the first "stand-alone" headsets hit the market. They don't connect to a computer or depend on your smartphone to supply the display and processing; they're self-contained, all-in-one devices that make VR truly easy to use for the first time ever. In 2020 the world of VR is going to be defined by these stand-alone headsets. The tethered-to-a-desktop headsets are still a high-end option for die-hards looking for the highest fidelity experiences possible, but an untethered stand-alone headset delivers on the promise of deeply immersive VR in the way previous tethered versions just haven’t—at least not without spending serious cash on hardware and accessories. The first next-gen stand-alone headsets are starting to hit store shelves already. Oculus released its version, the Oculus Quest , back in May 2019, and HTC is poised to release a modular competitor, the Vive Cosmos Play , later this year. What all this is for is a question that doesn't have a single answer. The easiest but least satisfying response is that it's for everything. Beyond games and other interactive entertainment, VR shows promising applications for pain relief and PTSD, for education and design, for both telecommuting and office work. Thanks to "embodied presence"—you occupy an avatar in virtual space—social VR is not just more immersive than any digitally mediated communication we've ever experienced, but more affecting as well. The experiences we have virtually, from our reactions to our surroundings to the quality of our interactions, are stored and retrieved in our brains like any other experiential memory. Yet, for all the billions of dollars poured into the field, nothing has yet emerged as the iPhone of VR: the product that combines compelling technology with an intuitive, desirable form. And while augmented and mixed reality are still a few years behind VR, it stands to reason that these related technologies won't remain distinct for long, instead merging into a single device that can deliver immersive, shut-out-the-world VR experiences—and then become transparent to let you interact with the world again. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg That may end up coming from Apple; the Cupertino company is reportedly at work on a headset that could launch as early as 2020. However, incredibly well-funded and even more incredibly secretive company Magic Leap has recently emerged from years of guarded development to launch the first developer-only version of its own AR headset; the company has said its device would be able to deliver traditional VR as well as hologram-driven mixed reality. But even with that sort of device, we're at the beginning of a long, uncertain road—not because of what the technology can do, but because of how people could misuse it. The internet is great; how people treat each other on the internet, not so much. Apply that logic to VR, where being embodied as an avatar means you have personal boundaries that can be violated, and where spatialized audio and haptic feedback lets you hear and feel what other people are saying and doing to you, and you're looking at a potential for harassment and toxic behavior that's exponentially more visceral and traumatizing than anything on conventional social media. And then there's the question of authentication. The internet has given us phishing and catfishing, deep fakes, and fake news. Transpose any one of those into an all-encompassing experiential medium, and it's not hard to imagine what a bad actor (or geopolitical entity) could accomplish. Those are the darkest timelines, for sure—and despite what the creators of Black Mirror seem to think, there's no guarantee things will swing that way. But if we've learned anything from how our lawmakers think about technology, it's that they don't think about it hard enough, and they don't think about it soon enough. So it's better to have these conversations now before we find ourselves trying to answer questions no one saw coming. Besides, the way things are going, there's going to be a lot of good coming at us in the next few years. Let's try to keep it that way. Updated March 2020: We've added some commentary about the state of VR in 2020 to reflect changes in the landscape. The Untold Story of Magic Leap, the World’s Most Secretive Startup When the first wave of high-end VR headsets landed in 2016, they realized a decades-long dream—but there was another technology already on the horizon. The Inside Story of Oculus Rift and How Virtual Reality Became Reality When the Oculus Rift first showed up at a videogame trade show in 2012, it was meant to be a Kickstarter project for a few VR die-hards. Turns out reality had other plans. Coming Attractions: The Rise of VR Porn Like many new technologies over the years, VR found an early foothold in the adult-film industry. But the results may upend everything you thought you knew about porn. The Display of the Future Might Be in Your Contact Lens AR is moving from our smartphones to eyeglasses and now contact lenses. This new company is at the frontier. What a Real Wedding in a Virtual Space Says About the Future They met in VR. They grew close in VR. They got married in VR, surrounded by their friends from around the world. As Social VR Grows, Users Are the Ones Building Its Worlds VR's growth hinges on the creativity of the people wearing the headset as much as it does on the technology powering it. Facebook's Bizarre VR App Is Exactly Why Zuck Bought Oculus When Facebook announced its social VR app, Spaces, it gave people their first look at why the company paid $3 billion to acquire the headset maker. Enjoyed this deep dive? Check out more WIRED Guides. Contributing Editor X Writer and Reviewer X Instagram Topics Wired Guide virtual reality augmented reality video games Jason Parham Virginia Heffernan Gideon Lichfield Vauhini Vara Kate Knibbs Kate Knibbs Lindsay Jones Jason Parham Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Apple's AR Glasses Are Hiding in Plain Sight | WIRED"

"https://www.wired.com/story/apple-ar-glasses"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Peter Rubin Gear Apple's AR Glasses Are Hiding in Plain Sight Photograph: Carsten Koall/Getty Images Save this story Save Save this story Save With all the phone and watch and TV and game and chip and other chip news coming out of Apple's big event last week, it was easy to forget the company's longest-running background process: an augmented-reality wearable. That's by design. Silicon Valley's advent calendar clearly marks September as the traditional time for Apple to talk finished hardware, not secretive projects. But those secretive projects have a weird habit of poking their heads into the light. A slew of features and language discovered recently inside iOS 13 and 13.1 seem to explicitly confirm the very thing Apple executives have steadfastly refused to acknowledge—an honest-to-Jobs AR headset. In fact, taken in conjunction with acquisitions and patent filings the company has made over the past several years, those hidden features have painted the clearest view yet of Apple's augmented dreams. First came StarBoard. At the very beginning of September, a leaked internal build of iOS 13 was found to contain a "readme" file referring to StarBoard, a system that allows developers to view stereo-enabled AR apps on an iPhone. The build also included an app called StarTester to accomplish exactly that. That marked the first explicit mention stereo apps—i.e., those that output to separate displays, like those found in AR/VR headsets—in Apple material. Not long after, on the day of the hardware event, Apple released Xcode 11, the newest version of the company's macOS development environment. Inside that set of tools lurked data files for what appeared to be two different headsets, codenamed Franc and Luck. The same day, iOS developer Steve Troughton-Smith found the StarBoard framework in the official "golden master" of iOS 13; he also pointed out references to "HME," which many speculated stood for "head-mounted experience." (HMD, or head-mounted display, is a common term for a VR/AR headset.) So far, so unprecedented. When Apple first released ARKit in 2017, it was the beginning of a long journey to familiarize developers with augmented reality and get them playing with the possibilities. Yet, the company has always been careful to situate AR as a mobile technology, people peeking through iPhones or iPads to shop or play with Legos, or even experience public art installations. Finding this kind of data, even hidden deep within OS developer files, marks an uncharacteristic transparency from Apple—as though the company is planning something sooner rather than later. What that thing might be depends who you ask. Reports from Bloomberg News and Taiwanese analyst Ming-Chi Kuo have long claimed that Apple would be beginning production on an AR headset this year for release in 2020—one that acts more like a peripheral than an all-in-one device, depending on the iPhone to handle the processing power. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Troughton-Smith came to a similar conclusion after poking through iOS 13. "The picture of Apple’s AR efforts from iOS 13 is very different to what one might expect," he tweeted. "It points to the headset being a much more passive display accessory for iPhone than a device with an OS of its own. The iPhone seems to do everything; ARKit is the compositor." That idea of a passive display accessory got fleshed out late last week, when another developer got StarTester up and running on a beta of iOS 13.1, which officially comes out today. X content This content can also be viewed on the site it originates from. That person also found specific numbers in the iOS framework referring to the fields of view for the two specific headset codenames: 58 and 61 degrees for Luck and Franc, respectively. (A third codename, Garta, seems to refer to a testing mode rather than a specific device.) All of which matches up with the thought that Apple is planning a small, lightweight product—one that lives up to the term "wearable" by being more like smart glasses instead of an unwieldy Microsoft HoloLens. "Fifty-eight degrees doesn't sound like much compared to an Oculus Rift, but compared to an nreal Light , which is 52 degrees, it's already pretty competitive," says J.C. Kuang, an analyst with AR/VR market intelligence firm Greenlight Insights. "That's the exact class of product we need to be looking at when we talk about what the architecture might look like." Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Mike Boland, chief analyst at ARtillery Intelligence, which tracks the augmented-reality mark, calls such a product a "notification layer," and posits it as an introductory device of sorts—one that acts as a bridge between the mobile AR of today and a more powerful headset that could ultimately replace the smartphone. "I've always been skeptical of 2020," he says. "If you look across the industry at the underlying tech, it's just not ready to build something sleek and light." However, an intermediary device like the one iOS 13 seems to point to could strike a balance, giving developers the chance to get used to building stereo experiences and develop best practices before needing to fully integrate with the " mirror world. " A recent patent seems to support the idea as well. "Display System Having Sensors," which Apple filed in March and was published in July, describes a companion system: a head-mounted device with inward- and outward-facing sensors feeds its inputs to a "controller," which then "render[s] frames for display by the HMD." A patent isn't the same as a plan, obviously, but it's a hell of a data point. How Apple gets from phone-tethered smart-glasses to something a fully realized spatial-computing platform—or how long it takes to do so—remains unclear, but elements of the road map are hidden in plain sight. "A lot of the tech they've already built and fully deployed is critical to their goal of building a discreet AR HMD platform," Kuang says. As an example, he points to last week's announcement that the iPhone 11 models could take photos of pets in Portrait Mode: "That's a good example of them working in little tweaks that don't appear to have relevance to AR, but are super-meaningful if you're a developer. The ability to recognize nonhuman faces significantly expands your ability to build tools and experiences." Two acquisitions Apple has made in recent years also suggest how the company might get there. Kuang traces the current StarBoard testing mode to the 2017 acquisition of a company called Vrvana. At the time, Vrvana's chief product was a mixed-reality headset—however, rather than rely on a transparent "waveguide" display like those in the HoloLens or Magic Leap One, it used front-facing cameras to deliver passthrough video to the user. (This is also how a company like Varjo delivers mixed reality using an VR headset.) "It ruffled some feathers because nobody was really down with a discreet headset using pass-through," Kuang adds of Vrvana. "But the StarBoard stuff presents exactly that: a Google Cardboard sort of functionality for iPhones. It's obviously for testing purposes, but it maybe gives us a little more insight into how Apple has been testing AR without having to resort to building a couple of hundred waveguide-enabled devices for testing purposes." Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Apple's other strategic move, buying Colorado company Akonia Holographics in 2018 , looks to have two possible reasons: not just for the waveguide displays that Akonia was working on, but for the "holographic storage" that was the company's original goal. The term, which refers to storing and accessing data in three dimensions rather than on the surface of a material (optical storage), has long eluded commercialization, but could prove pivotal to the long-term vision of AR. "The utopian vision of the end user device is super-lightweight and does functionally no computing compared to where we currently are," Kuang says. "Everything happens on the cloud. The kind of speed and transfer that comes with holographic storage could be a key part of that." Kuang points to another recent Apple patent, published just last week , proposing an AR display that delivers three-dimensional imagery through an Akonia-like waveguide system. In his view, it confirms the company's commitment to getting past the limitations of today's devices—particularly the eyestrain that results from trying to focus on virtual objects and real-world ones at the same time. "The fact that Apple is acknowledging it's a big problem and intends to fix it is huge," he says. "It's more than Microsoft can be said to be doing." It also suggests that while the iOS discoveries speak to an interim device, they're also likely only just the beginning. Much has been made of Apple's push into services to offset declining iPhone revenue; subscriptions like Arcade and TV+ are steps toward the company's stated goal of making more than $50 billion from such services annually. But that doesn't solve the question of what comes after the phone—and Boland sees AR as an integral part of any "succession plan" for Apple. Kuang agrees. "It's a very forward-looking vision for AR," he says of Apple's approach. "They're treating it as a computing modality rather than a display modality, which is critical." After six years in exile, Edward Snowden explains himself How to practice long-term thinking in a distracted world The suburbanites making the desert bloom with McMansions The Windows 10 privacy settings you should check right now Imagine the views from this Italian-designed Swiss train 👁 How do machines learn ? Plus, read the latest news on artificial intelligence ✨ Optimize your home life with our Gear team’s best picks, from robot vacuums to affordable mattresses to smart speakers. Contributing Editor X Topics AR augmented reality apple Eric Ravenscraft Brenda Stolyar Julian Chokkattu Brenda Stolyar Adrienne So Simon Hill Simon Hill Julian Chokkattu WIRED COUPONS TurboTax Service Code TurboTax coupon: Up to an extra $15 off all tax services h&r block coupon H&R Block tax software: Save 20% - no coupon needed Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Doordash Promo Code 50% Off DoorDash Promo Code + Free Delivery Finish Line Coupon Take $10 off Your Order - Finish Line Coupon Code Groupon Promo Code Groupon promo code: Extra 30% off any amount Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Take Your Ultrawide Monitors Everywhere With an AR Laptop | WIRED"

"https://www.wired.com/story/sightful-spacetop-augmented-reality-laptop-hands-on-news"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Brenda Stolyar Gear Take Your Ultrawide Monitors Everywhere With an AR Laptop Photograph: Sightful Save this story Save Save this story Save the concept of working from home has been utterly redefined in the past few years. As long as there’s Wi-Fi and a computer, many people can technically work from anywhere. But for those who have gotten used to clicking through multiple monitors or walking at a standing desk , working away from the house requires schlepping around a bunch of peripherals in order to be productive. But what if you didn’t have to crouch over a dark, tiny laptop screen at the coffee shop? Now you can harness the power of a multi-monitor setup with a pair of augmented reality (AR) glasses and a keyboard. Created by a new company called Sightful , founded by former executives of Magic Leap, Spacetop does exactly that. As the world's first AR laptop, it delivers the convenience of a virtual 100-inch screen with the ability to display as many windows and apps as you need to get work done from wherever you are. It’s available for purchase through an invitation-only early access program for $2,000. Delivery to those selected will start in early July. Anyone can apply, but Sightful says it's specifically looking for “enthusiastic early adopters” who will provide feedback the company can use to refine the experience. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Updated May 18: An earlier version of this article stated the Spacetop has a Qualcomm Snapdragon 845 processor. It's powered by the Snapdragon 865. We've corrected the story to reflect this. I spent only a brief time with Spacetop, but I was surprised at how little there was to it. It's a pair of glasses connected to a full-size keyboard with a touchpad connected by a wire. At 3.3 pounds, it's only slightly heavier than the latest 2.7-pound MacBook Air and compact enough to easily slide into your backpack or tote. To help bring Spacetop to this current form, Sightful pulled existing hardware from NReal (known for its AR glasses) and Wistron (an electronics manufacturer that works with laptop brands like HP and Dell). But the company spent time customizing the device, adding well-thought-out features to enhance the experience. The glasses went through multiple iterations to ensure they're comfortable to wear for long periods, without leaving marks on your face, snagging hair, or messing up makeup. The headset has also been optimized for viewing content up close, such as reading text. There's a physical button on the right arm that controls display brightness. You can order the AR glasses with prescription lenses at no extra charge (with invite-only access). Your Spacetop will then ship with a pair of custom-ground lenses magnetically attached. I typically wear AR and VR headsets on top of my glasses, so I was relieved to be able to test the device with lenses that matched my prescription. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Photograph: Sightful The keyboard is equipped with its share of custom-built features, including a mini display for QR codes, a cradle for the glasses, and custom LEDs for tracking the keyboard depending on how bright your surroundings are. As for standard features, the keyboard has two USB-C ports, both of which support power delivery fast charging (up to 65 watts), DisplayPort 1.4 (for external Full-HD screen support), and SuperSpeed USB up to 10 gigabits per second. There's a 3.5-mm headphone jack too. And it packs support for Wi-Fi 6, Bluetooth 5.1, and 5G (Sub-6) connectivity, so you can connect a mouse or other accessories. The keyboard also has a 5-megapixel camera sensor (2,560 x 1,920 resolution) that you can use for video calls. I didn't get to test it, but I couldn't help but notice that the low camera placement (below eye level) might look awkward in Zoom or Skype. It reminds me of the front-facing camera on an iPad, which sits on the side when the tablet is in landscape mode, but you could plug in an external camera via a USB-C port. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Under the hood is a Qualcomm Snapdragon 865 with a Kryo 585 eight-core CPU and Adreno 650 GPU. Sightful says it chose the 865 in part because of its real-time computer-vision capabilities coupled with extremely low battery consumption. You also get 8 gigabytes of memory and 256 gigabytes of storage. As for battery life, Sightful claims five hours at full use, which isn't a lot compared to other laptops that average nine or 10 hours (or more). At least you can recharge the Spacetop from 0 percent to 85 percent in less than two hours. It runs the company's proprietary operating system, Spacetop OS. As Sightful puts it, “If it's accessible on the web, it works with Spacetop.” So you'll have access to Google Workspace, Slack, Microsoft 365, and more, in addition to videoconferencing apps like Zoom, Microsoft Teams, and Google Meet. Judging from these specs alone, this isn't an ultra-powerful machine. It's not meant for handling intensive, graphically demanding work or power-hungry programs. At most, you'll be able to use it for basic tasks like web browsing, sending emails, video chatting, and messaging, simultaneously. Photograph: Sightful I've attended a lot of tech demos in my career, and I'm used to sitting through long tutorials before laying a finger on a new device—or else being micromanaged the entire time. So I was a little taken aback when Sightful founders Tamir Berliner and Tomer Kahan placed Spacetop in front of me without first demonstrating it themselves. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So This approach proved how simple and intuitive it is. I just put the glasses on and got to work. Greeted by a sea of apps, I sent a test email to myself, resized and moved windows around, and watched a video on YouTube, all with a few clicks of the keys on the keyboard and taps on the touchpad. Spacetop OS is extremely bare-bones, but it's identical to navigating a standard laptop. If you've used a computer, you can use Spacetop without any explanation required. With 1080p resolution per eye, the graphics and text looked crisp and clear enough to work with for long periods. You can also move freely around the room—all I had to do was press a couple of buttons on the keyboard to align the windows so they were in front of me again. Performance felt swift from what I saw, but I didn't get the chance to put it through its paces. The glasses, on the other hand, are another story. Don't get me wrong—they're comfortable. I wore them for most of the demo, which lasted about 40 minutes. There's even a handy Reality mode that basically acts as a screen saver so you can see what's actually in front of you. And, looking in the mirror afterward, I didn't see any telltale red marks that would reveal I'd been wearing an AR headset 10 minutes before. But I would have social anxiety wearing them in public. They just don't look like regular glasses. While they're certainly sleeker than a clunky virtual reality headset , they're not the most discreet. They look like a mix between swim goggles and safety glasses. I'm not sure I'd be able to sit in a coffee shop or on a flight without worrying about the weird stares I'd get. I'm generally skeptical about AR and VR, especially when it comes to the workplace. When the pandemic hit, I spent a few months working in Spatial , the VR videoconferencing app, but the novelty wore off every time I had to race to put on the headset so I wasn't late for a meeting. We're still not using Meta Horizon Workrooms ; it turns out that the only thing worse than a work meeting is a work meeting where you beam into a cartoon conference room and sit next to your coworkers’ cringe avatars. Tech giants aside, Spacetop isn't even the only startup working on bringing AR to the masses. As just one example, Nimo's smart AR glasses are still somewhere in gadget purgatory. After three years of watching this rigmarole, I've grown to appreciate a boring, reliable laptop, monitor, and webcam. But the best part about Spacetop is that the computer won't fundamentally change how we work. It just adapts to the way the workspace has changed, allowing us to take virtual versions of our ordinary desk setups wherever we want. As someone whose setup has grown to three external monitors, the ability to stretch my tabs and windows across multiple screens now makes or breaks my ability to focus. It's hard for me to work anywhere other than from home, which makes conferences or traveling a little difficult. One day, I will be free of the cramped screens of a portable monitor, at a coffee shop, on a flight, or in the car. Here's to hoping I'll eventually get used to wearing those funny-looking glasses though. You Might Also Like … 📩 Get the long view on tech with Steven Levy's Plaintext newsletter Watch this guy work, and you’ll finally understand the TikTok era How Telegram became a terrifying weapon in the Israel-Hamas War Inside Elon Musk’s first election crisis —a day after he “freed” the bird The ultra-efficient farm of the future is in the sky The best pickleball paddles for beginners and pros 🌲 Our Gear team has branched out with a new guide to the best sleeping pads and fresh picks for the best coolers and binoculars Product Writer & Reviewer X Topics Shopping laptops androids augmented reality remote work Boone Ashworth Boone Ashworth Eric Ravenscraft Adrienne So Medea Giordano Erica Kasper Julian Chokkattu Nena Farrell WIRED COUPONS TurboTax Service Code TurboTax coupon: Up to an extra $15 off all tax services h&r block coupon H&R Block tax software: Save 20% - no coupon needed Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Doordash Promo Code 50% Off DoorDash Promo Code + Free Delivery Finish Line Coupon Take $10 off Your Order - Finish Line Coupon Code Groupon Promo Code Groupon promo code: Extra 30% off any amount Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. 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"Microsoft’s HoloLens 2 Puts a Full-Fledged Computer on Your Face | WIRED"

"https://www.wired.com/story/microsoft-hololens-2-headset"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Lauren Goode Gear Microsoft’s HoloLens 2 Puts a Full-Fledged Computer on Your Face Microsoft wants the HoloLens 2 to be the most advanced mixed reality computer out there. Quinn Russell Brown Save this story Save Save this story Save If you ask Alex Kipman to name the most significant advancement in the brand-new version of HoloLens, Microsoft’s mixed-reality headset, he’ll say the answer is yes. It's not an evasion of the question—it's evidence of his excitement. Kipman, Microsoft’s technical fellow for AI and mixed reality, gets excited about “all of the things” in the HoloLens 2. When pressed, though, it comes down to three key improvements: It's more comfortable, it’s more immersive, and it offers more out-of-box value than the first HoloLens. Kipman uttered this mantra—“comfort, immersion, out-of-box value”—frequently during my day-long visit to Microsoft's headquarters last month, like someone who had been well coached by his communications staff. Later, when an editor asked me what was new about the new HoloLens 2, I realized the mantra was still rattling in my brain, as though it had been transmitted through the headgear. The new HoloLens 2 is more comfortable than the first headset, and more immersive. Its diagonal field of view has more than doubled, with Microsoft wielding a new kind of patented imaging technology. It has an AI processing unit and now connects to Azure, Microsoft’s cloud service. Alex Kipman, Microsoft’s technical fellow for AI and mixed reality, wearing the HoloLens 2 Quinn Russell Brown Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Whether the $3,500 headset provides more out-of-box value is a call for its commercial customers to make. This isn’t a headset you’ll use for gaming or for sending interactive poop emoji to friends, or one that the average consumer will ever wear at all. It’s not for “knowledge workers” like me and Kipman, people who sit at their desks all day, he says. It’s for people whose jobs are being digitally transformed—people who work in design or manufacturing, who fix gear shifts and work on oil rigs, military personnel. Try to forget, for a second, that HoloLens is a headset. Kipman thinks about it more as a full-fledged computer for a futuristic world of remote workers in need of expertise. And Microsoft is determined to make it the most advanced mixed-reality computer out there. That much is clear, even if all of the use cases for it haven’t crystallized yet. To grasp the significance of HoloLens 2, it helps to know its origin. The earliest seeds for HoloLens were planted as far back as 11 years ago. It was borne out of Kinect, the Xbox peripheral product that used a variety of sensors to compute depth maps and recognize humans within its field of view. Kipman is credited with inventing Kinect, and in 2010, he began channeling some of the Kinect's technology into a head-mounted holographic computer. It was known then as Project Baraboo, but it would later become HoloLens. When HoloLens officially launched in 2016, it was a 1.3-pound head-mounted display with depth-sensing cameras and an optical projection system that beamed holographic images directly into your eyes. While wearing one, you might see anything from a floating web browser to a cartoon fish in a bathtub to a three-dimensional motorcycle—all while still seeing the real world around you. Or you might see a remote technician pop up in your eye frame and show you how to fix a light switch. It isn’t a consumer device now, and it certainly wasn’t then, but Microsoft was trying to show off a wide variety of applications that could be easily grasped by regular people. The HoloLens was available only to developers when it first launched, since Microsoft wanted to spur development of new apps. (No AR or VR headset is worth the money without compelling apps; that was true then and is still true now.) Later that year, a version of HoloLens started shipping to any consumer in the US or Canada who had $3,000 to spend. The first HoloLens wasn’t a “success” in the way that you might describe the success of other technology products, whether that’s based on sales, ecosystem lock-in, or pure cachet. In some ways, it wasn’t meant to be a blockbuster hit in a public-facing way. But it was the first mixed-reality wearable that ran on a holographic-specific operating system—and it wasn’t a pair of lightweight smart glasses. It was an untethered headset running Windows 10, which meant it was an actual working face computer. Still, early customers had their complaints: It was heavy, it was unwieldy, it didn’t feel immersive enough. And Microsoft heard them, loud and clear. One of the most obvious updates to HoloLens 2 is its build. The first HoloLens was front-heavy, a whole bunch of components loaded onto your forehead. For this new version, Microsoft split up the pieces, positioning the lenses and some computing power in the front and moving the rest of it to the back. Microsoft’s senior director of design, Carl Ledbetter, calls this a split-architecture design. It came loaded with its own engineering challenges, because cables had to run between the front and back parts of the headset. These are now built into the arms of HoloLens 2. Ledbetter says this new form factor was critical to achieving a certain level of comfort and balance on the new model. “With HoloLens version one, there were just a lot of things we didn’t know we didn’t know,” Ledbetter says as he leads me around Microsoft’s Human Factors lab. “But luckily, since it’s been out there for three years, we’ve been able to talk to a lot of customers.” Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft The Human Factors lab is a cavernous space filled with as many mannequin heads as human ones; the latter are bent over their desks, toiling on the latest designs. There are also ear molds, gesture-control wristbands, custom-made eye depth gauges. For the past three and a half years, Lebetter and his team have used these tools to design a new HoloLens headset that would fit well on 95 percent of heads, regardless of gender, ethnicity, or age. It’s not just about finding the right fit, Ledbetter says, but about having empathy for the wearer. At one point, he hands me an intentionally oversized Xbox gaming controller. “There,” he says. “You’re five years old.” Ledbetter and his team have scanned over 600 human heads in the Human Factors lab. A hundred other people have been put through “stress tests” with HoloLens 2 prototypes—asked to watch a long movie or play the tabletop game Jenga or converse with other humans. The goal was to have people forget they were wearing it, ideally for up to two hours. In some cases, “we were getting more than two hours, and people weren’t taking it off at all,” Ledbetter says. Some tests involved sensors, attached to subjects’ necks, that measured muscle load or fatigue. Ledbetter claims, based on this data, that the new HoloLens is three times as comfortable as the old one. I wore HoloLens 2 for a few brief demos during my visit to Microsoft, and it’s undeniably more comfortable than the first version. It also weighs less, though in mere grams. The click-wheel on the back of the headset, which loosens or tightens the HoloLens around around your face, is less clicky than the first one. Microsoft says the battery life should match the first HoloLens, so, around three and a half hours. Kipman says he looks forward to the day when people run out of battery life on the HoloLens, meaning, they've worn it for a session that long. A series of 3-D printed molds of what would become the brow pad on HoloLens2 Quinn Russell Brown There are material upgrades too. The front enclosure is made of carbon fiber, which is supposed to keep it cool and light. It has anodized aluminum cooling channels that dissipate heat from the headset’s custom-made processor. The silicone back pad, the part that’s affixed to the back of your head now like a gray piece of toast, has a microtexture that’s designed to give just the right amount of grip without ripping your hair out. The thing that might make the most difference, at least for Microsoft’s target audience, is an old trick applied to a new headset: The front enclosure can now be flipped up, like cool-dude clip-on sunglasses. If you’re working in the field or on an assembly line and need to quickly switch between holographic instructions and conversing with a real live human being, you can just lift the lens up. Kipman delights in showing this off, lifting the “visor” up, pulling it down again. “Holograms everywhere!” he says when the lens enclosure resumes its downward position. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft These new features—the split architecture, its cooling mechanisms, the hinge that made visor mode possible—were in the works before the optics on HoloLens 2 were finalized, Ledbetter says. But the optics are what make holograms happen. The optics are by far the most interesting part of this new HoloLens. Last summer, news reports emerged that Microsoft had filed a patent with the US Patent and Trademark Office back in 2016 that described expanding the field of view on a display using MEMS laser-scanning technology. MEMS refers to microelectromechanical systems, which involve miniaturized electrical and mechanical components. According to academic journals, lasers have been a part of MEMS research and applications for decades. That part of Microsoft’s patent filing wasn’t new. What was new was Microsoft’s proposed method of modulating MEMS mirrors to direct lasers in a way that created greater angles, and as a result, a larger field of view. On the original HoloLens, the field of view—that virtual eye box through which you see holographic content—was not very big. At all. The stuff you were looking at often got cut off or edged out of frame if the object was too big for the window, or if you moved your head a certain way. Jeremy Bailenson, the founding director of the Virtual Human Interaction Lab at Stanford University, cowrote a 2017 white paper about the social influence of “virtual humans,” having used AR and VR headsets as part of the study. In it, the writers describe in painful detail the limitations of the HoloLens’ narrow field of view. “From an empirical standpoint, we know that field of view is critically important,” Bailenson tells WIRED. “It causes people to have a better overall experience, because they can move their head in a natural way.” So this was obviously one of the aspects of HoloLens that Microsoft had to improve upon. And it did. The first HoloLens had a 34-degree diagonal FOV; the new headset’s field of view has “more than doubled,” Kipman says, to a 52-degree diagonal field of view. (Microsoft declined to share exact measurements for this new eyebox, saying that the x-axis and y-axis are not the best way to think about the FOV improvements. But much of the expansion was in the vertical dimension.) Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft The HoloLens optics team also managed to maintain a resolution of 47 pixels per degree while expanding the box. This means that, while the first HoloLens had the equivalent of two 720p displays, one for each eye, this new face computer has the equivalent of a 2K display for each eye. And the lens stack has been reduced, going from three lens plates down to two. In my own experience wearing HoloLens 2, I still found myself coming up against the edges of the eye box. A hologram of a woman named Hannah, who gave me a rundown of Microsoft’s campus construction project in a taped holographic video, still became headless or footless if I moved too close to her. Same with the tops of windmills, which were part of a topography demo later in the day, one in which I could use my (real) hands to pinch and zoom the holograms in a new way. So, while the field of view has been improved and the content appears to be more crisp, we’re not quite at the point of holograms, uninterrupted just yet. Both Kipman and Zulfi Alam, who manages Microsoft’s optics engineering team, acknowledge that the visual experience on HoloLens 2 isn’t totally immersive yet. It’s the mechanical method by which they’ve increased the field of view, though, that they appear to be most excited about. The MEMS mirrors that Microsoft is using are the “largest small mirrors in the world,” Alam says. The mirror looked like a speck of debris on a conference room table; when I picked it up to peer at it, I could see it was a tiny reflective disc on my finger tip. Normally, with a DLP, LCD, or LCoS projector in a headset, light particles are spit out, refracted, bounced off of lenses, and beamed back into your eyes, essentially tricking them into seeing holograms. (The original HoloLens used a LCoS projector.) And HoloLens has enough sensors to know your head position in space, so it knows where to beam these images into your pupils into order to convince you you’re seeing things. Using the MEMS mirrors, which are strobing 54,000 times per second, HoloLens 2 is now splitting that light apart and reconstituting it at every single pixel. “It’s replicating your pupil multiple times,” Alam says. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft The benefit to doing it this way, he says, is that when you want to increase the field of view, you just change the angles of the mechanical system. You don’t have to build a bigger backplane to create a bigger field of view, which would then increase the overall size of the product. Like HoloLen’s physical redesign, this innovation also presents new challenges—such as developing the software to make this all work properly. “The control logic becomes very complicated,” Alam says. That’s all on the inside. Externally, HoloLens has to make itself useful to the enterprise customers who will be using this thing out in the wild. Microsoft has done some work there too. For example, HoloLens 2 supports more advanced gesture controls. Before, you could use your finger in a Redrum-like way to select holographic tiles that appeared before your eyes. You could also use a “bloom” gesture, a kind of hand-cupping motion, to go back to the Start menu on your holographic desktop. If you gazed at a holographic app icon long enough, you could highlight it. Now you can walk up to a virtual object in HoloLens 2 and manipulate it with your hands, twirl it, resize it, even press or punch it. The headet’s new eye-tracking tech means you can read a news story on a holographic browser, and the page will scroll for you—look, Ma, no hands. All of the earlier gestures still work, but it’s these new kinds of interactions that Microsoft believes will help usher us into a reality where mixed reality feels more natural. The author wearing HoloLens 2 Quinn Russell Brown Microsoft is also touting new cloud-based “spatial anchors,” designed to let people access holographic app features even if they’re not wearing a HoloLens. Let’s say I’m wearing a HoloLens 2, but you’re not; you’re on an iPhone or Android smartphone. Both of us should be able to look at that holographic rendering of Microsoft’s campus construction project at the same time, provided that the app developer built the app that way. Since app developers are still a critical piece of the HoloLens ecosystem, Microsoft is rolling out what it calls Dynamics 365 Guides, a prebuilt set of software features that will slot right into instructional apps for HoloLens. Want to teach someone how to fix the gear shift on an ATV? It should take you mere minutes to build that HoloLens app, Kipman says, not months. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft But Kipman, who has been at Microsoft for 18 years, sees HoloLens as something much bigger than just a headset that runs hologram apps. To him, it’s part of a technological revolution, one that happens every 30 years or so. In the 1950s there was the CPU; in the 1980s, the GPU. Each was responsible for handling a certain amount of computing workload. “Thirty years later, notice the pattern,” he says. “You can call it whatever you want, and we happen to call it the holographic processing unit, but the devices of the future will all have a CPU, a GPU, and some type of AI unit.” HPU 1.0 was the first instance of Microsoft’s holographic processing unit. HPU 2.0, present in the new HoloLens, is “perfect for algorithms, for machine learning,” Kipman says. “We also created deep neural-network cores that are optimized to run these models.” HoloLens 2 also now connects directly to Microsoft’s Azure cloud service, which Kipman says makes the head computer “light up in a different way.” This means that certain AI tasks are offloaded to the cloud, which results in more precision—like the difference between one-centimeter spatial mapping and one-millimeter spatial mapping—but might also take a few extra seconds for the headset to process things. Kipman insists that certain enterprise customers are OK with that latency. “I think if you’re talking about vision picking, the hot new thing in the logistics industry, where front-line workers process packages without scanners in their hands, you might go with something much lighter,” says J. C. Kuang, an analyst at Greenlight Insights who closely covers AR and MR. “That’s when you might go with Google Glass or an older model of Vuzix. But if you move into, say, architectural engineering construction to look at data on a work site, a much more involved computational process, then there are benefits to using HoloLens with AI operations running in the cloud.” Plus, Kuang adds, it makes sense that Microsoft would use Azure in any way it could. “In a vacuum, without even talking about augmented reality, Azure is evolving into a more and more important revenue stream for Microsoft,” he says. Attaching HoloLens to Azure might also be part of a larger strategy: one that allows Microsoft to avoid the “hype cycle,” as Kipman puts it. There are products, he says, that everybody believes will take over the universe overnight, which then leads to a “trough of disillusionment, because it doesn’t do that.” Some products make it to the other side of the chasm; some find their place in a niche market. But they’re not going to take over computing. “Then there are those things that are transformative,” Kipman says. “They really do live side by side with other eras of computing and push forward democratization and innovation to an order of magnitude. I do believe mixed reality is that. But, you know, we haven’t---and we’re not going to---overhype it.” Kipman, his mantra temporarily forgotten, was suddenly crystal clear. Amazon Alexa and the search for the one perfect answer The Russian sleuth who outs Moscow's elite spies AI-fueled apps could set us free— or make us less human The triumphant rediscovery of the biggest bee on Earth Facebook tamed the feral internet—and that’s too bad 👀 Looking for the latest gadgets? Check out our latest buying guides and best deals all year round 📩 Get even more of our inside scoops with our weekly Backchannel newsletter Senior Writer X Topics Microsoft augmented reality Eric Ravenscraft Brenda Stolyar Simon Hill Simon Hill Brendan Nystedt Scott Gilbertson Julian Chokkattu Reece Rogers WIRED COUPONS TurboTax Service Code TurboTax coupon: Up to an extra $15 off all tax services h&r block coupon H&R Block tax software: Save 20% - no coupon needed Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Dyson promo code Extra 20% off sitewide - Dyson promo code GoPro Promo Code GoPro Promo Code: save 15% on your next order Samsung Promo Code +30% Off with this Samsung promo code Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Google Glass 2.0 Is a Startling Second Act | WIRED"

"https://www.wired.com/story/google-glass-2-is-here"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Steven Levy Backchannel Google Glass 2.0 Is a Startling Second Act Google Glass 2.0 is here, and it's found a home in an unexpected place: Factories. Courtesy of AGCO Save this story Save Save this story Save Don’t call Heather Erickson a glasshole. Yes, that’s Google Glass on her frames. But she’s not using it to check her Facebook, dictate messages, or capture a no-hands video while riding a roller coaster. Erickson is a 30-year-old factory worker in rural Jackson, Minnesota. For her, Glass is not a hip way to hang apps in front of her eyeballs, but a tool—as much a tool as her power wrenches. It walks her through her shifts at Station 50 on the factory floor, where she builds motors for tractors. Steven Levy is Backchannel's founder and Editor in Chief. Sign up to get Backchannel's weekly newsletter. No one at Erickson’s factory is concerned that the consumer version of Glass, after an initial burst of media glory, was condemned for bugginess and creepiness, then ushered into a gadget version of the Bardo. The original Glass designers had starry-eyed visions of masses blissfully living their lives in tandem with a wraparound frame and a tiny computer screen hovering over their eye. But the dream quickly gave way to disillusionment as early adopters found that it delivered less than it promised—and users became the target of shaming from outsiders concerned about privacy. Within three years, Alphabet (the parent company of Google and its sister company, the “moonshot factory” called X) had given up Glass for good—or so people assumed. What they didn’t know was that Alphabet was commissioning a small group to develop a version for the workplace. The team lives in Alphabet's X division, where Glass was first developed as a passion project of Google cofounder Sergey Brin. Now the focus was on making a practical workplace tool that saves time and money. Announced today , it is called Glass Enterprise Edition. More From This Edition John Pavlus Meredith Rutland Bauer Karen Wickre Scott Rosenberg That’s what Erickson wears every day. She works for AGCO, an agricultural equipment manufacturer that is an early adopter of Glass EE. For about two years, Glass EE has been quietly in use in dozens of workplaces, slipping under the radar of gadget bloggers, analysts, and self-appointed futurists. Yes, the population of those using the vaunted consumer version of Glass has dwindled, tired of being driven out of lounges by cocktail-fork-wielding patrons fearing unwelcome YouTube cameos. Meanwhile, Alphabet has been selling hundreds of units of EE, an improved version of the product that originally shipped in a so-called Explorer Edition in 2013. Companies testing EE—including giants like GE, Boeing, DHL, and Volkswagen—have measured huge gains in productivity and noticeable improvements in quality. What started as pilot projects are now morphing into plans for widespread adoption in these corporations. Other businesses, like medical practices, are introducing Enterprise Edition in their workplaces to transform previously cumbersome tasks. The difference between the original Glass and the Enterprise edition could be summarized neatly by two images. The first is the iconic photo of Brin alongside designer Diane von Furstenberg at a fashion show, both wearing the tell-tale wraparound headband with display stub. The second image is what I saw at the factory where Erickson works, just above the Iowa state line and 90 miles from Sioux Falls, South Dakota. Workers at each station on the tractor assembly line—sporting eyewear that doesn’t look much different from the safety frames required by OSHA—begin their tasks by saying, “OK, Glass, Proceed.” When they go home, they leave their glasses behind. Left: Frazer Harrison/Getty Images. Right: Courtesy of AGCO. These Jackson, Minnesota, workers may be onto something. A recent Forrester Research report predicts that by 2025, nearly 14.4 million US workers will wear smart glasses. It wasn’t referring to fashion runways. It turns out that with Glass, Google originally developed something with promising technology—and in its first effort at presenting it, failed to understand who could use it best and what it should be doing. Now the company has found a focus. Factories and warehouses will be Glass’s path to redemption. A workplace version is quite a shift for one of the most hyped products in Google’s history. Glass first dropped into public consciousness five years ago as the featured product of Google’s big I/O conference in 2012. Literally dropped, as thousands of attendees watched a free fall from the point of view of a team of Glass-equipped skydivers hurtling toward the roof of San Francisco’s Moscone Center. The elaborately planned stunt set the tone for the launch of a product that was nowhere near ready for reliable use when it was released a year later. Google acknowledged that by calling early buyers “Explorers”—virtual Shackletons who knew they were venturing into a treacherous realm. Still, first impressions were rhapsodic: Time declared Glass one of the best products of the year, and everybody from Prince Charles to Beyoncé clamored to try it out. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg But soon Glass's failings became apparent. It was buggy, it felt awkward, and it really didn’t have a clear function. Then came a backlash from people interacting with Glass users, who worried that their private moments would be captured by stealthily recorded video. Establishments began banning Glass. The project simply wasn’t working. “When we originally built Glass, the work we did on the technology front was very strong, and starting the Explorer program was the right thing to do to learn about how people used the product,” says Astro Teller, who runs the X division. “Where we got a little off track was trying to jump all the way to the consumer applications.” He pauses. “We got more than a little off track.” In time, Glass jumped the track entirely, going dark in January 2015. Its website read, “Thanks for exploring with us”—and that seemed to be the finale, even as the company also promised, “The journey doesn’t end here.” Related Stories Uncategorized Steven Levy Uncategorized Steven Levy Gear Mat Honan In fact, a different journey had already begun. Even as the sound of breaking Glass was reverberating in the tech press, some early adopters were discovering that Glass was a powerful solution to a problem vexing the workplace. Workers who need real-time information—and both hands free—were natural beneficiaries of what Glass had to offer, even if Google hadn’t figured that out yet. It’s a choice between an immersive form of augmented reality, which overlays digital information on top of the real world, and an alternative that lets workers shift between the virtual and the actual. Some companies in the enterprise sector have been singing the praises of “mixed reality” helmets that overlay graphics and information onto a camera-captured display of the real world. But these are costly, bulky, and not well suited for routine tasks on a factory floor. In cases when all a worker needs is real-time access to information, a big helmet that takes over your entire field of vision is overkill. Smart glasses are a lightweight version of augmented reality—some people call this “assisted reality”—offering a computer display that one could view simply by shifting one’s gaze and taking in the rest of the world as it is. It’s cheaper and more comfortable than going full immersive. Without direction from Google, these companies began to purchase Explorer Edition units of Glass and use them with custom software to tackle specific tasks for their corporate customers. And Google noticed. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “We talked to all of our explorers and we realized that the enterprise space had a lot of legs,” says Jay Kothari, who now is project lead on the Glass enterprise team. Also noticing was Brin himself, who, according to Teller, reported the interest from corporations and suggested that a dedicated team might work on a specialized version of Glass to serve them. In April 2014, Google started a “Glass at Work” program that highlighted some of the early developers. And that year when a few people from X visited Boeing, which was testing Glass, they reported that their minds were blown by a side-by-side comparison of workers doing intricate wire-framing work with Glass’s help. It was like the difference between putting together Ikea furniture with those cryptic instructions somewhere across the room and doing it with real-time guidance from someone who’d constructed a million Billys and Poängs. Courtesy of Google The company decided to work on a version of Glass that would be totally separate from the consumer version. Then came the tricky part of where that team might live. Glass had supposedly “graduated” from X, but Alphabet put the Enterprise team back there. One reason was that an ace engineer named Ivo Stivoric was now a senior director at X. Stivoric had been steeped in wearables for almost two decades, co-heading a lab at Carnegie Mellon and cofounding a company called BodyMedia that was bought by Jawbone. “He literally was doing this 20 years ago,” says Teller. Also, the head of X’s rapid evaluation team, Rich DeVaul, had a background in wearables. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The eventual customers for this new version—from small businesses to huge corporations—had already been dealing with independent startups that adapted Glass for specific workplaces. The Glass team at X formalized that structure, creating an ecosystem that would support “solution partners” who would work with the Glass Enterprise team directly, including buying the actual devices from Alphabet. The partners would then sell the complete hardware and software package to corporate customers. The main task of the Enterprise team in X was creating a new model of Glass itself, improved for the rigors of the workplace and optimized with new features that the customers were clamoring for. In January 2015, they began shipping the resulting Enterprise Edition to the solution partners. Perhaps because of the unhealed wounds of the consumer fiasco, Google asked customers not to reveal the existence of EE. (Any pictures of their use of Glass had to show them using the Explorer Edition.) Those still using the original Explorer Edition will explode with envy when they see the Enterprise Edition. For starters, it makes the technology completely accessible for those who wear prescription lenses. The camera button, which sits at the hinge of the frame, does double duty as a release switch to remove the electronics part of unit (called the Glass Pod) from the frame. You can then connect it to safety glasses for the factory floor—EE now offers OSHA-certified safety shields—or frames that look like regular eyewear. (A former division of 3M has been manufacturing these specially for Enterprise Edition; if EE catches on, one might expect other frame vendors, from Warby Parker to Ray-Ban, to develop their own versions.) “We did a lot of work to lighten the weight of the frames to compensate for the additional weight [of the Pod],” says Kothari. “So the overall package with Glass and the frames itself actually comes out to be the average weight of regular glasses.” Other improvements include beefed-up networking—not only faster and more reliable wifi, but also adherence to more rigorous security standards—and a faster processor as well. The battery life has been extended—essential for those who want to work through a complete eight-hour shift without recharging. (More intense usage, like constant streaming, still calls for an external battery.) The camera was upgraded from five megapixels to eight. And for the first time, a green light goes on when video is being recorded. (Inoculation against Glasshole-dom!) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “It looks very similar to original Glass but improves on every aspect of it,” says Brian Ballard, CEO of Upskill, one of the most prolific of the so-called solution providers. “They had seen how we were using it, and rethought everything—how you charge it, fold it up, prevent sweating, wifi coverage.” Ballard says that the new version was essential for the pilot programs his big customers were running to become fully integrated into the workflow. “For our market we desperately needed a product with a brand like Google behind it. Our customers don’t buy things from Kickstarter.” Today’s announcement, which frees corporate users from keeping silent about the EE edition and opens it up to countless more businesses, is a milestone in the resurrection of a technology left for dead. “This isn't an experiment,” says Kothari. “It was an experiment three years ago. Now we are in full-on production with our customers and with our partners.” Yep. Glass is back. I saw Glass in action myself when I visited the AGCO factory in Jackson this month. AGCO is a $7 billion company that makes big farm equipment like tractors and sprayers under brand names like Challenger and Massey Ferguson. Its Jackson facility, which added the tractor assembly line in 2012, is a fairly high-tech operation, with a few autonomous robot carts roaming the aisles. 850 people work there. The expensive equipment that AGCO manufactures is most often custom-ordered by the user, so almost every unit constructed is a “snowflake” with a virtually unique set of features. In order to keep track of the specifications of each vehicle, AGCO originally had its workers consult laptops—which required a walk of about 50 feet and disrupted the work flow. “Sometimes someone was already using the computer, and then you’d have to find another,” says Heather Erickson. The company experimented with tablets, but even the heavy-duty industrial ones it bought typically lasted only a week in the punishing environment. Then someone suggested to Peggy Gulick, the director of business process improvement in Jackson, that AGCO try out this new thing called Google Glass. Gulick convinced her boss to buy a single Explorer unit. They got it in 2013 and were encouraged by its potential. It also seemed sturdier than a competitor in the marketplace, Vuzix’s Smart Glasses. But to adapt this consumer device to their workplace, they’d need a solutions provider. After weeks of trying to find one, and wasting a few months with one that didn’t work out, she finally connected with a Belgium-based company called Proceedix. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Working with Proceedix, AGCO began to tackle all the potential issues, from security—the Explorer couldn’t connect to an enterprise network—to device tracking and safety. “We weren't going to risk our employees' having headaches and other issues,” she says. (Indeed, some workers reported headaches before they got used to it.) All of that took months, but AGCO believed it would be worth it. “We knew the value of wearable technology when we first put it on the floor,” Gulick says. “In our first test in quality, our numbers were so high in the value it was adding that we actually retested and retested and retested. Some of the numbers we couldn't even publish because the leadership said they looked way too high.” Watching workers on the floor, you can’t always tell how much Glass is integrated into the process. You simply see people getting parts, bolting, ratcheting, and attaching—every so often swiping and tapping the side of their glasses. Once you see examples of what those workers are seeing, though, Glass’s advantages become more clear. A typical task at AGCO takes 70 minutes, broken into steps of three to five minutes. When a worker begins a step, it’s spelled out on the tiny screen. Menu items offer the options to go to the next step, take a picture, ask for help, and more. When a step is done, the worker says, “OK, Glass, proceed,” and the process repeats. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Heather Erickson. Photo by Steven Levy For tasks they have mastered, workers don’t need to look at the screen. But they can wake it at any time to see where a part must go, and even zoom into an object on the display for more detail. Glass tells them what kind of bolt is needed—a wrong-sized bolt could seriously damage a motor—and specifies which wrench to use and how much torque is required. If a part looks damaged, they can take a picture. Some workers prefer to swipe along the side of the frame to go to the next step; others work mainly via voice commands. Gulick says that not everyone has warmed equally to the process—some older, very experienced workers originally didn’t see how it would help them. “There was initial skepticism, but we got over it,” says Scott Benson, who assembles transmissions. And though a factory is not a cocktail lounge, privacy issues still come up. Gulick says there’s been discussion of installing a “bathroom bar” where people can hang their headsets to make sure that no one is snapping photos. But generally the workers simply accept Glass as part of their toolkit. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg In fact, they have to. “It’s like a torque tool,” says AGCO’s Rick Reuter, who is the Continuous Improvement Manager in Jackson. “It’s required to use a torque tool to torque down the lug bolts on a tire—if you don't do it, you're not following the process. Now, it's required to go through these electronic work instructions as part of your job. So the acceptance is a whole lot more different here than it would be for the public.” Some workers are outright enthusiasts, like Heather Erickson. When she was moved to a different station where the Glass process wasn’t implemented yet, after a few hours she went to Peggy Gulick’s office and asked to speed up the deployment. AGCO now has just over a hundred Glass units (it pays between $1300 and $1500 for each one), and Gulick says that it plans to order between 500 and 1000 more in the next 18 months as it moves the product into all its functions and in other locations. The company is particularly excited about how Glass helps with training—cutting the time from 10 days to only 3. When a company like AGCO embraces new technology, one naturally wonders how far it might take automation—and what that means for jobs. AGCO’s executives think Glass helps tamp down such suspicions. “We’re not using this to replace workers with a robot that does their job better—we’re helping them do their job better,” says Gulick. That’s a theme that other early customers of Glass EE are promoting. Upskill’s executive chairman and the chief economist of one of its customers, GE, co-authored a paper last month in Harvard Business Review entitled “Augmented Reality Is Already Improving Working Performance.” “There’s been concern about machines replacing human workers…” they wrote. “But the experience at General Electric and other industrial firms shows that for many jobs, combinations of humans and machine outperform either working alone. Wearable augmented reality devices are especially powerful.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg GE in particular has been enthusiastic in its Glass tests, claiming a 46 percent decrease in the time it takes a warehouse picker using the product. (Using Glass in this environment is as transformative as in factories—after a successful test, DHL says it plans to roll out Glass in its 2000 warehouses across the globe, where appropriate.) Another pilot project, in GE’s Aviation Division, used EE with a wifi-enabled torque wrench: Glass tells workers whether they are using the proper amount of torque. Eighty-five percent of the workers said that the system would reduce errors. “By the end of this year, we’ll have several sites deploying this,” says Ted Robertson, an engineering manager at GE Aviation. It’s not just blue-collar labor getting results with Enterprise Glass. When engineer and self-described “medical device guy” Ian Shakil first saw a prototype of Glass from some Google friends in 2012, he quit his job and started a company called Augmedix to use the technology to make medical examinations more productive—and more satisfying for patients and doctors alike. When seeing patients, the doctor using this system wears Enterprise Edition glasses and livestreams the entire examination to a “scribe” who may be a pre-med student taking a year off before medical school or, more commonly, a medical transcriptionist in India, Bangladesh, or the Dominican Republic. The scribe takes notes during the exam and, when appropriate, accesses the patient’s case history to provide relevant past readings, freeing the doctor to concentrate on the patient. Courtesy of Augmedix Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “The total time entering data has gone from 33 percent of our day to less than 10 percent,” says Davin Lundquist, the chief medical information officer for Dignity Health, who uses Augmedrix and Glass himself in clinical work. “And direct patient interaction has risen from 35 percent to 70 percent.” Lundquist’s enthusiasm for Glass underlines an irony: The very features that triggered criticism of the consumer version of Glass—the stealthy introduction of external information into real-life settings; the ability to record videos of bystanders unobtrusively—become the most valued features in the Enterprise Edition. “When you hear the word Glass, you think dehumanization, social disruption,” says Shakil. “We’re the opposite—being close to the patient; being able to put your hand on his or her shoulder to comfort them.” An Augmedix scribe at work. Courtesy of Augmedix Why does Glass work so well in those private settings when it so totally flopped in public? Perhaps because in the enterprise world, Glass is not an outgrowth of the intrusive and distracting smart phone, but a tool for getting work done and nothing else. The Enterprise Edition runs only the single application necessary to do the job. There’s no Facebooking, Tweeting, Snapping, notifications, or rage-generating headlines. “Glass in an enterprise setting is not a toy,” says Lundquist. “It’s a tool that enhances our ability to perform as professionals.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Has the doctor ever had patients who associate his eye rig with the consumer product that earned users a certain distasteful rectal sobriquet? “I haven’t had anyone who brought that up,” he says. “My younger patients ask, Is that Glass ? I let them try it out. In most cases my patients feel that it sets me apart as a cutting-edge doctor.” Of course, cutting-edge was what the original Glass was supposed to be—before Glass itself got cut. Will success in the workplace lead to a revival of the consumer edition? So far, the Enterprise effort is being run totally separate from what’s left of the consumer project. Though I tried hard to press Alphabet for a straight answer on the status of the latter effort, if indeed there is a status, all I got was an indication that between X, the Google Cloud division, and Google’s hardware division, there is an intent to keep the vision alive. “None of us have given up on the idea that over time Glass will become less and less intrusive, and that more and more people will use it,” says Teller. “But we're not going to prejudge exactly what that path is—that's where we went wrong last time. We’ll focus on the places that are actually getting value out of that and go through the journey with them, being open-minded about where it's going to go.” Maybe Google should consult Ken Veen, a quality checker in the AGCO factory in Jackson. He’s been using Glass EE for two years there as he tests tractors just off the assembly line. “Before, when I saw a problem, I’d have to write stuff on paper, then go to the computer and type it up,” he says. “Now I hit NOT OK and describe my problem, and it goes right to [the quality team].” Would he be interested in using Glass in his daily life? “I might be,” he says, after some consideration. “I could wash dishes and check my email. That could come in handy.” And then he goes back to testing tractors. 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"Apple Vision Pro Mixed-Reality Headset: Specs, Price, Release Date | WIRED"

"https://www.wired.com/story/apple-vision-pro-specs-price-release-date"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Lauren Goode Gear Apple’s Mixed-Reality Headset, Vision Pro, Is Here Photograph: Apple Save this story Save Save this story Save Apple finally unveiled its plans for a mixed-reality wearable computer today at WWDC, its annual software conference. Photograph: Apple The headset, named Apple Vision Pro, has been in the works for years, with Apple taking its familiar wait-and-see approach while other giant tech companies have dived headfirst into the still-kludgy AR/VR market. The new platform and headset have massive implications for the rest of the market; once Apple wades into a product category, it often both validates the category and obviates competitors. Recently, a report from Bloomberg suggested that top Apple executives have been at odds over the positioning of and release of this headset. None of that tension was apparent on stage today, when Apple chief executive Tim Cook showed off the device in a pretaped demo video. “It’s the first product you look through, and not at,” Cook said. “You can see, hear, and act with digital content just like it’s in your physical space. You’re no longer limited by a display.” “You can relive your most important memories in an entirely new way,” Cook added. “Apple Vision Pro will introduce spatial computing” similar to the way the iPhone introduced mobile computing, he said. Apple Vision Pro starts at $3,499 and will be available “early next year,” according to Apple. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Vision Pro shows an animation when you're immersed. When you want to interact with others, the display switches to show your eyes. Photograph: Apple As previously reported, the Apple headset allows the wearer to see the real or physical world around them, unlike VR headsets that fully envelop the face and limit visibility. There’s a floating “Home View” visible as soon as the wearer straps it on. And scenes in the pretaped video showed a person wearing the headset walking around their home, grabbing a sparkling water from the fridge, indicating that the company expects people will wear this as part of their day-to-day. Or during long flights. Content appears on large virtual screens floating in your actual environment. Photograph: Apple Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So The headset features 4K displays, infrared cameras, and LED illuminators. Company executives also remarked many times that the field of view isn’t limited, which means it’s likely not using the waveguide lens technology common on other augmented-reality headsets (which refract light and cast virtual objects into the wearer’s eyes.) It’s running on Apple’s M2 chip, as well as a new, mixed-reality-specific R1 chip. One of the notable features of the Vision Pro headset is its small dial, which lets wearers alternate between mixed-reality mode—seeing more of the real world—and virtual-reality mode, which offers more immersive face-computing. It also relies on voice input, including Siri, to open and close apps and play media. In the pretaped demo of the new headset, no hand controllers were used. Tiny spatial audio speakers are nestled in the soft headband. As previously reported, the Vision Pro is equipped with an external battery pack, similar to how other augmented-reality headsets, such as NReal’s glasses and Magic Leap’s headsets, have been designed. This sometimes makes for a clunkier experience overall, but it means the headset is lighter. Apple also emphasized the Vision Pro app experience. It’s touting a new technology—to call it new is almost humorous—called Eyesight. When someone is nearby, they’ll suddenly appear in your view, even if you’re using the headset in a more immersive mode. There’s also the option to capture a spatial photo or video from directly within the headset, thanks to a built-in 3D camera. (The same 3D camera will capture your image and create a realistic 3D avatar of you.) Photograph: Apple Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Some of the apps shown—though not fully demonstrated—were native Apple apps, such as FaceTime. You can also send emails, surf the web, and connect with external accessories for work. And, while Apple has been courting select developers for months, the official launch of Vision Pro means other app makers can start building or tweaking their apps for Apple’s latest platform. Microsoft apps, such as Teams, were mentioned during the video demo. Unity-based games will also be portable to the headset. “Apple Vision Pro will change the way we communicate and collaborate,” Cook said, just before welcoming Disney CEO Bob Iger on stage. Iger spoke vaguely of the ways the new platform could create new immersive experiences for Disney fans and teed off a demo of the Disney+ app being used in VR. Disney+ will be available at launch, Iger said. There are no controllers. Eye tracking, gesture tracking, and voice input control every interaction. You can tap your fingers together to select, and flick your fingers to scroll. Photograph: Apple While Apple’s strategy of biding its time before entering a product category has served the company well in the past, its official entry into mixed reality is coming at a curious time. Virtual reality and augmented reality have existed in some form for decades, but so far they have failed to reach mass adoption. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Shipments of VR headsets declined more than 20 percent in 2022, according to research from the International Data Corporation. IDC chalked this up to the limited number of vendors in the market, a challenging macroeconomic environment, and a lack of mass market adoption from consumers.” According to The Wall Street Journal , citing Pitchbook, venture capital investments in VR startups are also down significantly from a few years ago. After $6.3 billion was funneled into VR in 2019, last year’s investments totaled $4.8 billion. (It’s unclear exactly how much of that money is now flowing towards generative AI, the latest wave in the technology hype cycle.) Meta has come closest to making a dent in the VR market: The reasonably priced Meta Quest and Quest 2 VR headsets have sold better than most, with a reported 20 million units sold since the product’s launch. And the company just announced the Meta Quest 3 , a rush job ahead of Apple’s big announcement. According to IDC, Meta headsets comprise nearly 80 percent of the market. Even still, Meta has struggled to sell its much more expensive model, the $1,000 Meta Quest Pro. And it has shoveled billions of dollars into its “metaverse” strategy in order to achieve this modicum of success. The company has said it expects its 2023 losses from Reality Labs, its VR arm, to increase significantly year-over-year. But some remain optimistic about the potential for mixed reality to hit the mainstream, driven partly by Apple’s entry into the fray. After revising its outlook for VR-AR shipments for this year due to weak demand in 2022, IDC said that it still expects shipments to grow 14 percent in 2023 and to continue growing in the five years after that. Jitesh Ubrani, a research manager who tracks mobile and consumer devices, said in an analyst note that "Sony's new PSVR2 and Apple's foray into the space will help drive additional volume, while new devices from Meta and Pico, expected towards the end of 2023, will build momentum for VR in 2024.” Peggy Johnson, the chief executive of AR company Magic Leap, said in an interview with WIRED that Apple’s entry into the market is “absolutely a good thing” for the rest of the industry. “We’ve been largely standing alone for over a decade, working on R&D and trying to get a true augmented-reality system working,” Johnson said. “And there were years before that of technical spending. So it’s great when we see anybody coming into this space, because it helps the whole ecosystem. It’s a big validation.” Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Some app developers are excited by the prospects too. “I think this could be a Tesla Roadster moment for mixed reality,” said Anand Agarawala, cofounder and chief executive of AR/VR company Spatial. “Apple is so good at making hardware, they’re so good at UX, in a way that other folks who have entered the space haven’t been. So I think this could be a real ‘capture the imagination’ kind of year.” It might indeed be a “Tesla Roadster” moment, in the sense that when the electric vehicle first became available, some wondered whether it was a “costly toy” or the start of a new era. In the best-case scenario for Apple, both might be true. This story has been updated with more details about Apple Vision Pro's price and availability. 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All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Apple Vision Pro Hands On: The Opposite of Disappearing | WIRED"

"https://www.wired.com/story/apple-vision-pro-hands-on-demo"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Lauren Goode Gear Hands on With Apple’s Vision Pro: The Opposite of Disappearing Photograph: Justin Sullivan/Getty Images Save this story Save Save this story Save Apple’s long-awaited mixed-reality headset, the Vision Pro, is here. Or not yet here, but announced. In a crescendoed moment of its software conference keynote this morning, Apple executives revealed a pair of smart goggles that portend a post-iPhone world. There’s Apple again, taking a wait-and-see approach. There’s Apple, taking aim at Meta. There’s Apple taking over … your face. I had a hands-on (heads-on?) demo of the Vision Pro headset earlier today, in a building constructed on Apple’s campus specifically to house meetings about this new product. Apple executives declined to go on the record during the demo and subsequent briefing, but it was clear that Apple views Vision Pro as a spatial computing platform, not a singular device. Its standout feature—the ability to adjust the immersion level of your virtual environment—is probably its best selling point, even at $3,500. It means that app makers who want to build 2D overlays of collaboration software can do that, and content creators who want to shoot dinosaur movies in stereoscopic can do that too. Still, Apple is asking consumers to cough up an exorbitant amount of money for a product that has yet to prove its consistent worthiness. And whether it’s a platform or product might not matter to most people in this first iteration of the product. The headset uses eye-tracking, hand gestures, and voice for input. There are no hand controllers. Video: Apple After entering the Vision Pro’s temporary housing situation, I was greeted by an Apple employee who used a Face ID-like app to first scan my face and then, bizarrely, my ears. (The latter was for mapping spatial audio.) Then an Apple-employed optometrist scanned my eyeglasses in order to measure my corrective lens prescription, though I opted to wear contact lenses instead of my glasses, for a more comfortable face-computer experience. What a time to be alive! In a closed meeting room, a headset that had been personally calibrated for me sat on a coffee table. Vision Pro is indeed giving ski goggles, if the ski goggles were imagined by Denis Villeneuve. In the years leading up to this product launch, some blogs have published renderings that suggested a mash-up of preexisting Apple products, and these were not entirely off the mark: The seal of the goggles is reminiscent of the cloth-and-foam seal on the AirPods Max headphones, and the soft strap that runs along the top of the head looks a lot like an Apple Watch wristband. The “digital crown,” or dial, is familiar. Apple’s Vision Pro is a tethered headset, though that depends on what’s considered “tethered” in this strange new world. It’s connected to an external battery, a sleek aluminum pack that will get you two hours of uninterrupted run time. You can also tether the Vision Pro to a Mac, using USB-C, for nonstop Visioning. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So The battery pack. Photograph: Philip Pacheco/Getty Images I assumed this external battery pack meant the headset itself would feel as light as a feather, but it still felt hefty. Once I adjusted both a bigger backstrap and the top soft strap, I went through another calibration process, which concluded with an audible chime of approval. (Still, a light orb appeared in the middle distance throughout my demo.) The Vision Pro interface is intuitive—within a few gestures and taps on the digital crown, I had it down. External cameras obviate the need for hand controllers, because the device sees your hands. And internal eye-tracking cameras see where your eyes are looking, so it knows which app you want to open or close. In home mode, a virtual dock of Apple apps floated in front of me. I could still see the real-life living room surroundings. An AR home screen of Apple apps is as vanilla as it sounds. The app containers themselves were certainly not reinvented, and their icons were not little grabble globules or anything else that conferred volume. They were just … there. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So The more interesting part was how I interacted with them. I opened Photos by first gazing at the app, then pinching my forefinger and thumb together. I scrolled through photos by “grabbing” each image and swiping to the left, and expanded panoramic photos by staring and tapping at the Expand option. I scrolled web 2D pages in Safari using my eyes and a couple fingers. I opened Messages this same way, too, though audio interactions aren’t ready yet, and I wasn’t able to record or send a message. Most content I saw wasn’t fully volumetric, nor could I pinch the apps to scale up or bring myself into them. An Apple representative said that app makers can build these experiences in the future. FaceTime would be, in theory, an opportunity to create an extremely human experience in mixed-reality headsets. In my demo, it didn’t achieve this. The internal cameras within the headset are capable of capturing and regurgitating your face in digital form, a hyperrealistic digital twin that appears before the person you’re chatting with. In my FaceTime demo I chatted with the digital twin of an Apple employee who cheerfully talked me through some of these features. But she seemed disembodied. She was real, but she was also not. I’m afraid I don’t even recall her name. The digital crown lets you dial in the amount of reality you want. Video: Apple While using some apps, the room dimmed around me, which is one of the more compelling parts of Vision Pro. It either auto-magically dims when you’re using certain apps, or it can be manually dimmed using the little dial on your headset. Tap into one of the virtual “Environments” Apple seeded on the demo unit, and the Scandinavian normcore living room would disappear around me. Open Apple TV+ and air-tap into a stereoscopic video reel, then select Cinematic mode, and you might as well be in the Alamo Drafthouse. This is what Apple seems to think is the essence of making this a platform versus a product: You don’t have to choose between AR and VR. Your app can be anything you want it to be. Vision Pro shone in the entertainment category, especially because it was dynamic. I first watched a clip of Avatar 2 in 3D. Then, in a teaser of a new dinosaur-focused series from director Jon Favreau, a dinosaur stomped dangerously close to where I stood in the room based on the positioning of my sensor-filled headset. A digital butterfly fluttered around the room before landing on my outstretched finger. These experiences could absolutely happen in other AR or VR headsets. The difference is that Apple has the ability to entice Hollywood directors and app makers to build them. Apple’s Vision Pro headset has the potential to eventually mainstream AR in a way that other face computers haven’t, simply because it’s Apple. Already developers are expressing excitement about the headset. And again, at $3,500, the first units of the Vision Pro will likely be snapped up by developers and gadget lovers with disposable income. But the Vision Pro is also unlike almost every other modern Apple product in one crucial way: It doesn’t disappear. In fact, it does the opposite. It rests on your face and shields your eyes, sensory organs that are a crucial part of the lived human experience. The same is true of every other heads-up display in the world, whether it’s a pair of AR glasses, an industrial-focused headset, or fully immersive VR goggles. The experience can be remarkable and surreal, for sure; but it requires a suspension of disbelief and a sacrifice of autonomy. Even Apple can’t out-design its way out of what is fundamentally an obtrusive technology. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Every successful Apple product of the past two decades has disappeared into our lives in some way—the iPhone into our pockets, the iPad into our purses, the Apple Watch living on our wrists, and the AirPods resting in our ears. Wearing the Vision Pro for hours on end will call into question what it means to compute, but also, what it means to live in the real world. My forehead felt cool when I took the Vision Pro off after around 30 minutes, a testament to Apple’s considerate design. But my face also breathed with relief, the way it has after using other heads-up displays. The air feels more real out here. 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Is that bad? 🌞 See if you take a shine to our picks for the best sunglasses and sun protection Senior Writer X Topics WWDC apple first looks virtual reality Julian Chokkattu Simon Hill Simon Hill Nena Farrell Nena Farrell Michael Calore Matt Jancer Simon Hill WIRED COUPONS TurboTax Service Code TurboTax coupon: Up to an extra $15 off all tax services h&r block coupon H&R Block tax software: Save 20% - no coupon needed Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Doordash Promo Code 50% Off DoorDash Promo Code + Free Delivery Finish Line Coupon Take $10 off Your Order - Finish Line Coupon Code Groupon Promo Code Groupon promo code: Extra 30% off any amount Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"What Happens After a ‘Million-Mile Battery’ Outlasts the Car? | WIRED"

"https://www.wired.com/story/what-happens-after-a-million-mile-battery-outlasts-the-car"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Maddie Stone Science What Happens After a ‘Million-Mile Battery’ Outlasts the Car? Photograph: Getty Images Save this story Save Save this story Save This story originally appeared on Grist and is part of the Climate Desk collaboration. Electric vehicles (EVs) have a clear environmental advantage over their gas-guzzling counterparts, but when it comes to longevity, the two are in a dead heat. For a car built today, 200,000 miles is considered a good, long run, regardless of whether it’s powered by a lithium battery or an internal combustion engine. But if a flurry of recent reports are to be believed, EVs may soon surge ahead in this long-distance competition—not by mere thousands of miles, but by 800,000. Recently, multiple EV-battery makers have announced the imminent arrival of “million-mile” batteries, power packs that supposedly have enough juice to be driven to the moon and back twice. In May, a top executive at General Motors said the company was “ almost there ” on development of a million-mile battery; in June, Chinese battery maker Contemporary Amperex Technology told Bloomberg it was ready to produce batteries that last 1.24 million miles. For months, rumors have swirled that Tesla will soon roll out a million-mile battery on its own. Its 2019 Impact Report , released in early June, certainly reinforced that impression when it emphasized the environmental advantages of a “future Tesla vehicle with a million mile battery.” But what does the million-mile battery revolution actually mean? According to experts in battery storage technology and the EV market, claims of new batteries that will last a million miles don’t tell us much on their own. How these batteries can be used is going to depend, first and foremost, on how they perform and degrade over their so-called “million-mile” life span. Several experts pointed out that true million-mile batteries are likely to outlast whatever cars they’re built for, meaning their arrival could dramatically impact both second-use markets and battery recycling. “What they’re talking about with million-mile batteries is not so much that an average consumer would put a million miles on the clock,” said Simon Lambert, a co-lead investigator at the Recycling of Lithium-Ion Batteries project at the UK’s Faraday Institution , “but that you’d potentially be able to use the battery multiple times, either in vehicular energy storage or grid-connected stuff.” Most EV batteries on the road today—nearly all of which are lithium-ion batteries employing one of several different chemistries—are warrantied to last 8 to 10 years or 100,000 miles. Some automakers guarantee that the battery will retain at least 70 percent of its original capacity over that period, meaning the car’s range—the distance it can drive before needing to be charged—won’t degrade by more than 30 percent. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg In practice, early data suggests today’s EV batteries often last considerably longer with less degradation, said James Frith, an energy storage analyst for BloombergNEF, a clean-energy research firm. Tesla’s recent impact report, Frith notes, claims that Model S and X batteries lose less than 20 percent of their original charge capacity after being driven 200,000 miles. A Nissan executive, meanwhile, recently estimated that a Nissan Leaf battery will last about 22 years based on battery degradation data the company is collecting on EVs sold in Europe, according to Automotive News. “We’re only just getting to the point where we’ve had EVs on the road for 10 years, and we can really see how well those claims of battery life last,” Frith said. “But in general, we see EVs do tend to perform quite well.” In many cases, EV batteries are already outlasting the cars they are being put in. Hans Eric Melin, the founder of Circular Energy Storage , a market research firm focused on second-use and recycling of lithium-ion batteries, says that it’s “very unusual” for a car to be pulled off the road today because its battery has degraded fully. While this is sometimes the case for heavily driven electric taxis or Ubers, more often the battery experienced some sort of electrical malfunction, other components of the EV became worn out, or the car was totaled in a crash. “For Tesla Uber drivers that might have driven 300,000 to 400,000 miles, they might have to replace the batteries,” Melin said. “But usually, the battery will outlive the car.” That’s not to say even longer-lived batteries are a bad idea. For one, they could offer a significant advantage for companies operating fleets of taxis or delivery vehicles, which often rack up considerably more miles per vehicle than the average consumer. Even for individual drivers, million-mile batteries could change the calculus around EV ownership. Frith said that many prospective buyers are still worried about how long the battery will last and how the car’s charge capacity and range will decline over time. Batteries warrantied to maintain a good state of health over a million miles—or even a more conservative half-million—would go a long way toward assuaging these concerns. Longer-lived batteries also could be a boon to the emerging used EV market: “If you have a battery that can last a million miles, you’re not going to be worried that after 50,000 to 100,000 the capacity will be too low to sell to a second market,” Frith said. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg What’s more, since batteries take considerable energy to produce, there’s a solid environmental argument for extending their life. In general, companies should be able to claim that million-mile batteries are more climate-friendly than their 200,000-mile counterparts because the carbon emissions, resource consumption, and pollution associated with their production will be spread over many more years of use. Still, there’s a lot we don’t know about the million-mile batteries companies are working on, including how their performance will decline over time, which has very practical ramifications for what actually driving a million miles on one would be like. All lithium-ion batteries inevitably deteriorate as a result of both cycling (being charged and discharged) and simple calendar aging. This degradation affects both the battery’s energy storage capacity (which dictates the car’s range) and its power capability, or how quickly the battery can discharge energy (and thus accelerate). “The rate at which each of those things comes down really affects the performance of the battery in terms of second life,” Lambert said. Lambert suspects that in practice, batteries with a million-mile rating might have to be cycled through a series of less demanding applications as they get on in years and miles. Perhaps a million-mile battery would spend its first 100,000 miles in a sports car before getting transplanted into an electric cab for the next 400,000, before eventually being repurposed for grid energy storage or backup power systems, less demanding applications. While there is already an emerging industry collecting and repurposing EV batteries—data shared by Melin shows there are more than 300 megawatt-hours of repurposed EV batteries being used for energy storage throughout Europe in 2020, compared with just 18 megawatt-hours in 2016—there is still a lot of room for this industry to grow. However, such reuse could have trade-offs, says Gavin Harper, a research fellow at the Faraday Institution. Various studies and reports have projected that rapid growth of the EV industry could lead to shortages of key battery metals , like cobalt, in the not-too-distant future. If that happens, it might be better to recycle cobalt-rich batteries sooner rather than delay recovery of this critical material. (While there is no global policy governing end-of-life recycling of EV batteries, the European Union and China are developing policies that hold producers responsible for this waste.) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg “I think the cobalt content of the battery will have a real bearing on its value in reuse relative to recycling,” Harper said. The EV industry’s shift toward battery chemistries with less cobalt, he says, means that each battery recycled today potentially could supply enough of the metal to furnish multiple future batteries. Even if we don’t face a raw materials supply crunch, radically extending the life span of EV batteries has implications for how we meet our rising metals demand in the future, notes Linda Gaines, the chief scientist of Argonne National Laboratory’s ReCell Center, which focuses on lithium-ion battery recycling. “It means you’re not going to get the material back for recycling for a really, really long time,” Gaines said. “Which means, until that happens, you’re reliant on virgin raw materials” that need to be mined from the earth. And while million-mile batteries might seem to suggest that we’ll need fewer batteries (and thus fewer raw materials) overall, Harper says it’s also possible they could increase battery demand, since “often, when we make improvements in efficiency, we just end up consuming more.” But this is one case where that may be a good thing for the planet. “If those batteries are displacing higher-carbon energy stores” like gasoline, Harper said, “this may just accelerate our transition to decarbonization.” How masks went from don’t-wear to must-have Poker and the psychology of uncertainty An infrastructure arms race is fueling the future of gaming How to get Safari's privacy features in Chrome and Firefox Everything you need to work from home like a pro 👁 The therapist is in— and it's a chatbot app. Plus: Get the latest AI news 🏃🏽‍♀️ Want the best tools to get healthy? Check out our Gear team’s picks for the best fitness trackers , running gear (including shoes and socks ), and best headphones Topics Climate Desk Electric Vehicles Batteries Energy environment Rob Reddick Ramin Skibba Grace Browne Matt Simon Rob Reddick Hannah Ritchie Matt Simon Matt Reynolds Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Dame Pom Review: An Approachable and Adorable Vibrator | WIRED"

"https://www.wired.com/review/dame-pom"

"Open Navigation Menu To revisit this article, visit My Profile, then View saved stories. Close Alert To revisit this article, select My Account, then View saved stories Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Jaina Grey Gear Review: Dame Pom Facebook X Email Save Story Photograph: Dame Facebook X Email Save Story $95 at Amazon $99 at Dame If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED Rating: 8/10 Open rating explainer Sex toys are often categorized by their shape and general function. Rabbit vibes are two-pronged vibrators with a little extra prong for clitoral stimulation. Magic wands are shaped like a big thick wand with a blunt vibrating end. Bullet vibes are small, compact little tubes shaped like—you guessed it—bullets. This vibrator, the Dame Pom, is shaped like a marshmallow Peep. It eludes simple categorization, and that’s why it’s one of our all-time favorites. Photograph: Dame The Pom’s shape plays a big role in its versatility and approachability. It’s super cute and has a little beak on one side, which is great for delivering targeted stimulation to a small area, whereas the body of the toy diffuses the vibrations over a larger area. The entire thing is made of a soft, squishy, pliable silicone, and pressing it against your body or an erogenous zone helps it conform to the contours of your hand and your body. It's this design that makes it transfer powerful vibrations to those deep subcutaneous nerves. I appreciate the thoughtful placement of the buttons too. There's one on each side toward the bottom, and they are very easy to locate without looking, thanks to their shape. The vertically depressed button is for cycling through five vibration patterns, and the horizontal depressed button is for intensity. The latter is technically two buttons to increase or decrease intensity levels (there are five choices). This design makes it really easy to adjust the experience to your liking on the fly. It’s impressively powerful for a toy of this size. At full intensity, you can put it down and watch it wiggle its way across the table. If you hold it up and look at it, you can see the vibrations blurring the edges of the toy. Putting it beside a similarly sized toy, there’s a visible difference in the power of its upper-limit vibrations. It's not all about the highest levels, though. The mark of a well-made vibrator motor is evident from the quality of its lower-end vibrations. On low settings, can you still feel it below the surface of your skin? With the Pom, you definitely can. It’s very gentle, but you can still stimulate your deep tissues. The penis and clitoris share a lot of anatomical structures, and quite a few of them are below the surface. The bulb and crus of both the clitoris and penis extend down along the vulva and the scrotum, respectively (think of a wishbone-shaped organ). It’s important to keep this in mind when shopping for a vibrator. The best ones stimulate the nerves at the surface of the skin and the nerves and structures well beneath. The Pom does this very well, and that’s impressive for its size. Most other vibrators I've tested in this shape tend to do a good job of stimulating surface nerves, and on higher intensities, you can feel the vibrations internally. With the Pom, you can feel that deep nerve stimulation even at lower intensities. It’s awesome. This toy has been sitting on my nightstand for more than a year. In that time, it’s seen extensive use and shows no signs of external wear and tear. The silicone hasn’t discolored or separated from the body of the toy. The buttons are every bit as responsive as the day I unboxed it. The motors are still quiet, still powerful, still going strong. Only the battery has started to show some signs of aging. Photograph: Dame Dame Pom Flexible Vibrator Rating: 8/10 $95 at Amazon $99 at Dame If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED The battery life on the Pom has always felt a little short. At the highest intensity, I can usually get about 40 to 50 minutes of use. I can push it to about an hour if I keep the intensity level low. When it was brand-new, though, I could reliably get an hour out of it at the highest intensity. It'd be nice if there was a way to replace the battery to breathe new life into it. The magnetic charging cable is also short. In my bedroom, the outlet isn't right next to my bedside table, so I had to do some creative cable management to get it to work. The star of the show here isn't so much Pom's longevity, but rather its shape and design sensibility. The most common toys are a motor or shaft wrapped in plastic with a thin layer of body-safe silicone. It’s a very technical way to design a sex toy: Minimize the distance between the genitals and the stimulation device (the vibrating motor), simplify the shape, make it as pared down as possible. One-size-fits-all. But this mindset doesn’t consider the human on the other end. There is no average body. There is no average genital or erogenous zone. Our bodies are weird, man. Every single one is strange and unique in its own beautiful way. That’s a lesson the US Air Force learned in the 1950s when it attempted to redesign the cockpits in fighter planes. The Air Force developed a set of measurements to define an average pilot’s overall shape and size. The one-size-fits-all approach. But once the data came in, the problem was obvious: The average pilot didn’t exist. Instead, the Air Force had to instruct manufacturers to design cockpits to be adjustable to the statistical edges, so individual pilots could comfortably fly despite their unique body shapes. Attempting to make products that appeal to an average means you’re sometimes making a product for nobody instead of everybody. Dame took the opposite approach with the Pom. The flexible, unique shape can fit any body, any genitals, and it has a powerful motor to deliver rumbly vibrations alongside targeted stimulation over a small area. It’s an impressive feat, and after testing dozens of sex toys, it’s still one of my absolute favorites. Just make sure you keep it on the charger. Dame Pom Flexible Vibrator Rating: 8/10 $95 at Amazon $99 at Dame If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED $95 at Amazon $99 at Dame Writer and Reviewer X Instagram Topics Shopping health sex household Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"You’re Probably Underestimating AI Chatbots | WIRED"

"https://www.wired.com/story/plaintext-youre-probably-underestimating-ai-chatbots"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Steven Levy Business You’re Probably Underestimating AI Chatbots Photograph: Hector Roqueta Rivero/Getty Images Save this story Save Save this story Save In the spring of 2007, I was one of four journalists anointed by Steve Jobs to review the iPhone. This was probably the most anticipated product in the history of tech. What would it be like? Was it a turning point for devices? Looking back at my review today, I am relieved to say it’s not an embarrassment: I recognized the device’s generational significance. But for all the praise I bestowed upon the iPhone, I failed to anticipate its mind-blowing secondary effects, such as the volcanic melding of hardware, operating system, and apps, or its hypnotic effect on our attention. (I did urge Apple to “encourage outside developers to create new uses” for the device.) Nor did I suggest we should expect the rise of services like Uber or TikTok or make any prediction that family dinners would turn into communal display-centric trances. Of course, my primary job was to help people decide whether to spend $500, which was super expensive for a phone back then, to buy the damn thing. But reading the review now, one might wonder why I spent time griping about AT&T’s network or the web browser’s inability to handle Flash content. That’s like quibbling over what sandals to wear just as a three-story tsunami is about to break. I am reminded of my failure of foresight when reading about the experiences people are having with recent AI apps, like large language model chatbots and AI image generators. Quite rightfully, people are obsessing about the impact of a sudden cavalcade of shockingly capable AI systems , though scientists often note that these seemingly rapid breakthroughs have been decades in the making. But as when I first pawed the iPhone in 2007, we risk failing to anticipate the potential trajectories of our AI-infused future by focusing too much on the current versions of products like Microsoft’s Bing chat, OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Bard. This fallacy can be clearly observed in what has become a new and popular media genre, best described as prompt-and-pronounce. The modus operandi is to attempt some task formerly limited to humans and then, often disregarding the caveats provided by the inventors, take it to an extreme. The great sports journalist Red Smith once said that writing a column is easy—you just open a vein and bleed. But would-be pundits now promote a bloodless version: You just open a browser and prompt. (Note: this newsletter was produced the old-fashioned way, by opening a vein.) Typically, prompt-and-pronounce columns involve sitting down with one of these way-early systems and seeing how well it replaces something previously limited to the realm of the human. In a typical example, a New York Times reporter used ChatGPT to answer all her work communications for an entire week. The Wall Street Journal ’s product reviewer decided to clone her voice (hey, we did that first !) and appearance using AI to see if her algorithmic doppelgängers could trick people into mistaking the fake for the real thing. There are dozens of similar examples. Generally, those who stage such stunts come to two conclusions: These models are amazing, but they fall miserably short of what humans do best. The emails fail to pick up workplace nuances. The clones have one foot dragging in the uncanny valley. Most damningly, these text generators make things up when asked for factual information, a phenomenon known as “hallucinations”' that is the current bane of AI. And it’s a plain fact that the output of today’s models often have a soulless quality. In one sense, it’s scary—will our future world be run by flawed “ mind children ,” as roboticist Hans Moravec calls our digital successors? But in another sense, the shortcomings are comforting. Sure, AIs can now perform a lot of low-level tasks and are unparalleled at suggesting plausible-looking Disneyland trips and gluten-free dinner party menus, but—the thinking goes—the bots will always need us to make corrections and jazz up the prose. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Yet it’s folly to draw definitive conclusions based on these early versions of the technology, including the shotgun blast of AI updates announced by Google this week. Folks, this is an illusion. Today’s chatbots are taking baby steps in a journey that will rise to Olympic-level strides. Oren Etzioni, former CEO of nonprofit research lab the Allen Institute for AI, told me this week that they’re already getting better. One force driving that trend is the millions of users—including reporters trying to goad the systems into doing nutty things that make good copy—exposing areas in need of improvement. Computer scientists, whose specialty is optimizing, after all, have been hard at work addressing the flaws. “Hallucinations have already dropped substantially,” Etzioni says. The next wave of evolution will come as scientists figure out how to level up the quality and capabilities of these algorithmic super brains. “I expect continued breathtaking innovation in the near future because it's just so early in the cycle of understanding and building these generative technologies,” he says. I guarantee you that 10 years from now tasking a large language model with business communications is going to be nothing like using today’s beta versions. The same goes for search, writing a college essay, or running a political ad campaign. Not to mention churning out a network sitcom—which is why, in part, screenwriters are now on strike. The Writers’ Guild understands that GPT-4 can’t crank out an acceptable version of Young Sheldon right now but GPT-19 might actually make that series funny. This doesn’t necessarily mean that humans are doomed. As with previous technological breakthroughs, the sweet spot might lie in collaborations that automate drudge work and leave the most nuanced forms of creation to humans. As the tech improves, our new era will be marked by a fuzzy borderline between copilot and autopilot. My guess is that over time, more and more activities will cross over to the autopilot side. It won’t be long before AI circa 2023 looks like television sets from the early 1950s. Or the iPhone before the app store, which launched a year after the device appeared. Before I get off the phone with Etzioni, I ask him to envision AI as a motion picture. In that movie, how far along in the narrative would we currently be? He thinks for a moment before answering, but when he responds, there is little doubt in his voice. “We have just watched the trailer,” he says. “The movie has not even started.” Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It’s almost exactly 15 years since I tested the iPhone. My June 2007 review appeared in Newsweek. I liked it! Apple is already working hard at improving this first version of the iPhone. I think the best way to make it more valuable would be to encourage outside developers to create new uses for it, and Apple has indicated that they are welcoming Web-based applications geared to their new device. But as the Google Maps program shows, the results of a separate client application created for the iPhone can be spectacular, and I think the company will do well to keep those coming … Bottom line: In a sense, the iPhone has already made its mark. Even those who never buy one will benefit from its advances, as competitors have already taken Apple's achievements as a wake-up call to improve their own products. But for all its virtues, the iPhone is still a risky venture because it's yet to be proven that, despite the wow factor, millions of people are ready to pay several hundred dollars more than the going rate for phones—and in some cases, paying even more to bail out of their current mobile contracts. There's also a potential backlash from those sick of the hype. During our iPhone conversation, however, Jobs professed that he wasn't concerned about inflated hopes, and certainly not whether he would meet his own projections of 10 million sold in 2008: "I think we're going to blow away the expectations." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Certainly all those people lining up to buy iPhones will find their investment worthwhile, if only for the delight they get from dazzling their friends. They will surely appreciate the iPhone's features and the way they are intertwined to present a unified experience. But in the future—when the iPhone has more applications and offers more performance, with a lower price—buyers will find even more value. So smart consumers may well wait for that day. But meanwhile they can only look with envy as the person sitting next to them on the subway, or standing ahead of them in the Whole Foods line, is enjoying the phone that finally fulfills the promise of people-friendly palm-top communication and computing. Chris asks, “Why aren't media outlets and AI critics doing more to point out the terrible environmental cost in creating large language models and AI in general?” Hi, Chris. There’s no question that the new breed of AI models require a lot of computation, which means huge energy consumption. And though there has been reporting on the subject, you’re right that most articles concentrate on the technology, not the environmental impact. Maybe that’s because compared to mining Bitcoin and flying airplanes, the energy consumed by LLMs isn’t overwhelming. One study calculated that the energy Google consumed by training those models in 2019, for instance, was less than .005 percent of its total consumption—training a single model used the equivalent of providing electricity to about 100 homes. Another study figured that training one big LLM model churned out 626,155 pounds of CO 2 emissions—which is roughly equal to what five automobiles would produce in their lifetime. Running an LLM after it has been trained uses much less energy, though of course when millions are making queries the servers get a workout. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg When you calculate the total amount of energy consumed by AI, the numbers get bigger, and they will grow even more as we routinely use those power-hungry applications. Currently, an estimated 15 percent of Google’s data center energy comes from AI activities. That’s enough to power the city of Atlanta for a year. Mitigating this somewhat is the fact that big companies like Google and Microsoft try very hard to keep energy consumption in their data centers to a minimum. Google aims to make all its facilities and data centers carbon neutral by 2030. But there’s no way around it—ChatGPT, Bard, and Bing collectively draw tons of electricity as they chat with their millions of users. Nonetheless, I do think the ultimate measure of AI will come from its impact on the way we work, learn, and entertain ourselves. You can submit questions to [email protected]. Write ASK LEVY in the subject line. Texas wants to kill its booming clean energy business. Hopefully, not with AR-15s. One rosy view of the generative AI future: Hobbled by their creators to prevent hallucinations, the bots might get boring. Here’s everything Google announced at its i/o conference. Not surprisingly, lots of AI. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Is reality TV the new Prozac? Well, it saved this WIRED writer. Scooping plastic out of the ocean sounds like a good idea. Some marine life may beg to differ. You Might Also Like … 📧 Find the best bargains on quality gear with our Deals newsletter “ Someone is using photos of me to talk to men” First-gen social media users have nowhere to go The truth behind the biggest (and dumbest) battery myths We asked a Savile Row tailor to test all the “best” T-shirts you see in social media ads My kid wants to be an influencer. Is that bad? 🌞 See if you take a shine to our picks for the best sunglasses and sun protection Editor at Large X Topics Plaintext artificial intelligence Google io machine learning robotics future Will Knight Reece Rogers Paresh Dave Steven Levy Will Knight Will Knight Will Knight Will Knight Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Ultrahuman Ring Air Review: A Subscription-Free Smart Ring | WIRED"

"https://www.wired.com/review/ultrahuman-ring-air"

"Open Navigation Menu To revisit this article, visit My Profile, then View saved stories. Close Alert To revisit this article, select My Account, then View saved stories Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Simon Hill Gear Review: Ultrahuman Ring Air Facebook X Email Save Story Photograph: Ultrahuman Facebook X Email Save Story $349 at Amazon $349 at Walmart $349 at Ultrahuman £329 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED Rating: 7/10 Open rating explainer Once the preserve of biohacking billionaires, celebrities, and athletes, smart rings have grown enormously in popularity since the Oura ring first launched in 2015. The ability to track your health through an unobtrusive piece of jewelry still feels like a miniaturization miracle. Now there's another smart ring to take note of in this nascent category: the Ultrahuman Ring Air. Clearly positioned as a competitor for the third-generation Oura , the Ultrahuman Ring Air is technically very similar. It can track your sleep, recovery, and movement to offer insights and tips via an app on your smartphone. It is also similarly priced at $349, but that price includes a “lifetime subscription” to access your data and insights, whereas Oura charges $6 per month. I've worn the Ultrahuman Ring Air for a couple of months, and it is a delightfully easy way to track your health and sleep, but it’s not so great for fitness, and I encountered a few flaws. Photograph: Ultrahuman I used a sizing kit, wearing a dummy ring for 24 hours to find the ideal fit, which turned out to be size 11. (Size 10.5 would have been better, but Ultrahuman doesn't do half sizes.) Ultrahuman has an electronic sizing kit you can use that involves using your phone's camera, but you can have the company ship you a Ring Air Sizing Kit for free. I chose to wear the titanium ring on my left index finger—the only rule is you can't wear it on thumbs and pinkies. If I could choose again, I'd go with my middle or ring finger because I quickly discovered that the ring gets scuffed easily, and on your index finger, it has more contact with everything you pick up. I tested the matte black version, but Ultrahuman has since released other finishes (shiny black, gold, or silver), which may not scuff as easily. The Ultrahuman Ring Air solves two problems I typically have with sleep and fitness trackers. First, it’s comfortable enough to wear all the time, even to bed for sleep tracking. I find smartwatches and most fitness trackers uncomfortable and prefer to take them off at night. Second, the Ring Air offers insights into your data and nudges you toward healthier habits. Some fitness trackers give you a data dump but lack practical advice and insights. Photograph: Ultrahuman Ultrahuman Ring Air Rating: 7/10 $349 at Amazon $349 at Walmart $349 at Ultrahuman £329 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED Design-wise, the Ring Air is chunky and masculine (it's around 2.5 millimeters thick). It is noticeable enough that a few people asked me about it, but I’m not much of a jewelry wearer. The sensors are packed around the inside, but it’s smooth and comfortable. Smaller sizes only weigh 2.4 grams, but my ring is a little heavier at around 3 grams. I occasionally see the green light of the heart rate sensor if it’s dark, but it's easily the subtlest wearable I've worn. There's an infrared photoplethysmography (PPG) sensor, a noncontact medical-grade skin temperature sensor, a six-axis motion sensor, and colored LEDs for heart rate monitoring and blood oxygen saturation. It’s fine to wear in the shower or pool thanks to the IPX8 water resistance rating. You can review your data in the Ultrahuman app on your phone ( Android , iOS ). The ring connects via Bluetooth 5 Low Energy (LE), taking a few seconds to sync every time you open it. Ultrahuman crunches your data to offer three scores: Your movement index, sleep index, and a recovery score. The first two are for fitness and sleep, respectively, and they inform the recovery score, which indicates how hard you should push yourself that day. It's not unlike Fitbit's Daily Readiness score or Garmin's Body Battery. Photograph: Ultrahuman For movement, the Ring Air counts your steps, logs exercise, and estimates your cardiovascular fitness and blood oxygen levels (sadly, these last two are not available in the Android app yet). I like that it focuses on movement throughout the day and nudges you to stir when you have been sedentary for too long. Regular movement is prized over one big workout if you're sitting at your desk for hours. Unfortunately, the workout tracking, which is still in beta, is flaky. You have to trigger it manually, and the activity options are limited. The Ultrahuman app shows heart rate zones and calories burned at the end of the workout. Twice, I started tracking workouts, only to have the data disappear. The Ring Air also consistently fails to record my heart rate accurately. I can hit 150 beats per minute on the Apple Watch, but the Ring Air often says I’m still at 80 bpm or less. Since it is a work in progress, I'm keeping my fingers crossed it improves. My heart rate outside of workouts appears to be accurate and matches other trackers. Where the Ultrahuman Ring Air has been strongest is sleep tracking. I recently wrote a sleep tracker guide , comparing data across devices, and the Ring Air came closest to an accurate reflection of my slumber. It breaks out the stages (awake, REM, light, and deep), shows your heart rate variability (HRV), and tracks skin temperature. You can also log how you feel (tired, ready for action, or somewhere in between). Ultrahuman Ring Air Rating: 7/10 $349 at Amazon $349 at Walmart $349 at Ultrahuman £329 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED The Ring Air makes suggestions based on your circadian rhythm and the time of day. Get sunlight in the morning, delay stimulants until adenosine has cleared, and remember to stop drinking coffee toward the end of the day. It also uses heart rate drop as an indicator of recovery (if your heart rate drops earlier in the night, you recover better) and suggests reasons why it may not have fallen as quickly, such as meals too close to bedtime or alcohol. This is all commonsense stuff, and there’s a fair bit of unnecessary jargon when simpler language would suffice, but it helps to get nudges throughout the day. The app can feel complex at first, but dig into any of the elements being tracked or extrapolated, and you will find an explanation of why this metric is important and what it tells you. The color coding helps, with green indicating that a measurement is within your target range and red highlighting potential problems. Ultrahuman also compiles a weekly report showing trends to highlight where you have improved and what needs further improvement. Stat junkies will love this, but it might be overwhelming if you prefer a simple overview. There is also a tab with meditations, workouts, and sleep stories. There’s a fair bit of content in there, and the production values are good. Sadly, one tab in the app is just an advert for Ultrahuman’s M1 glucose monitoring patch. The app has had multiple updates since I started testing, so it is improving. But I think the event logging is clunky. As well as recording workouts, you can log activities or sleep after the fact, log what you eat, and input your weight. There’s an “Other” category for anything else you want to record. But the app could do a better job of integrating all of this data. Most fitness trackers allow you to set goals or adjust them based on your lifestyle, but this option is missing from the Ultrahuman Ring Air. It can be a little dispiriting to keep missing goals, and Ultrahuman’s insistence that I get 11,000 steps in every day is unrealistic for me, so I hope they allow some tweaking in the future. Photograph: Ultrahuman Overall, I am a fan of the Ultrahuman Ring Air. It's lovely to have such an elegant device tracking my health. I find the reminders genuinely useful. The Ultrahuman team also seems to be adding functionality at a steady pace. When I had a problem, the in-app support person was swift and helpful. (I switched from an Android phone to my iPhone, but it refused to sync. I had to delete the app and reinstall it to get it working.) Battery life is solid. Ultrahuman suggests up to six days, but four days is more realistic. The app nags you to charge when the battery hits around 20 percent. A wee charging pedestal and USB-C cable come in the box, but you’ll need your own power adapter. The Ring Air takes more than two hours to fully charge, which is enough time to forget about it, and I missed a couple of nights of data because of this. The obvious alternative is the Oura. It offers a more polished and accessible experience, plus workout tracking that's far more usable, but Oura has a sizable head start on Ultrahuman, and the fact you don’t need a subscription for the Ring Air is a big plus. It takes a few weeks to get valuable insights, but with enough data, trends emerge to help you identify potential reasons for poor sleep or how ready you are for a workout. I can’t say I feel like an ultrahuman yet, but the Ring Air is nudging me in the right direction. Ultrahuman Ring Air Rating: 7/10 $349 at Amazon $349 at Walmart $349 at Ultrahuman £329 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED $349 at Amazon $349 at Walmart $349 at Ultrahuman Contributor X Topics Fitness Trackers health review Reviews Sleep fitness Wearables Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. 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"The Video Games WIRED Loved Most in 2020 | WIRED"

"https://www.wired.com/story/video-games-wired-loved-most-2020"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons WIRED Staff Culture The Video Games WIRED Loved Most in 2020 Save this story Save Save this story Save In any normal year, a list of the 10 best recently released video games would adequately encompass that year in games. Not in 2020. The best way to describe the way we consumed games in 2020 was as “comfort food.” Sticking the same pack of over-buttered popcorn in the microwave every day after work just to feel something. Ordering a 4-pound bag of childhood-favorite shoestring licorice on Amazon and slurping it down within a week. There were lots of new games we adored—the stylish and sexy action indie Hades , for one, is WIRED’s unofficial game of the year. But for the most part, we were looking for more than novelty from our time gaming. We want to party in digital mansions swarming with catgirls. We want to channel our anxiety into managing spaceships. We want to flirt with the natural world. We want to dissociate on the couch with a free-to-play mobile game. Below are the games that we loved most in 2020. —Cecilia D'Anastasio Courtesy of Supergiant Games I was a little late to the Hades appreciation train, but after buying it in November, I just can’t stop playing. This has been a difficult year mentally and emotionally, and Hades takes you away from all of that into a fantasy hellscape with killer music. Seriously, the music is just that good. With the pandemic in full swing this holiday season, who wouldn’t identify with the protagonist Zagreus at least a little? We, too, want to escape the hell that is our reality and find Olympus (and our relatives and friends that are so close and yet so far). Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The best part about Hades , really, is that you can do a quick 20-minute or so run-through, diving in and out of the world as a release before moving on to something else, such as your new hobbies of baking bread and knitting. Beat up some bad guys, build some fun abilities bestowed upon you from the gods, listen to some great voice lines and banter, and get to explore Hell—what more could you want from an action role-playing game? Also, did I mention the music? — Saira Mueller Courtesy of BugByte Playing Space Haven is an exercise in being compulsively hyper-detail-oriented. Think Stardew Valley meets SpaceX. For instance, I have to make sure there’s enough oxygen for my fleet’s crews. That itself requires that they have enough water, which means I have to make sure they’re discovering pockets of space with mineable ice. And I had built facilities required for the two-step process of converting that ice to water, and then to oxygen. All the while not forgetting that I need to budget some of that water to grow food because, well, my astronauts need to eat. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Looking after my pixelated spacefarers requires dictating their work/sleep/leisure schedules, micromanaging their task priorities, building out their space, and keeping them safe on scouting expeditions. In a year when planning anything similar to those things in my own life often felt like a struggle, Space Haven’s minutiae-mechanics managed to afford my brain the same good chemicals that daily life offered under normal times, when there wasn’t a pandemic to worry about. —Phuc Pham Courtesy of Bungie OK, look, I’m just going to admit that Destiny 2 is my forever game. At least for now. It took the crown from Overwatch , when I realized I was spending more time raging than enjoying myself (not that I won’t pick it right back up whenever we get Overwatch 2 ), and the only game that’s challenged Destiny 2 for supremacy in the past year or so has been Genshin Impact. I’m saying this for myself. Consider it catharsis. The latest expansion, Beyond Light , advances the story in interesting and tangible ways, and while a lot of the game’s recent changes have been controversial, it’s the kind of controversy that breathes life into a game that could otherwise be a boring “log in, do game chores, log out” experience. It was easily one of my most anticipated releases of 2020, and for me, at least, it’s been rewarding enough that it’s kept me from opening any of the other games I’ve purchased lately—and yes, that includes Hades and Cyberpunk 2077 and other titles you’ll see on this list. So yeah, catch me on Europa if you need me, and if you have a Destiny 2 clan that’s chill and raids sometimes, please let me know. Please. I’m begging you. —Alan Henry Courtesy of Riot Games For better or for worse, I’m inexplicably obsessed with the League of Legends universe. I’ve had flings with nearly every title in Riot Games’ roster, but Teamfight Tactics has been the stickiest. When it comes to gaming, I prefer low pressure —I’d rather build a house or hoard loot than face a Big Bad—and TFT has some of the lowest stakes of all. I’ve taken a chance on plenty of new games this year. None of them stuck long-term until I tried this one. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The allure of the auto-battler is that everyone starts on an equal footing. You pray to RNGesus and hope that your next reroll or random event gives you the pieces of the puzzle that you need. TFT has a hardcore ranked community, but every Grandmaster starts each round with the same amount of luck as me (a lowly rank Gold I). The meta evolves swiftly, the cosmetic rewards are adorable, and there’s no pay-to-win structure. Each game takes around half an hour, making TFT the perfect lunch break distraction, and the community is surprisingly nontoxic. I especially appreciate TFT because it’s both easy to learn and completely free. There’s no daunting learning curve (like Civilization ) or misogynistic trolling (like Overwatch ). Just endearing characters, tasty loot orbs, and the constant temptation to tilt. —Louryn Strampe Courtesy of Square Enix Final Fantasy XIV has been the only safe place for me to party. In the massively multiplayer online role-playing game, players have channeled their frustrated social energies into raves, bar romps, live theater, and even orchestrated musical concerts. (Seriously—I heard a Moogle rendition of Nina Simone’s “Feeling Good” that low-key ripped.) One friend can pick me up in their black convertible, drive me through a crystalline wasteland, and drop me off with another friend who’s pummeling worms. I can join a 60-person Bob Ross–themed parade around town. It’s a great time. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Earlier this year, I convinced a surprising number of IRL friends to give the game a whirl with its fantastic free trial. The story content isn’t the main draw for us; it’s kind of a slog. FFXIV ’s greatest value is as a place for us to be ourselves, together, plus or minus a couple monsters. —Cecilia D'Anastasio Courtesy of Moon Studios Ori and the Blind Forest set a high bar for side-scrolling platformers in 2015. But because of the way the narrative played out—the ultimate goal is to restore life to a dead forest—there were few friendly faces to be found throughout most of the game. It’s a lavishly crafted, yet ultimately lonely experience. Enter 2020’s Will of the Wisps. The sequel’s ambitions are grander than its predecessor, and therefore somewhat messier. At first, the addition of so many new characters and their side quests almost feels intrusive—an overcomplication of an already perfected formula. The last thing I wanted from a game as polished as Ori was a series of boxes to check. But I quickly came to love the various adorable woodland critters who guide you along your way (and ask you to find the occasional hat). Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The characters in Will of the Wisps make the game’s gorgeous world feel alive and vibrant. The brilliantly bioluminescent landscape isn’t just pretty to look at, it feels suffused with history and personality. Of course, Ori’s world has problems of its own. There are great marauding monsters, fallen friends, and environmental devastation that will surely feel familiar to anyone who’s paid any attention to climate news in the past few months. But guiding Ori through these challenges is cathartic, and it’s deeply soothing when you emerge into an even more beautiful ecosystem that you helped create. At their core, these games are about leaving your campsite better than you found it. After a year of sickness, destruction, and chaos, Ori makes you feel like it’s still possible to spread light in a dark world. —Boone Ashworth Courtesy of Bandai Namco The only game I've ever finished is the original Katamari Damacy. I bought it for my PlayStation 2 about a decade and a half ago, and although it took about nine months to play through it, I actually reached the end and watched the credits scroll—something I've never seen in any other game. I'm just not very adept with the controls of most games, so I get frustrated and quit. There are some games where I can keep up, but I get bored quickly and just want to move on. That didn't happen with Katamari. I kept going until I snagged the final rainbow. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Fast forward a million years, and here I am holding a Nintendo Switch filled with Mario titles, an adventure game or two, and that silly Goose game that was last year's must-have. I don't want to play any of these, so I do a quick search and see that Katamari Damacy Reroll is in the Switch store. Not a sequel or a spin-off, but a faithful recreation of the original. Sweet baby Prince! Downloading! Soon, I'm charging around a cluttered suburban Japanese home, scooping up onigiri and pencil erasers, running away from giant mice. Of course, the similarities between the onscreen cluttered apartment and my own real-world cluttered apartment, which I've barely left since daylight saving time ended, are starker this year than most. Come to think of it, I should really put the Switch down and do some tidying up. Eh, one more roll? Then I'll take a break. —Michael Calore Courtesy of Playrix “Love” is maybe not the right word for my relationship to Homescapes. “Played” might not be the right word, either, to be honest. Homescapes is one of those ubiquitous match-three mobile games that requires no money, no thought, no strategy, no feelings. In other words, it was perfect for 2020. It offered just enough stimulation to keep my mind from fixating on the day’s grim headlines, and if I’m playing Homescapes , I am physically unable to keep doomscrolling. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg It’s almost not worth going into the conceit of the game, such as it is: You start to help a butler named Austin renovate his parents’ house by matching tiles and beating levels. The game, part of developer Playrix’s successful ’Scapes universe, has its critics. I won’t deny they make plenty of good points. But I am perversely amused by how Homescapes stretches out to fill seemingly endless space and time. Play it enough—and reader, trust me, I have—and you will begin to unlock areas that veer into the absurd. Austin’s childhood home turns out to have its own greenhouse, a boathouse, a dance hall, and a yacht. It seems like a suspicious amount of square footage for an older butler and a homemaker to acquire. And since we finished decorating his parents’ house, Austin has found a country estate of his own, whose amenities include a chocolate factory, a café, a throne room, and a marine biology lab. It all makes about as much sense as anything else this year. So I don’t think about it too much, and swipe on. —Caitlin Kelly Courtesy of Sega Yakuza: Like a Dragon feels like a PlayStation 2 game, and I mean that in the nicest way possible. In our next-next-gen age of multimillion-dollar marketing schemes, microtransactions, and “live service” demands for always-on connectivity, a game with straightforward combat mechanics, a relatively small map, and a plethora of tangential minigames could feel quaint. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Instead, Like a Dragon is bursting at the seams. It's genius. It’s absurd. It’s GTA meets Dragon Quest meets Crazy Taxi. The premise is sharp: A fresh-out-of-jail ex-yakuza thinks of the world as an RPG because he never learned adult coping skills. From there, Like a Dragon takes a pulpy crime tale and infuses it with psychedelic parodies of old-school Dragon Quest and Final Fantasy games. Party members’ jobs, usually something like knight or warlock, are literally blue-collar jobs: the foreman of a construction company who wields an enormous war hammer and can summon a parade of workers to stampede the enemy. A bartender can use an ice bucket to freeze enemies, while a riot police officer can use their shield to tank. Summons only up the ante. I can call a chicken to lay an MP-restoring egg or a biker to burn rubber over my enemies faces. I can call an adult man with a diaper fetish, his hideous cries reduce my enemies’ attack and defense. From there , I can call in an orbital strike from a satellite because Ichiban, in addition to being a himbo, also owns a billion-dollar dessert conglomerate. But the wildest surprise was the sharply political moments of earnest reality in the side quests. Here, the game replaces zany humor with earnest discussions of homelessness, anti-immigrant sentiment in Japan, and the demonization of sex workers. The “job” function doesn’t even unlock until Ichiban & Co. solve a series of patronizing fetch quests from a shady temp agency. Maybe I’m just getting old, but I’m less interested in games that ignore reality and am more into games that warp and refract it, highlighting the strangeness and unfairness of the world we live in. I certainly wasn’t expecting that from a game where the protagonist dresses like a member of the Bee Gees. —Sidney Fussell Courtesy of Playdots I know we are all looking for an escape from our 2020 nightmare. This is exactly what Two Dots has been for me. The game on my iPhone has been my respite from anxiety. It is completely mindless and pairs perfectly with ambient TV or a fun podcast that is not at all news-related. Connecting colorful dots and working through puzzles that include ladybugs and fruit-eating monkeys while vaguely absorbing the plot of my latest Netflix binge leaves absolutely no room in my brain for anything else. This game would probably be an excellent friend on an airplane, as well. I’ll let you know if I ever do any traveling again. —Elena Lacey 📩 Want the latest on tech, science, and more? Sign up for our newsletters ! 2020 was the year of canceled culture Curl up with some of our favorite longreads from this year The future of social media is all talk 2020 shows the danger of a decapitated cyber regime The best indie games you may have missed this year Read all of our Year in Review stories here Topics Year in Review video games Matt Kamen Boone Ashworth Megan Farokhmanesh Eric Ravenscraft Matt Kamen Megan Farokhmanesh Reece Rogers Reece Rogers Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"How to Transfer Save Data From One Nintendo Switch to Another | WIRED"

"https://www.wired.com/story/how-to-transfer-nintendo-switch-save-data"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Eric Ravenscraft Gear How to Transfer Save Data From One Nintendo Switch to Another Photograph: Getty Images Save this story Save Save this story Save Your Nintendo Switch is loaded up with precious game save data, not to mention your prized screenshots and gripping gameplay recordings. You don’t need to upgrade to the new Switch OLED , but if you are—or you just need to swap from one console to another—you’ll need to transfer all of this data over. There are a couple of ways to do it. Transferring save game data and your screengrabs involve different processes, and for the latter, you’ll need a separate MicroSD card. Things are also very different (in a good way) if you pay for Nintendo Switch Online. Here, we break down all the details so you can follow the process that best applies to you. Here's how to transfer your Switch data. Your most precious data—all the save data and progress you’ve made in your games—is tied to the user profile you created when you first set up your Switch. It's the profile you pick each time you start a game, with a name and an avatar. All of that associated data is stored on your Switch and needs to be copied over to your new console. There are two ways to do this, and one of them costs money. If you subscribe to Nintendo Switch Online , then this process is (much) easier. Photograph: Eric Ravenscraft When you first sign up for Nintendo Switch Online , your games will automatically be set to back up data to the cloud. However, you can individually control which games get backed up, and you can manually back up data by heading to Settings > Data Management > Save Data Cloud. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So On your new Switch, log in to your Nintendo account. You can either do this during the normal setup process when you first get your Switch or by selecting an existing profile from the home page and selecting “Link Nintendo Account.” When you do, you'll be able to manually download save data for each game by heading to the aforementioned settings page. To redownload your games, head to the Nintendo eShop, tap on your profile picture on the top right, and go to Redownload. You can keep playing games on both Switches if you plan to keep both. Just make sure you toggle on Automatic Save-Data Download in Settings > Data Management > Save Data Cloud > Settings. This makes sure that the save file is always updated to the newest data no matter which Switch is being used, meaning you can pick up where you left off on any of your consoles. If another person in the household wants to play a game you own on the older console, the Switch will need to be connected to the same Wi-Fi network, and you'll need to deregister it as the primary console after you transfer, which we get to further below. It's worth noting that Animal Crossing: New Horizons has a special process for transferring your island from one Switch to a new system. You can read the instructions here. Also, developers can choose to disable syncing cloud game saves, so some games like Splatoon 2 and Pokémon Sword and Shield won't transfer over. If that happens, you can transfer them manually with the steps below. Photograph: Eric Ravenscraft If you don't have a Nintendo Switch Online and don't want to get it, you can still transfer data over, but it's a little more annoying. You’ll need both Switch devices handy, as well as an internet connection and a Nintendo account. Make sure the profile you want to transfer is signed into your Nintendo account on the Switch you’re transferring data from. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Important note: Don’t sign in to your Nintendo account on the console you want to transfer data to. If you link your Nintendo account to a profile on the new Switch, this process won’t be able to merge them, so wait until you’re instructed to sign in. Once everything is ready, you can follow these steps on both the source Switch you’re transferring data from, and on the target Switch you’re transferring data to: Go to System Settings from the home screen. Select Users from the left-hand menu. Select Transfer Your User and Save Data. Click Next. At this point, the process for each console will diverge. On the old Switch, choose Source console , and click Continue. On the new Switch, choose Target console. You’ll then be able to sign into the Nintendo account that’s associated with the profile you want to transfer. Once you’re signed in on the target console, click Continue on the source console. The process will take a few minutes to copy data from one device to another, depending on how much data you have to transfer. Unfortunately, after this point, your data won’t be available on the source console anymore. You can’t have data on both consoles at the same time—unless you pay for Nintendo Switch Online—so make sure you’re ready to move before you commit. You can have multiple profiles on a single Switch, and not every profile has to be associated with a Nintendo account. However, if you do have multiple Nintendo accounts on a single Switch, you’ll need to repeat this process for each of them if you want to move them over to a new console. And just like before, this process doesn't actually transfer your games. You'll still need to go to the eShop and manually redownload each title by clicking on your profile and heading to the Redownload tab. Once you've transferred your games and save data over, you might want to deregister your original Switch as the primary console for your account. Each account can only have one primary console, which gets special privileges that other consoles on your account don't. The primary console can play the games you've purchased while offline, and other people's profiles on that Switch can play the games you've bought. A single Switch can be the primary console for as many accounts as you want, but each account can only set one Switch as its primary. On a Switch that isn't the primary console for an account, you can log into your account on one profile and still play games you've purchased, but only if you maintain a connection to the internet. Other profiles on that Switch can't play those games unless the owner has purchased it themself. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So If you need to change which Switch is your primary console, follow these steps: On the Switch you plan to deregister, launch the eShop from the home screen. Select your profile icon in the top-right corner of the screen. On the right side of the screen, scroll down to the Primary Console section. Select Deregister. After you do this, the next Switch you open the eShop on will become your new primary console. You can change this as often as you need to, but only one console can be the primary at a time. The above processes transfer your data, but they leave all your screenshots and recordings behind. These aren’t quite as critical, and you can leave them where they are, but if you want to bring them over to your new Switch, you’ll need a MicroSD card. You might already have one in your Switch, since the original console only had a meager 32 GB of storage space. Once you have a MicroSD card in your console, follow these steps: Go to System Settings from the home screen. Select Data Management. Select Manage Save Data/Screenshots and Videos. Select Manage Screenshots and Videos. From this screen, you can choose to transfer all of your screenshots and videos to your MicroSD card. Once they’re copied over, you can remove the SD card from your old Switch and insert it into the new one. However, you might want to take the opportunity to plug the card into a computer and backup or transfer the files somewhere you can store them safely over the long term. All your important data should now be transferred from your old console. If you’re planning to give away or sell your old Switch, you might want to reformat the console to delete all data and settings from it first. Special offer for Gear readers: Get a 1-Year Subscription to WIRED for $5 ($25 off). This includes unlimited access to WIRED.com and our print magazine (if you'd like). Subscriptions help fund the work we do every day. 📩 The latest on tech, science, and more: Get our newsletters ! 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Check out our Gear team’s picks for the best fitness trackers , running gear (including shoes and socks ), and best headphones Product Writer and Reviewer X Topics Nintendo how-to tips consoles video games gaming tips Jaina Grey Simon Hill Eric Ravenscraft Reece Rogers Simon Hill Julian Chokkattu Brenda Stolyar Adrienne So WIRED COUPONS TurboTax Service Code TurboTax coupon: Up to an extra $15 off all tax services h&r block coupon H&R Block tax software: Save 20% - no coupon needed Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Doordash Promo Code 50% Off DoorDash Promo Code + Free Delivery Finish Line Coupon Take $10 off Your Order - Finish Line Coupon Code Groupon Promo Code Groupon promo code: Extra 30% off any amount Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Nintendo Labo Review: Which Kit is Best? (Vehicle, Variety, Robot Kits) | WIRED"

"https://www.wired.com/review/review-nintendo-labo-variety-and-robot-kits"

"Open Navigation Menu To revisit this article, visit My Profile, then View saved stories. Close Alert To revisit this article, select My Account, then View saved stories Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Jeffrey Van Camp Gear Review: Nintendo Labo (Vehicle, Variety, and Robot Kits) Facebook X Email Save Story Nintendo Facebook X Email Save Story $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED Rating: 9/10 Open rating explainer I was a rambunctious, energetic child. It was hard for me to sit still for anything, but if you gave me a box of Lego and a good set of instructions, I could sit for hours. I had Lincoln Logs, Tinker Toys, K’Nex, model cars, you name it. There’s a wonderful zen to quietly assembling something. But then, what do you do after you're done? The true test of a building toy is whether you find creative ways to play with it once it’s finished. Toys like K’Nex could always be repurposed for games or rebuilt in perpetuity. Models and electronic Technozoids (yes, they were a real thing on the other hand tended to end up in the closet or on a garage sale table sooner rather than later. As crazy as my little building projects got, nothing from my childhood was as ludicrously weird and inventive as the new Nintendo Labo. Nintendo’s latest nutty idea is a trio of Switch games that each come with more than two dozen sheets of corrugated cardboard. To play the included games, you must first spend at least an hour snapping and folding together what Nintendo calls Toy-Cons: cardboard controllers. One kit comes with smaller Toy-Cons you can use on a table, like a piano and fishing rod, another lets you create steering wheels to control three types of vehicles, and the last lets you spend hours making a wearable robot backpack and suit. All the step-by-step instructions are on your Switch, and when you finish a Toy-Con, a mini game is unlocked. You slide the Switch touchscreen into its designated slot in the cardboard, then slip in the Switch’s two motion control Joy-Con controllers into, say, the handle of the fishing rod you just assembled, and off you go. Before you know it you’re reeling in digital fish. I’ve built some forts out of cardboard and opened my share of boxes, but I never realized how serenely thrilling corrugated cardboard is as a material. I found myself in a state of pure calm freeing the cardboard cut-outs and punching out the little holes and chads as I went (I leave no hanging chads). Much of the fun comes from the quirky way each cardboard Toy-Con is designed. No build is predictable and it’s fun to figure out precisely how the odd mess of cardboard will ever come together, but it always does so in surprising, brilliant ways. After a few days with Labo, I feel like I’ve already learned a bit about construction and how to fortify a cardboard creation. I can only imagine what a creative kid who normally plays Minecraft might dream up after getting a taste for Toy-Cons. Nintendo Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED The on-screen instruction manual for each Toy-Con also adds to the fun. The sometimes snarky, often amusing instructions, feel like a part of the experience, not just a prerequisite before the real game starts. I don’t remember Lego instructions ever telling me to choose “whichever [shortstrap] speaks to you in your soul,” encouraging me to take breaks after finishing sections, or making up rhymes like “Dum diddly dum dade! Not long ‘til the arms are made!” to keep me engaged. Each set of instructions walks you through every fold and snap, complete with sound effects for every touchscreen tap. Each step clearly lays out which pieces you’ll need to snap out of which cardboard sheet and 3D models let you zoom in or move the camera with the Switch touchscreen. Most of the projects tend to take at least a half hour, and some last as long as 4 hours. The only thing that occasionally broke my zen was the Nintendo Switch itself. The most comfortable way for me to get to work was with the Switch on my dining room table, propped up with its kickstand. Unfortunately, the Switch is wobbly and fell down more than a few times, and ran out of battery in the middle of long projects. Hopefully Nintendo will make a Switch with more than 3-5 hours of battery life someday. Which Labo Should You Buy? There are three Nintendo Labo kits, and they each include multiple cardboard Toy-Cons to build, games to play with them, and a Discover section, where a group of kooky characters with suspiciously appropriate names like “Professor Gerry Rigg” and “Lerna Lotte” will teach you tons of tips and tricks, and unlock extra modes, customizations, and doo-dads in the games. All of three kits are fun, but they’re made for different kinds of players. Nintendo Photograph: Nintendo The Vehicle Kit ($70) is the newest Labo Toy-Con, and my favorite (probably yours, too). It's just hitting shelves in September, about five months after the Variety and Robot Kits debuted. This kit is all about steering and piloting, and has a pretty deep and wacky exploration game attached to it. You can build a spray can, gas pedal, an airplane joystick, a double-handed submarine steering box, and an extremely robust steering wheel. The steering wheel looks polygonal, like it's from an old Nintendo 64 game, but it's packed with features, including a jet boost cord you can yank, a horn, a lever for reverse, and two twistable, flickable stalks for other functions, like window wipers and shifting gears. With the gas pedal, it sometimes felt like I was using a full racing wheel for driving simulators. Granted, it always felt like a racing wheel made of cardboard, but the control is impressive nonetheless. It will take 5-10 hours to build the five kits, and they're a lot of fun to put together, like the Variety Kit. Unlike the Variety Kit and Robot kits, the gameplay they unlock is actually more fun than the build. The Vehicle Kit also has an adventure mode where you can freely drive or fly around an open world with 10 zones to explore, each with at least eight small little challenges in them, like finding the gas station in each zone, herding plastic toy cows, or shooting balloons out of the sky. I've already spent a few hours driving, flying, and subbing around the island, and there's a lot I haven't completed. The submarine is my least favorite, but I'm sure other players will love it. Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED Nintendo Even if you're not into the challenges, it's still a delight to use the motion control to fly and drive. Even non-gamers will enjoy trying it out. It shows the potential of Labo kits to bring new types of control to life. It's also easy to swap between control types, taking the air or water in seconds, with a Joy-Con "key" that you slide in and out of each steering gadget. Your second Joy-Con is always in the gas pedal. If a friend also has a Vehicle Kit, you can face them in a surprisingly fun Battle mode (I had fun blasting the AI opponent alone, too). A few other minigames are also included. Nintendo has already committed to bringing Labo steering wheel to Mario Kart 8 Deluxe (the Variety Kit motorcycle handlebars will, too). Hopefully these steering options become usable in more games. Nintendo Nintendo If you’re interested in Labo, or you're shopping for a kid, it’s probably because you want to construct a lot of cardboard gadgets and make some of your own. The Labo Variety Kit ($70) is a good introduction. It includes five different table-top Toy-Cons, letting you construct a working piano, a fishing rod with a sandbox-style fishing game, two small cars that buzz across the floor, motorbike handlebars for racing, and a house with a Tamagotchi-like creature living in it. Most of these mini games are fun to play for a few minutes, but lack a ton of depth unless you spend time to learn their secrets. There are moments when you’ll wish Nintendo would hold your hand more or keep teaching. After having a ton of fun constructing a cardboard piano for three hours, the end result was a surprisingly functional piano that could play all the notes, and a bunch of extra tools that make fun noises (like cats meowing or weird men yelling). The Toy-Con Piano even has the ability to swap between octaves and record music. Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED My problem: I don’t know how to play a piano. I wish Nintendo had included more tutorials on how to play some classic songs or old Nintendo themes. It hints at some ideas, but leaves it to you to be creative and play whatever you want. For for some kids, this is a gateway to ideas. For the little Jeffreys out there, it may mean that the piano Toy-Con doesn’t get used as much. Other games are more fun to tinker around with. And the Variety Kit has a Garage section, which lets you make your own Toy-Cons. If you or your kid loves to play open-ended games like Minecraft or create inspired Lego creations without instructions, the Variety Kit is a great way to go. Nintendo Nintendo If you or your child like the idea of using your arms, legs, head, and body to control a giant flying robot fighting machine, the Labo Robot Kit ($80) is for you. Instead of five unique, cardboard Toy-Cons, this kit has a single 4-hour project. Your mission is to construct a complex backpack, headset, and string-tethered controls for your feet and hands. It’s very fun, but more about gameplay than discovery. Once you’re wearing the suit, you can use your hands to punch objects and your feet to walk. As a 30-something adult man, I felt a tad embarrassed wearing this corrugated getup, even alone in my apartment, but I also had a ton of fun. It’s not virtual reality, but feels more immersive than some VR games I’ve played thanks to its responsive controls. Your first mission is to smash a city, so you can stomp on buildings or anything else you feel like destroying. If you crouch down, you can transform into a tank and blast enemies that way too. But that’s just the start. Nintendo Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED There are five different types of challenges with multiple levels and they each teach you a new move or ability. If a sibling or friend also has a Labo Robot suit, and you own an extra set of Joy-Cons , you can fight each other in a multiplayer mecha deathmatch. There are other extras, like the ability to fully recolor and customize the look of your robot, a free-for-all music mode that lets you play instruments by moving your arms and legs, and a calorie counter that tells you how many calories you’re burning by stomping and punching away. You won't find endless fun here, and it's a lot of work to put on a full suit every time you want to play, but you can goof around for many hours before feeling like you've mastered the game. Like the Variety Kit, this set also has a Garage that lets you program your own cardboard Labo (or the new robot suit you own). Nintendo For some of you, the Garage will be too much, but for others, it's where the real fun begins. In this area of the software, you can set up rules to program Labo to do a bunch of things. You just tell it what the trigger is (example: if a Joy-Con moves) and then what the result should be (example: make the screen light up). Any of the console's sensors, motors, and buttons are are your disposal. It hasn't happened yet, but if the games attract a community, there could be websites full of instructions on how to make custom Toy-Cons, and Etsy sellers could have a field day peddling pre-cut cardboard to curious kids. Nintendo already sells Labo masking tape in Japan and offers a U.S. Customization Set. It's clear that more cardboard is coming. There are a lot of STEM games and programming toys out there, but there isn’t anything quite like the Nintendo Labo. Building out of cardboard is far more freeing and rewarding than I thought it would be. Even if you rip something or make a mistake, there’s always an easy fix: grab some tape. Anything can be modded, too—as soon as you feel comfortable tinkering with Nintendo’s simple programming interface (and once your parents give you permission to use the scissors). The Labo Toy-Cons work so well they're often magical, but you also get to learn exactly how they work as you build them. That said, some of the Toy-Con games, especially those in the Variety Kit , are open ended and might seem shallow once you're done putting everything together. If building isn’t the top reason you’re buying a Labo, opt for the Vehicle Kit , which has a more comprehensive game attached to it. Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED When I first got Labo, I wondered if it would be like a good set of Lego, or more like something you make and then put on the shelf. The answer will depend on you (or your kid). Nintendo has stuffed an incredible amount of playful software into its three Labo Kits, and goes out of its way to encourage creativity by letting you customize and experiment. With enough imagination, kids and adults can get way more than $70 worth of fun out of any Labo. Heck, I might pay $70 just to sit and peacefully assemble another cardboard gadget. Nintendo Labo Cardboard Kits Rating: 9/10 $45 at Amazon £30 at Amazon If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Learn more. Please also consider subscribing to WIRED $45 at Amazon Reviews Director X Topics Nintendo Reviews Shopping Console Games video games Jeffrey Van Camp David Pierce Chris Kohler Brendan Nystedt Jeffrey Van Camp Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. 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"Better Than Human: Why Robots Will — And Must — Take Our Jobs | WIRED"

"https://www.wired.com/2012/12/ff-robots-will-take-our-jobs"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Kevin Kelly Gear Better Than Human: Why Robots Will — And Must — Take Our Jobs Baxter is an early example of a new class of industrial robots created to work alongside humans. Save this story Save Save this story Save Imagine that 7 out of 10 working Americans got fired tomorrow. What would they all do? It's hard to believe you'd have an economy at all if you gave pink slips to more than half the labor force. But that—in slow motion—is what the industrial revolution did to the workforce of the early 19th century. Two hundred years ago, 70 percent of American workers lived on the farm. Today automation has eliminated all but 1 percent of their jobs, replacing them (and their work animals) with machines. But the displaced workers did not sit idle. Instead, automation created hundreds of millions of jobs in entirely new fields. Those who once farmed were now manning the legions of factories that churned out farm equipment, cars, and other industrial products. Since then, wave upon wave of new occupations have arrived—appliance repairman, offset printer, food chemist, photographer, web designer—each building on previous automation. Today, the vast majority of us are doing jobs that no farmer from the 1800s could have imagined. It may be hard to believe, but before the end of this century, 70 percent of today's occupations will likewise be replaced by automation. Yes, dear reader, even you will have your job taken away by machines. In other words, robot replacement is just a matter of time. This upheaval is being led by a second wave of automation, one that is centered on artificial cognition, cheap sensors, machine learning, and distributed smarts. This deep automation will touch all jobs, from manual labor to knowledge work. First, machines will consolidate their gains in already-automated industries. After robots finish replacing assembly line workers, they will replace the workers in warehouses. Speedy bots able to lift 150 pounds all day long will retrieve boxes, sort them, and load them onto trucks. Fruit and vegetable picking will continue to be robotized until no humans pick outside of specialty farms. Pharmacies will feature a single pill-dispensing robot in the back while the pharmacists focus on patient consulting. Next, the more dexterous chores of cleaning in offices and schools will be taken over by late-night robots, starting with easy-to-do floors and windows and eventually getting to toilets. The highway legs of long-haul trucking routes will be driven by robots embedded in truck cabs. All the while, robots will continue their migration into white-collar work. We already have artificial intelligence in many of our machines; we just don't call it that. Witness one piece of software by Narrative Science (profiled in issue 20.05) that can write newspaper stories about sports games directly from the games' stats or generate a synopsis of a company's stock performance each day from bits of text around the web. Any job dealing with reams of paperwork will be taken over by bots, including much of medicine. Even those areas of medicine not defined by paperwork, such as surgery, are becoming increasingly robotic. The rote tasks of any information-intensive job can be automated. It doesn't matter if you are a doctor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic. And it has already begun. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Here's why we're at the inflection point: Machines are acquiring smarts. We have preconceptions about how an intelligent robot should look and act, and these can blind us to what is already happening around us. To demand that artificial intelligence be humanlike is the same flawed logic as demanding that artificial flying be birdlike, with flapping wings. Robots will think different. To see how far artificial intelligence has penetrated our lives, we need to shed the idea that they will be humanlike. Consider Baxter, a revolutionary new workbot from Rethink Robotics. Designed by Rodney Brooks, the former MIT professor who invented the best-selling Roomba vacuum cleaner and its descendants, Baxter is an early example of a new class of industrial robots created to work alongside humans. Baxter does not look impressive. It's got big strong arms and a flatscreen display like many industrial bots. And Baxter's hands perform repetitive manual tasks, just as factory robots do. But it's different in three significant ways. First, it can look around and indicate where it is looking by shifting the cartoon eyes on its head. It can perceive humans working near it and avoid injuring them. And workers can see whether it sees them. Previous industrial robots couldn't do this, which means that working robots have to be physically segregated from humans. The typical factory robot is imprisoned within a chain-link fence or caged in a glass case. They are simply too dangerous to be around, because they are oblivious to others. This isolation prevents such robots from working in a small shop, where isolation is not practical. Optimally, workers should be able to get materials to and from the robot or to tweak its controls by hand throughout the workday; isolation makes that difficult. Baxter, however, is aware. Using force-feedback technology to feel if it is colliding with a person or another bot, it is courteous. You can plug it into a wall socket in your garage and easily work right next to it. Second, anyone can train Baxter. It is not as fast, strong, or precise as other industrial robots, but it is smarter. To train the bot you simply grab its arms and guide them in the correct motions and sequence. It's a kind of "watch me do this" routine. Baxter learns the procedure and then repeats it. Any worker is capable of this show-and-tell; you don't even have to be literate. Previous workbots required highly educated engineers and crack programmers to write thousands of lines of code (and then debug them) in order to instruct the robot in the simplest change of task. The code has to be loaded in batch mode, i.e., in large, infrequent batches, because the robot cannot be reprogrammed while it is being used. Turns out the real cost of the typical industrial robot is not its hardware but its operation. Industrial robots cost $100,000-plus to purchase but can require four times that amount over a lifespan to program, train, and maintain. The costs pile up until the average lifetime bill for an industrial robot is half a million dollars or more. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So The third difference, then, is that Baxter is cheap. Priced at $22,000, it's in a different league compared with the $500,000 total bill of its predecessors. It is as if those established robots, with their batch-mode programming, are the mainframe computers of the robot world, and Baxter is the first PC robot. It is likely to be dismissed as a hobbyist toy, missing key features like sub-millimeter precision, and not serious enough. But as with the PC, and unlike the mainframe, the user can interact with it directly, immediately, without waiting for experts to mediate—and use it for nonserious, even frivolous things. It's cheap enough that small-time manufacturers can afford one to package up their wares or custom paint their product or run their 3-D printing machine. Or you could staff up a factory that makes iPhones. Photo: Peter Yang Baxter was invented in a century-old brick building near the Charles River in Boston. In 1895 the building was a manufacturing marvel in the very center of the new manufacturing world. It even generated its own electricity. For a hundred years the factories inside its walls changed the world around us. Now the capabilities of Baxter and the approaching cascade of superior robot workers spur Brooks to speculate on how these robots will shift manufacturing in a disruption greater than the last revolution. Looking out his office window at the former industrial neighborhood, he says, "Right now we think of manufacturing as happening in China. But as manufacturing costs sink because of robots, the costs of transportation become a far greater factor than the cost of production. Nearby will be cheap. So we'll get this network of locally franchised factories, where most things will be made within 5 miles of where they are needed." That may be true of making stuff, but a lot of jobs left in the world for humans are service jobs. I ask Brooks to walk with me through a local McDonald's and point out the jobs that his kind of robots can replace. He demurs and suggests it might be 30 years before robots will cook for us. "In a fast food place you're not doing the same task very long. You're always changing things on the fly, so you need special solutions. We are not trying to sell a specific solution. We are building a general-purpose machine that other workers can set up themselves and work alongside." And once we can cowork with robots right next to us, it's inevitable that our tasks will bleed together, and soon our old work will become theirs—and our new work will become something we can hardly imagine. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So To understand how robot replacement will happen, it's useful to break down our relationship with robots into four categories, as summed up in this chart: The rows indicate whether robots will take over existing jobs or make new ones, and the columns indicate whether these jobs seem (at first) like jobs for humans or for machines. Let's begin with quadrant A: jobs humans can do but robots can do even better. Humans can weave cotton cloth with great effort, but automated looms make perfect cloth, by the mile, for a few cents. The only reason to buy handmade cloth today is because you want the imperfections humans introduce. We no longer value irregularities while traveling 70 miles per hour, though—so the fewer humans who touch our car as it is being made, the better. And yet for more complicated chores, we still tend to believe computers and robots can't be trusted. That's why we've been slow to acknowledge how they've mastered some conceptual routines, in some cases even surpassing their mastery of physical routines. A computerized brain known as the autopilot can fly a 787 jet unaided, but irrationally we place human pilots in the cockpit to babysit the autopilot "just in case." In the 1990s, computerized mortgage appraisals replaced human appraisers wholesale. Much tax preparation has gone to computers, as well as routine x-ray analysis and pretrial evidence-gathering—all once done by highly paid smart people. We've accepted utter reliability in robot manufacturing; soon we'll accept it in robotic intelligence and service. Next is quadrant B: jobs that humans can't do but robots can. A trivial example: Humans have trouble making a single brass screw unassisted, but automation can produce a thousand exact ones per hour. Without automation, we could not make a single computer chip—a job that requires degrees of precision, control, and unwavering attention that our animal bodies don't possess. Likewise no human, indeed no group of humans, no matter their education, can quickly search through all the web pages in the world to uncover the one page revealing the price of eggs in Katmandu yesterday. Every time you click on the search button you are employing a robot to do something we as a species are unable to do alone. While the displacement of formerly human jobs gets all the headlines, the greatest benefits bestowed by robots and automation come from their occupation of jobs we are unable to do. We don't have the attention span to inspect every square millimeter of every CAT scan looking for cancer cells. We don't have the millisecond reflexes needed to inflate molten glass into the shape of a bottle. We don't have an infallible memory to keep track of every pitch in Major League Baseball and calculate the probability of the next pitch in real time. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So We aren't giving "good jobs" to robots. Most of the time we are giving them jobs we could never do. Without them, these jobs would remain undone. Now let's consider quadrant C, the new jobs created by automation—including the jobs that we did not know we wanted done. This is the greatest genius of the robot takeover: With the assistance of robots and computerized intelligence, we already can do things we never imagined doing 150 years ago. We can remove a tumor in our gut through our navel, make a talking-picture video of our wedding, drive a cart on Mars, print a pattern on fabric that a friend mailed to us through the air. We are doing, and are sometimes paid for doing, a million new activities that would have dazzled and shocked the farmers of 1850. These new accomplishments are not merely chores that were difficult before. Rather they are dreams that are created chiefly by the capabilities of the machines that can do them. They are jobs the machines make up. Before we invented automobiles, air-conditioning, flatscreen video displays, and animated cartoons, no one living in ancient Rome wished they could watch cartoons while riding to Athens in climate-controlled comfort. Two hundred years ago not a single citizen of Shanghai would have told you that they would buy a tiny slab that allowed them to talk to faraway friends before they would buy indoor plumbing. Crafty AIs embedded in first-person-shooter games have given millions of teenage boys the urge, the need, to become professional game designers—a dream that no boy in Victorian times ever had. In a very real way our inventions assign us our jobs. Each successful bit of automation generates new occupations—occupations we would not have fantasized about without the prompting of the automation. To reiterate, the bulk of new tasks created by automation are tasks only other automation can handle. Now that we have search engines like Google, we set the servant upon a thousand new errands. Google, can you tell me where my phone is? Google, can you match the people suffering depression with the doctors selling pills? Google, can you predict when the next viral epidemic will erupt? Technology is indiscriminate this way, piling up possibilities and options for both humans and machines. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So It is a safe bet that the highest-earning professions in the year 2050 will depend on automations and machines that have not been invented yet. That is, we can't see these jobs from here, because we can't yet see the machines and technologies that will make them possible. Robots create jobs that we did not even know we wanted done. Photo: Peter Yang Finally, that leaves us with quadrant D, the jobs that only humans can do—at first. The one thing humans can do that robots can't (at least for a long while) is to decide what it is that humans want to do. This is not a trivial trick; our desires are inspired by our previous inventions, making this a circular question. When robots and automation do our most basic work, making it relatively easy for us to be fed, clothed, and sheltered, then we are free to ask, "What are humans for?" Industrialization did more than just extend the average human lifespan. It led a greater percentage of the population to decide that humans were meant to be ballerinas, full-time musicians, mathematicians, athletes, fashion designers, yoga masters, fan-fiction authors, and folks with one-of-a kind titles on their business cards. With the help of our machines, we could take up these roles; but of course, over time, the machines will do these as well. We'll then be empowered to dream up yet more answers to the question "What should we do?" It will be many generations before a robot can answer that. This postindustrial economy will keep expanding, even though most of the work is done by bots, because part of your task tomorrow will be to find, make, and complete new things to do, new things that will later become repetitive jobs for the robots. In the coming years robot-driven cars and trucks will become ubiquitous; this automation will spawn the new human occupation of trip optimizer, a person who tweaks the traffic system for optimal energy and time usage. Routine robo-surgery will necessitate the new skills of keeping machines sterile. When automatic self-tracking of all your activities becomes the normal thing to do, a new breed of professional analysts will arise to help you make sense of the data. And of course we will need a whole army of robot nannies, dedicated to keeping your personal bots up and running. Each of these new vocations will in turn be taken over by robots later. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So The real revolution erupts when everyone has personal workbots, the descendants of Baxter, at their beck and call. Imagine you run a small organic farm. Your fleet of worker bots do all the weeding, pest control, and harvesting of produce, as directed by an overseer bot, embodied by a mesh of probes in the soil. One day your task might be to research which variety of heirloom tomato to plant; the next day it might be to update your custom labels. The bots perform everything else that can be measured. Right now it seems unthinkable: We can't imagine a bot that can assemble a stack of ingredients into a gift or manufacture spare parts for our lawn mower or fabricate materials for our new kitchen. We can't imagine our nephews and nieces running a dozen workbots in their garage, churning out inverters for their friend's electric-vehicle startup. We can't imagine our children becoming appliance designers, making custom batches of liquid-nitrogen dessert machines to sell to the millionaires in China. But that's what personal robot automation will enable. Everyone will have access to a personal robot, but simply owning one will not guarantee success. Rather, success will go to those who innovate in the organization, optimization, and customization of the process of getting work done with bots and machines. Geographical clusters of production will matter, not for any differential in labor costs but because of the differential in human expertise. It's human-robot symbiosis. Our human assignment will be to keep making jobs for robots—and that is a task that will never be finished. So we will always have at least that one "job." In the coming years our relationships with robots will become ever more complex. But already a recurring pattern is emerging. No matter what your current job or your salary, you will progress through these Seven Stages of Robot Replacement, again and again: 1. A robot/computer cannot possibly do the tasks I do. [Later.] 2. OK, it can do a lot of them, but it can't do everything I do. [Later.] 3. OK, it can do everything I do, except it needs me when it breaks down, which is often. [Later.] 4. OK, it operates flawlessly on routine stuff, but I need to train it for new tasks. [Later.] 5. OK, it can have my old boring job, because it's obvious that was not a job that humans were meant to do. [Later.] 6. Wow, now that robots are doing my old job, my new job is much more fun and pays more! [Later.] 7. I am so glad a robot/computer cannot possibly do what I do now. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So This is not a race against the machines. If we race against them, we lose. This is a race with the machines. You'll be paid in the future based on how well you work with robots. Ninety percent of your coworkers will be unseen machines. Most of what you do will not be possible without them. And there will be a blurry line between what you do and what they do. You might no longer think of it as a job, at least at first, because anything that seems like drudgery will be done by robots. We need to let robots take over. They will do jobs we have been doing, and do them much better than we can. They will do jobs we can't do at all. They will do jobs we never imagined even needed to be done. And they will help us discover new jobs for ourselves, new tasks that expand who we are. They will let us focus on becoming more human than we were. Let the robots take the jobs, and let them help us dream up new work that matters. Kevin Kelly ( kk.org ) is senior maverick of Wired and the author, most recently, of What Technology Wants. Simon Hill Simon Hill Jaina Grey Brenda Stolyar Boone Ashworth Matt Jancer Simon Hill Adrienne So WIRED COUPONS Modloft Discount Code Black Friday Sale: 50% off sitewide + Extra $100 Modloft discount code SHEIN Coupon Code Up to 30% off -SHEIN Coupon Code Instacart promo code Instacart promo code: $25 Off your 1st order + free delivery Doordash Promo Code 50% Off DoorDash Promo Code + Free Delivery Ulta Beauty coupon Ulta Beauty Coupon Code: get $3.50 Off $15 qualifying purchase Uber Eats promo code Uber Eats promo code 2023: $15 off Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Pete Buttigieg Loves God, Beer, and His Electric Mustang | WIRED"

"https://www.wired.com/story/pete-buttigieg-interview-god-beer-electric-mustang"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons By Virginia Heffernan Backchannel Pete Buttigieg Loves God, Beer, and His Electric Mustang Facebook X Email Save Story Photograph: Argus Paul Estabrook Save this story Save Save this story Save The curious mind of Pete Buttigieg holds much of its functionality in reserve. Even as he discusses railroads and airlines, down to the pointillist data that is his current stock-in-trade, the US secretary of transportation comes off like a Mensa black card holder who might have a secret Go habit or a three-second Rubik’s Cube solution or a knack for supplying, off the top of his head, the day of the week for a random date in 1404, along with a non-condescending history of the Julian and Gregorian calendars. As Secretary Buttigieg and I talked in his underfurnished corner office one afternoon in early spring, I slowly became aware that his cabinet job requires only a modest portion of his cognitive powers. Other mental facilities, no kidding, are apportioned to the Iliad , Puritan historiography, and Knausgaard’s Spring —though not in the original Norwegian (slacker). Fortunately, he was willing to devote yet another apse in his cathedral mind to making his ideas about three mighty themes—neoliberalism, masculinity, and Christianity—intelligible to me. This article appears in the Jul/Aug 2023 issue. Subscribe to WIRED. Illustration: Vivek Thakker Because Buttigieg , at 41, is an old millennial; because as a Rhodes Scholar at Oxford he got a first in PPE (Philosophy, Politics, and Economics), the trademark degree for Labour-party elites of the Tony Blair era; because he worked optimizing grocery-store pricing at McKinsey; because he joined the Navy in hopes of promoting democracy in Afghanistan; because he got gay-married to his partner Chasten in 2018; and because, as mayor of South Bend, Indiana, he agitated to bring hipster entrepreneurism and “high-tech investment” to his rust-belt hometown , I had to ask him about neoliberalism, the happy idea that consumer markets and liberal democracy will always expand, and will always expand together. I was also fascinated by the way that Buttigieg, who has long described himself as obsessed with technology and data, has responded to the gendering of tech, and especially green tech, by fearsome culture warriors, including Marjorie Taylor Greene. Buttigieg, whose father was a renowned Marxist scholar, was himself a devotee of Senator Bernie Sanders as a young man. He now recognizes that the persistence of far-right ideology, with its masculinist and antidemocratic preoccupations, is part of the reason that neoliberalism has come undone. Not everyone, it seems, even wants a rising standard of living if it means they have to accept the greater enfranchisement of undesirables, including, of course, women, poor people, Black people, and the usual demons in the sights of the world’s Ted Cruzes and Tucker Carlsons. He also talked about his faith. Lefties these days are said to be less religious than right-wing evangelicals, but between Buttigieg, whose Episcopalianism grounds his decisionmaking, and his boss, President Joe Biden, whose robust Catholicism drives his sincere effort to revive America’s soul, perhaps a religious left is rising again. Virginia Heffernan: What is neoliberalism, and what happened to it? Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Pete Buttigieg : When it comes to neoliberalism, we got mugged by reality. That’s one cheeky way to put it. Poor old liberals. Always getting mugged by reality, or just muggers. Look, in the early part of my adulthood, neoliberalism was described almost as a consensus that just made sense—at least to everybody in positions of influence. Now it’s very different. We have experienced the end of the end of history. We have certainly experienced the limitations of the consensus. None of the assumptions from between roughly 1991 and 2008 have survived. Specifically? Certainly not the idea that the global move toward democracy is a one-way street. Nor the idea that greater integration between markets and governments means greater harmony politically. Nor the idea that if we acted to make sure the pie gets bigger, everyone’s slice would follow suit, which was the promise that was made to the industrial Midwest at the time of NAFTA. The lived reality of the younger generations is that they are experiencing climate issues not as a theoretical possibility but as a clear and present danger. These are generations that have experienced the reality that disparities, including racial disparities, left alone, will only compound. They won’t cure of their own gravitational tendency. … or tendencies of the market? Right. Because market tendencies depend very much on what you have to begin with—the initial endowment, as the economists call it. But your initial endowment looks very different if your previous generation was dispossessed. Last year I was in Berlin as they were confronting the tectonic disruption that had been caused by Russia’s invasion of Ukraine. They have this very German word for it: Zeitenwende. A turning point. The war blew up their presumption that when it came to Russia, more integration between it and Europe would mean more stability. This has been our presumption about China too—that greater economic integration would mean not just greater stability, but a more or less inevitable move on the part of China into greater acceptance of democratic norms, market norms, and a rules-based international order. We’ve come to the point where we are super-integrated, but that economic relationship with China has not yielded the kind of comfort that was promised. As we careen toward the second quarter of the century, suddenly industrial policy sounds less retro and more like a response to the times. “Industrial policy”—is this paleoliberalism? Well, there are some new, or at least renewed, ways of thinking about transportation policy we work on at DOT that embrace the importance of public investment, which is a big part of the philosophy of the infrastructure bill. There are more than 32,000 new infrastructure projects now underway in every state and territory, all across the country. We created an interactive map so people can see what's up in their communities. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg We’re also facing the effects of anticompetitive behavior in pretty much every industry connected to the movement of people and goods. Was there, maybe, a comeback of a pared-down version of neoliberalism—or at least the hope that markets and democracy might work in sync—when Ted Cruz coined “Woke Coke” to show contempt for Coca-Cola’s protest of voter suppression in Georgia? Well, yes, there’s something delicious about the way that Cruz and the rest of them have positioned themselves on one side of the fence. And Netflix, Coca-Cola, Disney, and Bud Light are on the other side. Along with most of America. There may in fact be a center of gravity in this country that includes both a Democratic majority of the American people, and even something of a consensus, at least among mainstream business leaders. We have certain commitments around democracy and inclusion that are really elemental to the whole system. Photograph: Argus Paul Estabrook True. But the right likes to dismiss any political action—even in the name of elemental American ideals—as pretense or virtue-signaling. I think of the time Putin defined the Kremlin’s enemy as foie gras, oysters, and “gender freedoms.” An American conservative might hear him and say, OK, foie gras, pronouns—annoying, pretentious, sure. But do Republicans really want to be dragged into a bigger far-right project, including the renunciation of democracy, modernity, civil rights, human rights? Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Look, the mainstream right’s political project was twofold. It was to prevent legal access to abortion and to sustain lower taxes for the wealthy. Those are kind of the two greatest pillars of the mainstream right now. They’re now the dog that caught the car. And, to switch metaphors, they rode a tiger to get there. They made a lot of distasteful bargains in order to get there. Sometimes the military—the military , of all institutions—comes under attack from the far right. On ideological grounds. Yet another front in the culture war. The woke Pentagon. You could add that to the list: Bud Light, Coke, football, Disney … and the Army. You can only put yourself on the wrong side of so many red, white, and blue American institutions, and the question becomes, Is this about you? Speaking of is-this-about-you, have you followed the masculinity crusade of former TV personality Tucker Carlson—testicle warming and the rest? I mean, where to begin on this? Fears about masculinity are a way into the fear of displacement. Masculinity establishes a default place, and that place is being shifted and threatened by modernity. A man as the head of the household. The only one who earns income. The default leader in any social or political organization. The politicization of masculinity is code for Nothing in your life has to change. The problem is, of course, lots of things have to change. Either because there was something wrong with the old way—or because, even as the old way seemed perfectly fine, it’s not an option. This is true with the realities of climate change. If you can’t face that change, you might retreat to the default place of masculinity. Maybe that’s why someone characterized electric vehicles as emasculating. I think it was Marjorie Taylor Greene. Are they not? To me, a car is a car. Actually, the electric truck has got more torque than a regular truck. And it’ll tow just as well. And yet EVs unaccountably fall on the femme side of the ledger, like Impossible burgers. Right. A lot of this discussion about masculinity doesn’t have anything to do with the immediate function that’s at stake. I’m thinking about burgers, right? I love a good cheeseburger. I hate a bad veggie burger. I like a good veggie burger. The Burger King Impossible Whopper with bacon is not a bad combo. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Likewise, when it comes to driving. I mean, there’s a very literal, physical, technical sense in which power is at stake when you drive. It feels good to be driving a vehicle with a lot of power. The vehicle I get around DC in is a Mustang Mach-E. The fact that Ford made one of their first electric vehicles a Mustang is probably not an accident. It has three modes. Whisper, Engage, and Unbridled. There are propulsion sound effects involved in the different modes to help you feel conscious of the power of the engine. Clearly, we have a chance to rewrite some of these easy gender tropes. My life happens to cut across them. I like drinking beer, lifting weights, splitting wood. I'm also gay and I like playing piano. I do a lot of the caregiving for our toddlers and other things that supposedly aren’t masculine. Your secrets are safe with me. So what’s going to stop the androgen-addled, Putin-besotted ideologues? When it comes to conspiracy theories and extreme partisan ideologies, I found two things are true. One, it’s always more people than you would think. Disturbingly so. But it’s also, almost always, much less than a majority. The problem, of course, is there are some features of the American system where you could be a long way from the majority and still take control of certain decisions. We’re seeing a lot of counter-majoritarian movements, with, of course, abortion being an example. But facts still matter. And when a fact is challenged, or a supposed fact, like “the Russian Federation’s army is unbeatable.” Right? I have to think that catches up to you. At a certain point, in Russia, for example, you see those charts by region of the areas that suffered the most casualties. Just as a statistical matter, it is impossible for a false narrative to hold. And here in the US the confrontation with reality comes every time I get a letter of support from a House Republican for a transportation project using funds from the bill they voted against. It’s shameless. But it’s also reassuring that they’re the first to come to a ribbon-cutting when we fund a project in their community. It’s a reminder that there is such a thing as true and false. These funds are helping all over the country. That’s true. And one thing that’s false is that it was a good idea to be against these funds. It was a bad idea. People like infrastructure, I guess. Even Marjorie Taylor Greene isn’t pro-pothole. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Exactly. Everyone here cares about delivering on the president’s view that the way we vindicate democracy, at a time when democracy really is being challenged frontally, is we take care of the basics. In my corner of this administration, we work on things like fixing bridges and holes in the road and keeping people safe in the transportation systems. Another major goal of ours is to reverse the rise of roadway deaths in this country. Early data suggests we may be seeing those numbers stop rising and then go down. That could be the most important thing we do here, because a day’s worth—one day’s worth—of roadway deaths in this country represents more death and destruction than a year’s worth of losses across the rest of our transportation system. So given how hard we work to push the number of, for example, accidental railway casualties from the single digits toward zero, and to make sure there are not just no airline crashes but no close calls with airlines, what it would mean to reverse that rise in roadway deaths, which claims about 40,000 lives a year, yeah, that’s an enormous one. Do you think the administration’s work on the basics is getting through? Every time I go to celebrate a new bridge, we have a great time with local leaders who fought so hard to get it done. But it bears little chance of penetrating the national news of the day. Our task here is to deliver so much good news that the volume of it outweighs the tendency to focus on what went wrong. I think we might do this. One formulation is that we’ve delivered the most significant economic legislation since FDR, the most important infrastructure initiative since Eisenhower, and the second most important health care work since LBJ. All while dealing with the first land war in Europe since Truman and facing the biggest public health crisis since Wilson, with the slimmest governing majority in Congress in almost 100 years. You see it that way and you think, Well, yeah. That’s right. We’ve gotta shout that from the rooftops. Let’s talk about Christianity. The first time I heard you say “Christ” and not “Jesus,” I figured out you were an Episcopalian. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg I didn’t know that was a tell! I’m not sure if it is in the books as a tell. But that’s how I read it. So how does your faith influence you? Well, every policy decision I make should be equally fair to people of every faith and no faith. It should be as defensible to me as somebody who is religious as it would be if I were not. At the same time, you can’t help but notice certain rhymes between your religious convictions and the choices you’re called on to make in a job like this. There’s a lot in the faith tradition that I hold close about “the least of these” [the imperative to help the needy]. This doesn’t just go to the worth of your choices, but even your worth as a person, which depends in no small measure on how you make yourself useful to those who have the least power and the least means. When you’re making public policy, you’re often asking yourself, “How does this choice help people who would have the least going for them?” So that’s part of it. Photograph: Argus Paul Estabrook Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Running DOT seems to suit you. Are there more ways the challenges of transportation speak to your spiritual side? There’s just a lot in the scriptural tradition around journeys, around roads, right? The conversion of Saint Paul happens on the road. I think we are all nearer to our spiritual potential when we’re on the move. Something about movement, something about travel pulls us out of the routines that numb us to who we are, to what we’re doing, to everything from our relationships with each other to our relationships with God. That’s part of the reason why so many important things in the Bible happen on highways. And then journeys—they’re also just marvels. Every flight is a marvel that pulls us out of that in the same way that religious rituals, holidays, liturgies are one kind of routine that pulls us out of another kind of routine. When you get on a plane, people buckle their seat belts and listen to the flight attendants’ very predictable pronouncements. It’s routine. It’s almost a ritual, right? And yet you’re preparing to fly through the heavens. Life is a combination of drudgery and miracles. Part of what keeps me at home in the Episcopal faith is that it is liturgically rather conservative. I like that routine. I don’t know if you’ll remotely agree with me, but I’ve come to consider January 6 as a triumph of something like drudgery—or at least of the mundane. Even after terrible violence, destruction, and bloodshed came to the US Capitol, Congress returned to carry out its clerical workday. The paperwork got filed. The flag of the ordinary was still there. Yeah, I agree there’s something that bears more attention about how Congress stayed, came back, finished the job. That’s real. And the fact that the Republic held is real. And another under-remarked fact is the courts did a good job of surfacing what was true and what was false. Because in the US court of law there are actual consequences to lying, and you have to actually present evidence in favor of your client, so it turns out to be less susceptible to the warping of reality. That being said, part of why we would hesitate to assign any triumph to that day—in addition to just the awfulness of it—is that we don’t yet know how the story ends. When we look back at moments further in history, we think of the outcome as settled and stable. We have to go out of our way to be rightly afraid of how close we came. If you study the Cuban Missile Crisis, it’s a study in leaders doing the right thing. But, also, the more you put yourself in their shoes, the more terrifying it is. How do you think this particular crisis will resolve? I think a lot now about the worst experience of my life, the critical hospitalization of my son. He was treated with RSV, which is a respiratory disease. Like many viruses, it takes a certain course where it gets worse and worse and worse. It reaches the worst moment. And, if the patient survives, then it gets better and better. The terror of it as a parent is the only way you know it’s getting better is when it’s stopped getting worse. There are a lot of things like that in the world. The conditions of our democratic institutions—we don’t know how much rougher things might get before things get better. Let us know what you think about this article. Submit a letter to the editor at [email protected]. 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"Craig Venter's Epic Voyage to Redefine the Origin of the Species | WIRED"

"https://www.wired.com/2004/08/venter"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons James Shreeve Craig Venter's Epic Voyage to Redefine the Origin of the Species Save this story Save Save this story Save Picture this: You are standing at the edge of a lagoon on a South Pacific island. The nearest village is 20 miles away, reachable only by boat. The water is as clear as air. Overhead, white fairy terns hover and peep among the coconut trees. Perhaps 100 yards away, you see a man strolling in the shallows. He is bald, bearded, and buck naked. He stoops every once in a while to pick up a shell or examine something in the sand. A lot of people wonder what happened to J. Craig Venter, the maverick biologist who a few years ago raced the US government to sequence the human genetic code. Well, you’ve found him. His pate is sunburned, and the beard is new since he graced the covers of Time and BusinessWeek. It makes him look younger and more relaxed - not that I ever saw him looking very tense, even when the genome race got ugly and his enemies were closing in. This afternoon, the only adversary he has to contend with is the occasional no-see-um nipping at some tender body part. "Nobody out here has ever heard of the human genome," he told me a week ago, when I first joined him in French Polynesia. "It’s great." Venter is here not just to enjoy himself, though he has been doing plenty of that. What separates him from your average 58-year-old nude beachcomber is that he’s in the midst of a scientific enterprise as ambitious as anything he’s ever done. Leaving colleagues and rivals to comb through the finished human code in search of individual genes, he has decided to sequence the genome of Mother Earth. What we think of as life on this planet is only the surface layer of a vast undiscovered world. The great majority of Earth’s species are bacteria and other microorganisms. They form the bottom of the food chain and orchestrate the cycling of carbon, nitrogen, and other nutrients through the ecosystem. They are the dark matter of life. They may also hold the key to generating a near-infinite amount of energy, developing powerful pharmaceuticals, and cleaning up the ecological messes our species has made. But we don’t really know what they can do, because we don’t even know what they are. Venter wants to change that. He’s circling the globe in his luxury yacht the Sorcerer II on an expedition that updates the great scientific voyages of the 18th and 19th centuries, notably Charles Darwin’s journey aboard HMS Beagle. But instead of bagging his finds in bottles and gunnysacks, Venter is capturing their DNA on filter paper and shipping it to be sequenced and analyzed at his headquarters in Rockville, Maryland. The hope is to uncover tens or even hundreds of millions of new genes, an immense bolus of information on Earth’s biodiversity. In the process, he’s having a hell of a good time and getting a very good tan. "We’re talking about an unknown world of enormous importance," says Harvard biologist and writer E. O. Wilson, who serves on the scientific advisory board of the Sorcerer II expedition. "Venter is one of the first to get serious about exploring that world in its totality. This is a guy who thinks big and acts accordingly." He certainly talks big. "We will be able to extrapolate about all life from this survey," Venter says. "This will put everything Darwin missed into context." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg For now, though, the expedition has run aground, snagged on an unanticipated political reef here in French-controlled waters. But it may all work out tomorrow. Right now, the sun is just beginning to soften toward sunset, and a gentle breeze is rustling the palms. Venter has disappeared in the direction of the boat, and one of his crew members, wearing a Sorcerer II T-shirt over her bathing suit, is waving me back. Must be close to dinnertime. The last time I spent a few days with Venter on his yacht was in 2002 on St. Barts. He was in a much darker mood. He had just been fired as head of Celera Genomics and was hiding out in the Caribbean, licking his wounds. He had started the company four years before to prove that a technique called whole-genome shotgun sequencing could determine the identity and order of all DNA code in a human cell and do it much faster than the conventional method favored by the government-funded Human Genome Project. He had already made science history by using his technique to uncover the first genome of a bacterium, but most people doubted it would work on something as large and complicated as a human being. Undaunted, he pushed ahead, informing the leaders of the government program that they should just leave the human genome to him and sequence the mouse instead. Venter also promised that he would give away the basic human code for free. Celera would make money by selling access to gobs of additional genomic information and the powerful bioinformatics software tools needed to interpret it. His critics claimed that he was trying to have it both ways, taking credit for providing the world with the code to human life and reaping profits for his shareholders at the same time. Venter cheerfully agreed. Things didn’t quite go according to plan. His gambit did indeed accelerate the pace of human DNA sequencing, and the shotgun approach has now become the standard method of decoding genomes. But galled by the effrontery of Venter’s challenge, the Human Genome Project scientists closed ranks and ramped up their efforts quickly enough to offer a draft of the genome almost as fast as Celera’s nine-month sprint. In June 2000, the increasingly bitter race came to an end in a politically manufactured tie celebrated at the White House. The détente with the public-program scientists lasted about as long as it takes to pack up a camera crew. And by that summer, Celera, once king of the startup biotech sector, had already begun a long sad slide into the stock-price cellar and corporate obscurity. "My greatest success is that I managed to get hated by both worlds," Venter told me on St. Barts. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg I didn’t see much of him after that. I was finishing a book about the genome race, during which he had given me access to Celera. But I had plenty of material by then and needed some distance from his inexhaustible, often exhausting ego. (As is true for many highly successful people, it was all about him.) I knew his funk would not last very long. Life was too short, and the thrill of accomplishment too powerful a drug for him. Using $100 million from Celera and other stock holdings, he started a nonprofit, the J. Craig Venter Science Foundation, that would free him to do any kind of science he wanted without obligation to an academic review panel or a corporate bottom line. In 2002, the foundation launched the Institute for Biological Energy Alternatives in Rockville, Maryland. At the top of his to-do list: Create life from scratch, splicing artificial DNA sequences to build a functioning synthetic genome then inserting it into a cell. The ultimate goal would be to endow this man-made organism with the genes to perform some specific environmental task - gobble carbon dioxide from the atmosphere, say, or produce hydrogen for fuel cells. Last November, Venter announced that his IBEA team, led by Nobelist Hamilton Smith, had successfully constructed a functioning virus molecule out of 5,386 DNA base pairs in a mere two weeks. "Nothing short of amazing," said US secretary of energy Spencer Abraham, whose agency funded the work. To me, the press conference hoopla had a tinny ring. Another team at SUNY Stony Brook had manufactured a larger virus a year earlier, albeit using a technique that had taken three years. But viral genomes are much smaller than those of truly living organisms - a mere few thousand base pairs, compared with hundreds of thousands in the smallest genome of a bacterium. Most scientists doubted that Venter and his colleagues, or anyone else, could build a genome that big from scratch and get it to work in a cell. Venter was saying he could do it in three to five years. Venter resurfaced in the news early this year with a more substantial, if less sensational, announcement. By applying the whole-genome shotgun method to an entire ecosystem instead of to an individual genome, he had conducted a study of microbial diversity in the Sargasso Sea near Bermuda. Known to have a low concentration of nutrients, the Sargasso was also assumed to harbor relatively few microorganisms. But instead of an ocean desert, Venter found an abundant and varied soup of microbes wherever he sampled the seawater. In March, he announced that his Sargasso team had discovered at least 1,800 new species and more than 1.2 million new genes. Conservatively speaking, that doubled the number of genes previously known from all species in the world. This code was to be made available on GenBank, a public genetic database, for researchers everywhere to use with no strings attached. Included were almost 800 new genes involved in converting sunlight into cellular energy. As a kicker, Venter also revealed that the Sargasso trip was only a pilot project for a vastly more ambitious undertaking: His yacht the Sorcerer II was at that moment in the Galépagos Islands, embarked on a two-year, round-the-world expedition that promised to overwhelm the huge amount of data from the Sargasso Sea. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg A few days later we were talking about how I might join him for a segment of the trip through French Polynesia. "I have this idea of trying to catalog all the genes on the planet," he said, matter-of-factly. I wasn’t sure what that meant - how can anybody find all the genes in the world? How would you use all that raw material when there was already more information in the world’s genetic databases than anyone knew what to do with? But I had never been to the South Pacific, and the names of the places where the boat planned to take samples - Hiva Oa, Takapoto, Fakarava - sounded like the tinkling of shells. I figured it was time to reconnect. When I return to the Sorcerer II for dinner, Venter is dressed in the blue Speedo he’s been wearing most of the time I’ve been down here. He’s checking email on one of the boat’s five computers (not counting the litter of laptops in the main cabin). Charlie Howard, the Sorcerer II ’s captain, is relaxing on deck, as much as he ever relaxes. I remember him from St. Barts. In his previous life, Howard was an electrical engineer in Toronto. Then he decided to take a year off and sail to the Caribbean, and when the year was over he couldn’t think of a good reason to go back. He is 47 now and has been living on boats more or less his whole adult life. Venter can get off the boat anytime and fly back to the States to conduct business, then rejoin the crew later. If Howard were to leave, the expedition would stop. We are on Rangiroa, the largest of many atolls in the Tuamotu Islands, 200 miles northeast of Tahiti. It consists of a low and thin broken ring of beach and vegetation surrounding a huge lagoon. Darwin sailed through the Tuamotus on the Beagle in 1835, marveling at how islands just barely above the sea managed not to be swept away by the ferocious Pacific. More than a half century earlier, Captain James Cook’s HMS Endeavour sighted land here after an open-water passage of 5,000 miles from Tierra del Fuego. "I’m in awe of Cook," Howard says. "Imagine sailing through these islands at night. Nothing but the sound of the surf to let you know you might be in trouble up ahead. That would be scary stuff." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Among those aboard the Endeavour was a young man named Joseph Banks, a member of the Royal Society and "a Gentleman of Large Fortune, well versed in Natural History," according to British Navy records. At 25, Banks was just a few years older than Darwin was when he made his voyage on the Beagle - eager, handsome, and by all accounts a very personable fellow. He got along particularly well with the native women he encountered during the Endeavour ’s subsequent languid stay in Tahiti. Banks had paid-10,000 - the equivalent of about $1 million today - for the privilege of joining Cook’s expedition. His aim was to collect and describe every plant, animal, fish, and bird he could lay his hands on. Just three days out of Plymouth, England, he noted the presence of "a very minute sea Insect" in some water taken on board to season a cask. But most of Banks’ descriptions, like Darwin’s, were of the larger life-forms he shot from the sky, netted from the ocean, or uprooted from the ground. A decade earlier, the Swedish botanist Carl Linnaeus had estimated the total number of plant and animal species on Earth to be no more than about 12,000; Banks and his team (including a student who had worked under Linnaeus) recorded some 2,500 new ones on the Endeavour ’s three-year voyage alone. On his return home, he was the toast of all England, adored by the press and a frequent visitor of the king. Like Banks and Darwin, Venter believes his circumnavigation will greatly increase the number of known species. Of course, his methods and equipment are vastly more sophisticated. But the world he’s exploring is also much more obscure than the one they studied. Scientists estimate that the microbial species identified so far account for less than 1 percent of the total number on Earth. Even under a microscope, the simple shape of microorganisms - rods and spheres, for the most part - makes it difficult to use morphology to describe and classify them, as Banks and Darwin were able to do with the animals and plants they collected. Finally, most microbes do not reproduce sexually, but some do swap genes across species lines, confounding the very notion of "species" in this teeming context. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg All this has led to a skewed view of Earth’s biodiversity. People think of insects as the most numerous organisms. Split open any single insect and hundreds of thousands of microbes will tumble out. Billions live in a handful of soil in your garden or in that gulp of seawater you coughed up at the beach last summer. Yet of the roughly 1.7 million plant and animal species so far named and described, only some 6,000 are microbes - all of which have been cultured. The true number out there may be closer to 10 million. Or perhaps 100 million. Nobody really knows. "Imagine if our entire understanding of biology was based on a visit to the zoo," says Norman Pace of the University of Colorado, Boulder. "That’s where we’ve been in microbiology." Over the past 30 years, Pace has led a generation of microbiologists who use gene sequences instead of morphology and behavior to identify and classify species. This approach does not require culturing the bugs in a petri dish - you just isolate the right bit of DNA using standard molecular biology. Some "housekeeping" genes are so essential to the maintenance of life that they can be found throughout the living world with the order of their DNA letters more or less intact. But over time, small changes do crop up through harmless mutations. Thus, a very close match in the order of letters in such a gene implies a close relationship between two species; a less similar match, a more distant relationship. By combining all such comparisons, you can construct a whole phylogeny of the known microbial world. It is very much a work in progress. In 1987, the first such family tree, constructed by Carl Woese at the University of Illinois, identified 12 phylogenetic divisions. Now there are about 80. One gene in particular, called 16S rRNA, has become a workhorse for identifying and classifying microbes. Every species, from the lowliest bacteria to humans, has one and only one 16S rRNA gene. Extract the DNA from some seawater or soil and count the number of different 16S genes, and you have at least a general idea of how many microbial species there are in the sample. Compare the DNA sequences of those genes, one to another, and you have a notion of their family relationships as well. Venter would have pleased the microbiologists by going to the Sargasso Sea and looking for 16S rRNA genes or zooming in on some other target. But zooming in is not his style. He likes to zoom out. "My theme has always been randomness and random sampling," Venter says. "Every time, people have said it was the wrong way to go about it. And every time, I’ve made major contributions." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Venter’s approach is to take all the DNA from all the microbes he found in the Sargasso Sea at any given location and smash it into bits. He then tries to assemble the pieces into complete genomes, applying the same whole-genome shotgun assembly method he relied on when he conquered the human genome. The computer algorithms he uses are in fact those developed at Celera, though somewhat more refined. The target, however, is very different: Instead of one huge genome, like a giant jigsaw puzzle, there are thousands of tiny puzzles, with no guide to tell which piece belongs in which puzzle. The results from the Sargasso samples surprised Venter. Since the microbial population was so diverse, it was harder for the algorithms to figure out whose DNA was whose and to bundle the fragments neatly into whole genomes. It turned out that only two organisms’ genetic codes were represented in their entirety - far fewer than Venter had anticipated. The study also cast serious doubt on the whole idea of comparing 16S rRNA genes to determine the number of species in a sample. Two assembled sections occasionally contained identical 16S rRNA genes, but the stretches of DNA surrounding the genes would be much too divergent to lump both assemblies into one species. Venter’s study made it look like the 16S rRNA approach was analogous to classifying mammals by comparing just their noses. On the other hand, without a lot more sequences fed into the equation - prohibitively expensive because of the cost of running sequencers - the shotgun assembly approach wasn’t able to get a handle on the number of species, either. There appeared to be a minimum of 1,800, but there could be tens of thousands, depending on what assumptions the computational biologists on Venter’s team used. "What Craig did was like grabbing a cubic mile of Amazon rain forest and trying to sequence the whole thing," says Pace. "He shouldn’t be surprised that it was really complex. Anybody who would do that doesn’t have a good concept of a scientific question." Venter might have answered his critics with a targeted follow-up study of the Sargasso Sea. Instead he decided to sequence the world. "There’s an infinite number of questions you could ask," he says. "We’re just trying to figure out who fucking lives out there." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The Sorcerer II expedition began last August in Halifax, Nova Scotia. Venter chose the departure point partly because another famous scientific expedition - the voyage of HMS Challenger - had visited Halifax in 1873, and partly, he concedes, because he had never sailed that far north and wanted to see what it was like. The Sorcerer II then headed to the Gulf of Maine, continuing down the coast to Narragansett Bay and Chesapeake Bay, passing Cape Hatteras, and cutting around Florida into the Gulf of Mexico, through the Panama Canal and south to the Cocos and Galépagos islands. About every 200 miles, the crew has been taking water samples. Jeff Hoffman, aka Science Boy, oversees the work and doubles as a deckhand. He is 31, has an easy southern manner, and is all but done with a doctorate in microbiology from Lousiana State University. His long, pleasant face is made longer by a goatee that has been sprouting since the expedition got under way. While taking time off from his studies, he was just hanging out and skiing with buddies in Colorado when he got a job interview at IBEA. The fact that Hoffman was a competitive swimmer especially intrigued Venter, who had been one himself. Now Hoffman is sailing around the world. "My dad says I’m the only guy he knows who can fall in a pile of shit and come out smelling like roses," he says. When sampling, Hoffman records the latitude and longitude of a site, along with temperature, salinity, pH, pressure, wind speed, and wave height. Seawater, usually from a depth of about 5 feet, is pumped into a large plastic barrel on board and piped through a cascade of filters mounted in gleaming stainless steel casings in the aft cockpit (see "How to Hunt Microbes," page 111). The filtering process takes up to five hours, including setup and cleanup; during downtime, Hoffman listens to his iPod or lifts weights. When all the water has passed through, he carefully uses tweezers to remove the filters, then bags them. The bags are labeled, frozen, and periodically sent back to his colleagues in Rockville to be analyzed. Sometimes Hoffman scrawls a personal note on the label, like Send burritos or We’re out of Jack Daniels. The color of the used filter papers changes depending on what’s on them. The ocean is hardly one big homogeneous soup. Just by looking at these filters - some seem barely stained, others look like they’ve been dipped in pond scum - you can see there is a lot of variation in the microbial populations from one spot to another. The ones from Halifax Harbor look like they’ve been used for toilet paper, which in a sense they have, since Halifax is one of the largest harbors in the world without a comprehensive sewage treatment system. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Some of the most spectacular sampling came during two weeks in the Galépagos, islands that became famous for Darwin’s sojourn there, as well as for the varieties of finches, mockingbirds, tortoises, and marine iguanas that did so much to buttress Darwin’s theory of natural selection. Venter conceived of his expedition as following in Darwin’s footsteps, and now he was sailing into the same bays and trudging up the same rocky paths as the great man himself. He had organized the visit well ahead with scientists at the Charles Darwin Research Station on the island of Santa Cruz to ensure sampling in the most productive spots; these included several unusual environments, each likely to contain a unique spectrum of microbial life, with differing metabolic pathways and hence different sets of genes. In several locations, they took soil samples to supplement the water specimens. Getting those samples from the top of Wolf Island was a separate adventure. It required four crew members to leap onto a sheer rock face from a dinghy surging on 7-foot-tall surf, while Howard fought to keep the boat from crashing into the cliff. They picked their way up the slope wherever they could find a foothold, navigating around the famously unafraid frigate birds and boobies and trying especially to avoid the babies pecking at their hands and feet. All this in roasting heat. "It was a pretty intense climb," Hoffman tells me. "We were all sweating our asses off." On the return trip, he and another climber flung themselves off the cliff face into the cool water 30 feet below. Venter’s expedition also took samples from mangrove swamps, iguana nesting areas, and interior lakes. The team obtained a promising sample directly from a sulfur vent bubbling up from the seafloor off another chunk of rock called Roca Redonda. Venter and Brooke Dill, the expedition’s diving master, plunged 60 feet underwater with the sampling hose, struggling not to be swept away or battered against the rocks by the swirling currents. Sea lions danced overhead. To get a sample from a flamingo-dotted pond on the island of Floreana, Venter, Hoffman, and others lugged 13-gallon carboys over a hill to be loaded onto the boat. It was worth it. The 100-degree water was so full of life that the filters clogged up after only 3 gallons of water had passed through. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg A week after my trip, I caught up with the Galépagos samples at IBEA in Rockville, where molecular biologist Cyndi Pfannkoch, who runs the DNA prep facility, took me through the extraction process. The filter papers are first cut into tiny pieces and placed into a buffer that cracks open the cell walls of the organisms, spilling their contents. Chemicals are added to chew up proteins and leave just the DNA, which is spun out of the solution. Pfannkoch pulled a vial from a rack and held it up to the light. "See that white glob down there?" she said. "That’s DNA from the flamingo pond. Compared to a typical sample, this is huge. I can’t wait to see what’s in it." On our way out the door to visit the lab where the DNA is sequenced, Pfannkoch opened a huge freezer; stored inside at -112 degrees Fahrenheit were Hoffman’s labeled pouches. She took out a bag and rubbed the thick layer of frost off the label with a finger. In addition to the ID, it read: Panamanian women are hot. When the boat was five days out from the Galépagos, a shrieking alarm warned that the engine was dangerously overheating. Howard rushed below and found that the belt driving the alternator and water pump had shredded. In preparation for just these incidents, he had squirreled away spare parts behind every floor and ceiling panel, and he replaced the belt easily. But a day later that one blew, too. Howard dug into the problem and discovered that a couple of ball bearings had self-destructed in the pulley holding the belt. That was one part with no spare. To make things worse, the ship was about to enter the Pacific doldrums, and it might have taken weeks to reach Polynesia under sail. "When you hear Charlie yelling, ’Oh, shit!’ that’s not good," Hoffman says. "The guy is MacGyver." Howard cursed some more, thought for a while, then rigged up a workaround by cannibalizing some bearings from a less crucial pulley. He wasn’t sure if it would hold 10 minutes or 10 hours. It’s a couple of weeks later now, and the engine is still running on the fix. Then there are the political obstacles. Marine research is governed by the United Nations Convention on the Law of the Sea, which outlines what one country must do when undertaking science in another’s territorial waters. If you’re talking about garden-variety oceanographic research, obtaining permission is usually easy. But the unprecedented scale of this genetic dredging project - We’re going to sequence everything we find! - would raise a few red flags even if its leader were not J. Craig Venter. And the obstacles are higher since many people are still certain that "Darth Venter" tried to privatize the human genome, allowing access to the code only to the deep pockets who could afford it. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg This time around, he’s doing everything he can to convince the world that he has no commercial motive: Here, take it all, I ask for nothing in return. His generosity has actually exacerbated his political problems. By the nature of its research, the Sorcerer II expedition falls under the jurisdiction of the United Nations Convention on Biological Diversity, which has established guidelines for "benefit sharing" of resources. In return for access to their waters, in other words, governments expect a piece of the action. But if - like Venter - you are giving everything away, you don’t have any benefits to share. "The irony is just too great," he says. "I’m getting attacked for putting data in the public domain." The expedition has also come under assault by activists. On March 11, while the Sorcerer II was in the Galépagos, the Canada-based Action Group on Erosion, Technology, and Concentration issued a press release titled "Playing God in the Galépagos." "J. Craig Venter, the genomics mogul and scientific wizard who recently created a unique living organism from scratch in a matter of days, is searching for pay dirt in biodiversity-rich marine environments around the world," it reads. While Venter might have promised not to patent the raw microbes he found, the environmentalists’ argument went, he or someone else could genetically modify them, then claim patents on the engineered life-forms. Whatever he was doing, the ETC Group saw it as an immediate international concern. The release also cited Accién Ecolégica, which accused Venter of pirating Ecuador’s resources, because his permits to export samples from the Galépagos were not properly authorized. The day after the near-disaster with the alternator pulley, Venter was immediately notified by Rockville of a fax from the French Ministry of Foreign Affairs politely informing him that his application to conduct research in French Polynesia was denied. The ministry understood that the Sorcerer II ’s mission was to collect and study microorganisms that might prove helpful for health and industry, but France wished to protect its "patrimony" by restricting "extraction of these resources by foreign vessels." "It’s French water, so I guess they’re French microbes," Venter told me when he got the news. (The Sorcerer II ’s communications technology is high-end for boats twice its size, and a phone call from the middle of the Pacific to my home in New Jersey was no big deal.) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg He didn’t sound too worried. He had already enlisted the French ambassador to the US to lobby Paris on his behalf, and some top French scientists were writing letters of protest to the ministry. But when the Sorcerer II reached the French Polynesian island of Hiva Oa in the Marquesas archipelago, the port captain there informed Venter and Howard that their vessel was not allowed to leave the harbor. Impounding a private foreign vessel merely on suspicion is against international law, and Venter protested to the US State Department, which informed the ministry that it considered the act a violation of the honor of the United States. The Sorcerer II was allowed to proceed as a normal tourist vessel, but with a warning not to attempt to take any samples. After three weeks, a formal convention was drawn up and signed by Venter and the French Polynesian administrator overseeing research. The president of French Polynesia would also need to sign the document, but this was a mere formality. Sampling could begin at any moment. A few days later, I meet up with Venter at the InterContinental Beachcomber Resort in Papeete, the capital of French Polynesia. Decades of commercial and industrial growth have taken the paradise out of the Tahiti that Banks sailed into aboard the Endeavour back in 1769, but the InterContinental has trucked a little of it back in. The vibrant gardens beneath my balcony give way to an azure pool surrounded by a beach of pure, imported white sand, beyond which lies the lagoon. Half a mile out, the waves break on the reef. Nine miles away, the island of Moorea springs up from the sea, its jagged green peaks bundled in thunderclouds. After dinner, we take in the hotel’s Tahitian dance show. The women sway and wave their arms, and the men lunge about, slapping their arms and fluttering their knees and uttering sudden loud testosterone-fueled barks in unison. This is the otea - originally a war dance - and at times it seems the men are about to leap into their pirogues and invade Moorea. The next morning I notice that the bellhop loading our bags into the car looks familiar. He was one of the dancers. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg By this point, the Sorcerer II has been released from its political shackles on Hiva Oa and has proceeded westward to the Tuamotus. We fly out to meet the boat at Rangiroa. As we come in for a landing, I can see it anchored just inside the lagoon, sleek and white, decks shining in the sun. We are met at the airport by Howard and Juan Enriquez, a friend of Venter’s for about 10 years. In the early 1990s, Enriquez, whose mother is a Boston Cabot, was head of Mexico City’s Urban Development Corporation and deeply immersed in Mexican national politics. Since meeting Venter, he has become an enthusiastic teacher, writer, and promoter of genomic science and enterprise - a sort of freelance genomophile. He spent two years as a senior research fellow and founding director of the Life Science Project at Harvard Business School and is currently the CEO of Biotechonomy, a life sciences venture capital firm. He has been traveling with the expedition for more than a month. "I gave up a lot for this," Enriquez tells me as we motor out to the Sorcerer II in a dinghy. "I canceled a meeting with Bush and blew off a couple of foreign ministers. But what could be more exciting than sailing around the world, discovering thousands of new species?" We’re greeted on deck by Hoffman and first mate/second engineer Cyrus Foote, both barefoot and stripped to the waist. "We mooned the plane as you flew over," Hoffman tells Venter. "I’m not sorry I missed that," he replies and goes below to confer with Howard and change into his blue Speedo. I stay on deck and Enriquez gives his take on the permit issue. He’s philosophical about it, seeing it as part of the history of civilization. His theme is information. When humans invented cave art, they gained an enormous advantage over other animals because they were able to convey information about things that were not actually present. The next major step was the invention of Egyptian hieroglyphics, a way of standardizing information. Then came the much more efficient 26-letter alphabet, then, in the 1950s and ’60s, the two-letter alphabet of binary code. Now, he says, the four-letter code of the genetic script - A, C, T, and G - is driving another revolution. Through the application of genomics, an acre of land once used to produce food, feed, or fiber will be used to produce medicine out of plants, and microbes from the ocean will be recruited to make free energy. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg This puts a whole new spin on things. "The world is going genomic," Enriquez says. "If you do not perceive the possibilities in this shift, if you say no instead of yes , you will be left in the past. There will be whole societies who end up serving mai tais on the beach because they don’t understand this." Including the French, unless they get their act together and allow the Sorcerer II and projects like it to go forward. "What you’re watching right now with the permit issue is almost a mirror image of what happened in the digital age," he says. "With Minitel, France had the Internet wired to every house 10 years before anybody else. But instead of having an entrepreneurial system that said yes, they had a closed system that said no, you can’t do this, you must use French software, we’ll tax your stock options. And now Finland is beating the shit out of France in the digital revolution." While Enriquez goes to shore to arrange a diving expedition, Howard shows me around the boat, pointing out the changes that have been made to convert a luxury yacht into a research vessel that looks and feels pretty much like a luxury yacht. One of the most obvious adjustments is the lab bench set up in the library next to the galley; it includes a $35,000 fluorescent microscope hooked up to a 42-inch plasma videoscreen on the wall (also useful for watching movies). At 95 feet long, Howard says, the Sorcerer II is almost exactly the size of the Endeavour. But where Cook’s vessel was made of wood, hemp, and pine tar, Venter’s is fabricated from foam core, epoxy resin, and carbon fiber. The Sorcerer II ’s aerodynamic hull is essentially that of a modern racing yacht, while the Endeavour ’s was a "huge bulbous box with square ends," Howard says. Cook navigated by the stars and measured water depth with a knotted rope. Venter has bottom-imaging sonar and assorted other navigational aids, including digitized charts with GPS. We have 10 people on board, all of whom have a reasonable expectation of returning home alive. Of the 94 who left England aboard the Endeavour , some 40 died en route, including most of Banks’ retinue of artists, fellow naturalists, and servants. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Howard introduces me to the rest of the crew. Maybe it’s all the tanned flesh and tight stomachs, but they seem to radiate physical competence, moving fluidly about the deck as if they are genetically adapted to this microenvironment. Foote, the youngest at 26, has spent most of his life on the water, except for a stint as a graphic designer in Manhattan. A skilled sailor, he’s also an expert surfer and free diver. (On a recent dive, five sea urchin spines pierced his hand. He knew enough not to try to pull out the barbed spines, calmly pushing them through the other side of his hand instead.) Tess Sapia, the cook, has been working on boats in one capacity or another since leaving her native California; she has a captain’s license. Dill, the diving master, joined the Sorcerer II with Foote in Newport, Rhode Island, serving also as marine naturalist and deckhand. Stewardess and deckhand Wendy Ducker just joined the crew in the Galépagos. Years ago she worked as an advertising art director in San Francisco. But that was before her resort job in Zimbabwe, which involved skydiving, white-water rafting, safari walking, and bungee jumping off the Victoria Falls bridge. She then spent a couple of months backpacking through Brazil. She was learning to surf in the Dominican Republic when Howard contacted her about this job. "I wanted to do a circumnavigation and was looking for adventure," she tells me, as if she’d been sacking groceries up to that point. When I wake up the next day, Venter is in the main cabin reading an email from his office; Howard leans over his shoulder. Dill is setting the table for breakfast. "So the big news this morning is your friends the French are going to send a gunboat out to escort us," he tells me. (I’m not quite sure why he calls them my friends, but it could have to do with an incident in a bar on St. Barts that I’d rather forget.) "They want to make sure we sample where we said we would. We’re not supposed to tell the State Department about this. It might put a chill on French-American relations. Being as how they’re so cozy right now and all," Dill says. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg "They’d like to know if we’d like to invite an officer on board, too," Venter says. "How do you say ’fuck you’ in French?" Everybody gathers, and Sapia serves breakfast: bacon, fruit, and "freedom toast." I sneak a peek at the email. It’s a bit less dramatic than Venter made out - for instance, it says vessel , not gunboat - but the gist is about right. All that’s needed to begin sampling is the president’s signature - except that the signed document then has to be faxed to Paris for confirmation, and Easter weekend is approaching, with Monday being a French holiday in short, sampling probably won’t start until Wednesday, or even Thursday - when I’m scheduled to go home. The next morning, just off Rangiroa, I look around the edge of the lagoon we’re anchored in. I don’t see any gunboats. "Why don’t we just take some samples and throw them away if permission doesn’t come through?" I ask Howard. "Because if they caught us, they could impound the boat," he says. "Take the crew off. Cancel the expedition. This is serious stuff." Nobody else seems impatient, least of all Venter, and gradually the sun and heat and breathless beauty of the place begin to blunt my own sense of urgency. Enriquez organizes an excursion to a nearby reef so rich with sea life they call it the Aquarium. The next day we drift-snorkel from the ocean to the lagoon. Sharks and fish abound. Over here’s a manta ray. Down there, a Napoleon wrasse, like a great rainbow-colored bus. Foote circles below me for two minutes at a time on a single breath of air. "He’s a marine animal," says Dill. Later, Enriquez and I take the dinghy into the sleepy town to get some food coloring to dye eggs for an Easter egg hunt. The shops don’t have any food coloring, or any eggs for that matter. I read Banks’ journal from the Endeavour. At night we watch movies on the big plasma screen. There’s a card game. Venter considers himself a whiz at hearts, which naturally makes me want to take him down. I lose. The day after Easter we motor over to a secluded lagoon on the other side of the island, where we snorkel some more, and Venter walks naked on the beach. Enriquez whips up his special "coco locos," which pack a punch. That night, somebody paints my toenails purple. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg With all this lolling about, you’d think I’d at least be able to corner Venter. But a téte-é-téte - me with my notebook, him with his thoughts - keeps getting put off. Venter really wants to go diving. Sapia could use some help shucking coconuts for her marinade, and what have I done today to pitch in? Howard and Foote are going waveboarding, and, you know, this may be my last chance ever to try it. Three days disappear like magic. I try to explain to Venter that there’s a lot I don’t understand. How can you tell where one species ends and another begins? How do you even know what to call a species? What are you going to do with all the information you gather? What is the question being asked, other than, "Who’s fucking out there?" "You gotta do your homework, Jamie," Venter says, slipping into his wet suit for another dive. "It’s all in the Sargasso Sea paper." I retreat to my cabin with the copy I’ve brought along. It’s dense stuff. Searching for clarification on how species boundaries are determined, I find this: "From this set of well-sampled material, we were able to cluster and classify assemblies by organism; from the rare species in our sample, we use sequence similarity based methods together with computational gene finding to obtain both qualitative and quantitative estimates of genomic and functional diversity within this particular marine environment." This is one of the easier sentences in the text. I put the paper aside and slip back into reading Banks. "I found also this day," he wrote on March 3, 1769, "a large Sepia cuttle fish laying on the water just dead but so pulld to peices by the birds that his Species could not be determind; only this I know that of him was made one of the best soups I ever eat." Banks was writing more than 200 years ago, but I suspect that most of us are a lot closer to his understanding of what life means than to what Venter and his colleagues are writing about today. Part of the reason, of course, is the obscurity of the life they are exploring. Another reason is that this new approach to exploring biodiversity builds from the ground up, combining DNA sequences into genes, genes into inferred species, species into functional ecosystems. It’s no wonder that the language used to describe it is opaque to those of us accustomed to the birds and the bees and the flowers and the trees. Then there is the question of the sheer volume of data being generated. Banks found about 2,500 species, a graspable number. "Just between Halifax and the Galépagos, I wouldn’t be surprised if we find 10 million new genes," Venter tells me. "Maybe 20 million." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Always the big boast - but he’s probably right. Even Venter’s harshest critics have to acknowledge the astonishing amount of information, arguably more than anyone in history, he has generated about life. But how does all this information turn into knowledge ? What conceptual route leads from this tidal wave of data to an organizing idea, in the way that Darwin’s patient measuring of finch beaks and barnacle shapes gradually added up to the theory of natural selection? By the time the Sorcerer II circles the globe and the samples are sequenced and analyzed, Venter may indeed have "collected" 100,000 new species and tens of millions of new genes. Does he, or anyone else, possess the conceptual tools needed to pull some great truth out of such an ocean of information and vivify it like a bolt of lightning bringing Frankenstein’s monster to life? This question is bouncing around in my head when we all go out to dinner on shore for our last night on Rangiroa. Permission to sample still hasn’t come through, and after a week of hanging out in this frustrating paradise it’s time to head back to Tahiti and home. The 10 of us are sitting at a long table under the stars in a little restaurant Enriquez has found. Venter is at one end of the table, and I’m at the other. Halfway through the meal, he says maybe this is a good time for that interview. It’s not as if there haven’t been plenty of chances to sit down without everybody else around, times when I haven’t had a couple of glasses of wine. I tell him I haven’t brought my notebook. Somebody helpfully rips open a paper bag and hands it to me to write on. Now I’m even more annoyed. But I start writing. "The goal is to create the mother of all gene databases," Venter says. Let’s say you accomplish that goal, I reply. Is that enough for you personally? Banks set out to collect a lot of new species, and he succeeded. But he didn’t question the meaning of what he was collecting, the way Darwin did. Are we in an era now when just accumulating data is enough, or is there a question you’re trying to answer, an assumption you’re trying to test? Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg "There’s not one question, there are a million questions," he says. "I think what Jamie’s asking is whether our expedition is like Charles Darwin’s or more like Joseph Banks’," says Foote. Exactly. "Darwin didn’t walk around the Galépagos and come up with the theory of evolution," Venter says, a bit testily. "He was exploring, collecting, making observations. It wasn’t until he got back and went through the samples that he noticed the differences among them and put them in context." Would you be satisfied, I ask, if all you did with this expedition was increase the number of genes and species known? "If I could boost our understanding of the diversity of life by a couple orders of magnitude and be the first person to synthesize life? Yeah," Venter says. "I’d be happy, for a while." It’s not a very enlightening answer, but I suppose asking someone, "Are you the next Darwin?" isn’t a very fair question. We leave the next afternoon, Venter at the helm as we head out of the passage from the lagoon to the open ocean. It starts to rain, and the seas build until they’re washing over the bow. Given his headlong "sequence now, ask questions later" approach to science, you might expect he’d be at least a little reckless as a sailor, but he’s supremely careful, monitoring the tension on every line, his eyes moving calmly from the sails and the gauges to the crew moving about the deck, watchful most of all for their safety. Once clear of the islands, we take watches through the night while the autopilot steers the boat toward Tahiti. With the roll and pitch of the boat, sleeping is impossible. I stumble up on deck early the next morning - "No standing upon legs without assistance of hands," Banks wrote in his journal on a day with swells like this. Venter is sitting alone in the cockpit, one hand on the helm, the other around a mug of coffee. "We’ve got a few minutes before breakfast," he says casually. "Why don’t we continue that conversation from the other night?" I’d rather talk when I’m not holding on to the table to keep from falling over, but Tahiti looms off the bow, and I may not get another chance. It turns out that behind his glibness, Venter has actually thought a great deal about what might be called the data overload problem. He acknowledges that neither he nor anyone else yet knows what to make of the millions of gene sequences left in the Sorcerer II ’s wake. "How the hell can anyone work out the function of that many genes?" he says. "There aren’t enough biologists in the world, even if they work full-time on the problem for the rest of their lives." Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Still, he says, just appreciating the true extent of the diversity of life on Earth is a major step, even if we have yet to understand which genes belong to which species and what role those genes play in the microbes’ lives. Venter uses astronomy as an analogy. Galileo could peer into a telescope and make inferences about the nature of the universe based on the motions of the stars and planets he observed. But it wasn’t until we understood the true immensity of space and could measure it against the speed of light that we could calculate back in time to the origins of the universe. With whole galaxies of genes to compare, Venter says, perhaps we’ll similarly be able to work back to understanding the origins of life. "Darwin was limited by what he could see with only his eyes, and look what he was able to accomplish," he says. "We want to use the minimal unit of the gene to look at evolution instead. People have been doing this with a dozen genes. We’ll have 10,000." In the meantime, he imagines creating a Whole Earth Gene Catalog , complete with descriptions of every gene’s function. If you want to find the role of 100,000 genes, Venter says, the trick is to find a way of doing 100,000 experiments at once. All you would need that’s not already available is a synthetic genome, a sort of all-purpose template onto which you could attach any gene you wished, like inserting a blade onto a handle. You could then test the resulting concoction to see if it performed a specific vital task, such as metabolizing sugar or transporting energy. Using existing robotic technologies, you could do thousands of such experiments at once, in much the same way that a combinatorial chemist tests thousands of chemical compounds simultaneously to see if they have the desired effect on a target molecule. Most will not. But the ones that do can be investigated further. "I call it combinatorial genomics," Venter tells me. "It’s one of my better ideas if it works. In fact, it’s one of my better ideas if it doesn’t work." Whether it works depends, of course, on Venter’s ability to construct a functioning synthetic genome. I ask how that project is coming along. The smallest genome known, that of the infectious bacterium Mycoplasma genitalium , is 100 times the size of the synthetic virus Venter’s team created. He acknowledges that the group is still a long way from being able to create a genome that big, much less getting it to function in a cell. So what they’re working on first is an artificial genome intermediate in size, between a virus and a bacterium. If they succeed, their creation will be unlike anything engineered in a lab. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg "Would you call this thing alive?" I ask. "It’s just a genome," he says. "But yeah, eventually we’ll put it in a cellular context. We’re going public with this by the end of the year. You’ll like it when you hear it." With Venter, there must always be something new swelling on the horizon. Young Joseph Banks was content just to describe the new varieties of life he collected on his voyage. For him, this was a survey of God’s creation. Aboard the Beagle a half century later, Darwin was already questioning how the species he collected came to be. His ultimate answer wrested the helm from God and put it in the hands of natural processes instead. Now we’re sailing into a new evolutionary time, when we will have at least a finger on the tiller. Venter is hardly the only scientist leading us there, but he alone is taking the measure of life’s true diversity and dreaming up new life-forms at the same time. It’s not surprising that a lot of people, such as the activists who challenged him in the Galépagos, think he’s moving too fast, too heedlessly, into the future. But we can’t go backward. And nothing can be discovered by standing still. Venter’s team takes samples from ecosystems around the world and sends them to his gene-sequencing HQ at the Institute for Biological Energy Alternatives in Rockville, Maryland. Here’s the way the microbes are snagged, bagged, and tagged. 1. Sampling Every 200 miles, Sorcerer II ’s crew pumps 53 gallons of seawater on board, from a depth of about 5 feet. The water is strained through a series of three increasingly fine paper filters. The filters are sealed, labeled, frozen, and periodically airlifted to Rockville for analysis. 2. Shotgunning Back in the US, the filter papers are cut up and chemically treated to strip away all but the organisms’ DNA. This solution is then "shotgunned" - forced through a pinhole nozzle under high pressure - to break the long strands of DNA into millions of fragments. 3. Tagging The fragments of DNA are copied, broken into smaller pieces, and tagged with fluorescent dyes corresponding to the four bases: A, C, T, and G. An electrical charge carries the pieces through capillaries - tubes about the width of a human hair. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg 4. Sequencing As they move through the capillaries, DNA pieces arrange themselves by length. A laser then scans the ends of each tagged piece, creating rough sequences called "reads." 5. Assembling and Classifying Computer algorithms assemble longer DNA sequences by joining segments where there are overlapping stretches of code. The number of species can be estimated by comparing the DNA in the sample to known species. Classification into species can be determined by similarity among samples. 6. Annotating Data specialists "blast" stretches of DNA against databases of known genes - comparing them base letter by letter. If a novel gene has a sequence similar to a known gene, they are assumed to have similar functions. James Shreeve ([email protected]) is the author of The Genome War: How Craig Venter Tried to Capture the Code of Life and Save the World. credit illustration by Kenn Brown Imagine if our entire understanding of biology was based on a visit to the zoo. Thatés where weéve been in microbiology.-molecular biologist and phylogenetic researcher Norman Pace credit Ian White Craig Venter credit Courtesy J. Craig Venter Venter (far left) and two scientists from the Smithsonian Tropical Research Institute sample soil on Barro Colorado, an island at the mouth of the Panama Canal. credit Courtesy J. Craig Venter Jeff Hoffman (near left), aka Science Boy, brings a 13-gallon carboy aboard the Sorcerer II with two guides. The sample comes from a flamingo pond on Floreana Island in the Galépagos. credit Courtesy J. Craig Venter Shipés captain Charlie Howard (foreground), an electrical engineer in his previous life, looks on as the crew takes a sample from the open sea. credit Courtesy J. Craig Venter Seawater is triple-filtered in the aft cockpit. In the Sargasso Sea alone, Venterés team discovered at least 1,800 new species and more than 1.2 million new genes. 100 million species or bust: Venterés yacht, the Sorcerer II, is on a two-year, 25,000-mile microbe-collecting journey inspired by two earlier scientist-explorers: Joseph Banks on HMS Endeavour from 1768 to 1771, and Charles Darwin on HMS Beagle from 1831 to 1836. credit Stephen Rountree 1. Sampling: Every 200 miles, Sorcerer IIés crew pumps 53 gallons of seawater on board, from a depth of about 5 feet. The water is strained through a series of three increasingly fine paper filters. The filters are sealed, labeled, frozen, and periodically airlifted to Rockville for analysis. credit Stephen Rountree 2. Shotgunning: Back in the US, the filter papers are cut up and chemically treated to strip away all but the organismsé DNA. This solution is then-shotgunnedé-forced through a pinhole nozzle under high pressure-to break the long strands of DNA into millions of fragments. credit Stephen Rountree 3. Tagging: The fragments of DNA are copied, broken into smaller pieces, and tagged with fluorescent dyes corresponding to the four bases: A, C, T, and G. An electrical charge carries the pieces through capillaries-tubes about the width of a human hair. credit Stephen Rountree 4. Sequencing: As they move through the capillaries, DNA pieces arrange themselves by length. A laser then scans the ends of each tagged piece, creating rough sequences called-reads.é credit Stephen Rountree 5. Assembling and classifying: Computer algorithms assemble longer DNA sequences by joining segments where there are overlapping stretches of code. The number of species can be estimated by comparing the DNA in the sample to known species. Classification into species can be determined by similarity among samples. credit Stephen Rountree 6. Annotating: Data specialists-blasté stretches of DNA against databases of known genes-comparing them base letter by letter. If a novel gene has a sequence similar to a known gene, they are assumed to have similar functions. Feature: Craig Venter’s Epic Voyage Plus: How to Hunt Microbes Topics magazine-12.08 Brent M. Foster Erica Kasper Swapna Krishna Phoebe Weston Will Knight Ramin Skibba Ramin Skibba Emily Mullin Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"The Amazon S3 Outage Is What Happens When One Site Hosts Too Much of the Internet | WIRED"

"https://www.wired.com/2017/02/happens-one-site-hosts-entire-internet"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Klint Finley Business The Amazon S3 Outage Is What Happens When One Site Hosts Too Much of the Internet Getty Images Save this story Save Save this story Save If you've been having trouble using some of your favorite apps today, you're not alone. Users have reported trouble with sites and apps like Medium, Slack, and Trello. The problems seem to stem from trouble with Amazon's cloud storage service S3, which Amazon confirmed is experiencing "high error rates," particularly on the East Coast. Several other Amazon services appear to be having problems as well, but countless sites rely on S3 to host images and other files. Even Amazon's site itself relies on S3, leading to some baffling updates from the company. The outages bring to mind the attack on an internet company called Dyn last October that brought much of the web to its knees. Technologically, the S3 outage doesn't bear much resemblance to the Dyn incident, but the effect is similar: So many sites and apps are down that it feels almost like the internet itself is malfunctioning. That flies right in the face of the promise of the internet. Corporate consolidation in tech has implications for competition—but it also affects the resilience of the internet itself. Although it's not true that the internet was designed to withstand a nuclear attack, the fact that there's no central authority in charge of the network makes it, in theory, resilient to attacks on a single company or computer. But as the Amazon outage and the attack on Dyn prove, the internet is actually pretty brittle. The "winner takes all" dynamic of the tech industry concentrates more and more power into fewer and fewer companies. That consolidation has implications for competition but also affects the resilience of the internet itself. So many people rely on Gmail that when the service goes down, it's as if email itself has gone offline, even though countless other email providers exist. Facebook is practically synonymous with the internet for many people all over the world. Dyn isn't as well known as Amazon or Facebook. But its internet address service plays a central role in helping web browsers translate an address like "facebook.com" into a string of numbers that a computer can use to actually download a web page. When that service broke down under a DDOS attack, users were stuck unable to access much of the internet. The Epic Story of Dropbox’s Exodus From the Amazon Cloud Empire Oracle Just Bought Dyn, the Company That Brought Down the Internet Amazon’s Snowmobile Is Actually a Truck Hauling A Huge Hard Drive Amazon plays its own outsized role. Amazon won't say exactly how big its cloud is, but in 2012 one analyst estimated that Amazon hosted around 1 percent of the entire web. It has only grown since then, leading to speculation the cloud could some day overtake Amazon's retail business. The S3 storage service alone hosts about 1.6 times more data than its major competitors combined, according to the analyst firm Gartner. Even many sites not fully hosted by Amazon take advantage of its Cloudfront service, which speeds up websites by distributing their data across the country. According to the firm Datanyze , Cloudfront is by far the most widely used service of its kind. Meanwhile, Google and Microsoft—two other giants—have emerged as Amazon's major cloud competitors. Amazon's cloud itself relies on the decentralization of the internet. It has servers all over the world, though customers generally pick which regions to host their data. Even within a region, Amazon has multiple data centers in case one goes offline. But Amazon occasionally runs into problems that knock out services for an entire region. When that happens in the eastern region, its most popular, it tends to take down large swaths of the net, which may be what happened today. Some of the web's founding thinkers have been working alongside younger hackers to try to make the internet more truly a decentralized utopia. In the meantime the tech giants have only gotten bigger, pulling ever-more of the internet into their orbit. Until the web breaks free from that gravitational pull, expect more internet outages. Update at 5:30pm ET on 2/28/2017: Amazon says the problem was resolved at around 5:10pm ET today. The problem lasted for at least four hours. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Contributor X Topics Amazon Cloud Computing The Web Gregory Barber Vittoria Elliott Paresh Dave Vittoria Elliott Will Knight Kari McMahon Will Knight Will Bedingfield Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"The Inventors of the Internet Are Trying to Build a Truly Permanent Web | WIRED"

"https://www.wired.com/2016/06/inventors-internet-trying-build-truly-permanent-web"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Klint Finley Business The Inventors of the Internet Are Trying to Build a Truly Permanent Web Vint Cerf April Greer/The Washington Post/Getty Images Save this story Save Save this story Save If you wanted to write a history of the Internet, one of the first things you would do is dig into the email archives of Vint Cerf. In 1973, he co-created the protocols that Internet servers use to communicate with each other without the need for any kind of centralized authority or control. He has spent the decades since shaping the Internet's development, most recently as Google's "chief Internet evangelist." Thankfully, Cerf says he has archived about 40 years of old email—a first-hand history of the Internet stretching back almost as far as the Internet itself. But you'd also have a pretty big problem: a whole lot of that email you just wouldn't be able to open. The programs Cerf used to write those emails, and the formats in which they're stored, just don't work on any current computer you'd likely be using to try to read them. As fragile as paper is, written documents and records have long provided historians with a wealth of insight about that past that often helps shape the present. And they don't need any special technology to read them. Cerf himself points to historian Doris Kearns Goodwin's 2005 bestseller Team of Rivals , which she based on the diary entries and letters of Abraham Lincoln and his cabinet members. The book influenced how President Obama shaped his own cabinet and became the basis for the Steven Spielberg film Lincoln. In short, old records are important. But as Cerf's own email obsolescence shows, digital communications quickly become unreadable. Don't believe it? What would you do right now if you wanted to read something stored on a floppy disk? On a Zip drive? In the same way, the web browsers of the future might not be able to open today's webpages and images--if future historians are lucky enough to have copies of today's websites at all. Says Cerf, "I'm concerned about a coming digital dark ages." That's why he and some of his fellow inventors of the Internet are joining with a new generation of hackers, archivists, and activists to radically reinvent core technologies that underpin the web. Yes, they want to make the web more secure. They want to make it less vulnerable to censorship. But they also want to make it more resilient to the sands of time. Today, much of the responsibility for preserving the web's history rests on The Internet Archive. The non-profit's Wayback Machine crawls the web perpetually, taking snapshots that let you, say, go back and see how WIRED looked in 1997. But the Wayback Machine has to know about a site before it can index it, and it only grabs sites periodically. Based on the Internet Archive's own findings, the average webpage only lasts about 100 days. In order to preserve a site, the Wayback Machine has to spot it in that brief window before it disappears. Making the Web Just a Second Faster Would Be a Big Deal I Turned Off JavaScript for a Whole Week and It Was Glorious The Average Webpage Is Now the Size of the Original Doom What's more, the Wayback Machine is a centralized silo of information—an irony that's not lost on the inventors of the Internet. If it runs out of money, it could go dark. And because the archives originate from just one web address, it's relatively easy for censors, such as those in China, to block users from accessing the site entirely. The Archive Team--an unrelated organization--is leading an effort to create a more decentralized backup on the Internet Archive. But if Internet Archive founder Brewster Kahle, Cerf, and their allies who recently came together at what they called the Decentralized Web Summit have their way, the world will one day have a web that archives itself and backs itself up automatically. Some pieces of this new web already exist. Interplanetary File System , or IPFS, is an open source project that taps into ideas pioneered by the decentralized digital currency Bitcoin and the peer-to-peer file sharing system BitTorrent. Sites opt in to IPFS, and the protocol distributes files among participating users. If the original web server goes down, the site will live on thanks to the backups running on other people's computers. What's more, these distributed archives will let people browse previous versions of the site, much the way you can browse old edits in Wikipedia or old versions of websites in the Wayback Machine. "We are giving digital information print-like quality," says IPFS founder Juan Benet. "If I print a piece of paper and physically hand it to you, you have it, you can physically archive it and use it in the future." And you can share that copy with someone else. What would you do right now if you wanted to read something stored on a floppy disk? On a Zip drive? Right now IPFS is still just a tool the most committed: you need to have IPFS's software installed on your computer to take part. But Benet says the team has already built a version of the software in JavaScript that can run in your browser without the need to install any new software at all. If it winds up on everyone's browsers, the idea goes, then everyone can help back up the web. Unlike the early web, the web of today isn't just a collection of static HTML files. It's a rich network of interconnected applications like Facebook and Twitter and Slack that are constantly changing. A truly decentralized web will need ways not just to back up pages but applications and data as well. That's where things get really tricky--just ask the team behind the decentralized crowdfunding system DAO which was just hacked to the tune of $50 million last week. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg The IPFS team is already hard at work on a feature that would allow a web app to keep trucking along even if the original server disappears, and it's already built a chat app to demonstrate the concept. Meanwhile, several other projects-- such as Ethereum, ZeroNet and the SAFE Network —aspire to create ways to build websites and applications that don't depend on a single server or company to keep running. And now, thanks in large part to the Summit, many of them are working to make their systems cross-compatible. Even if the web winds up in a new, better of digital archive, plenty of problems still remain. Today's web isn't just a collection of static HTML files; it's dynamic apps like Facebook, Twitter, and Slack. The operating systems and hardware of the future might not be able to read or run any of those. The same holds true for videos, photos, maybe even text. Many efforts are afoot to right those weaknesses. But why bother? 'We are giving digital information print-like quality.' After all, if anyone really cares about a specific file or site, can't they just transfer the files to newer media and convert the most important files to newer formats? The problem with that line of thinking, Cerf says, is that people often don't always know what's important right away. For example, sailors have kept meticulous records of weather and temperatures in locations all over the world for centuries. That sort of information probably seemed useless, the sort of thing geeks of old preserved out of a vague sense of historical purpose. But guess what: climate scientists may find all that weather data very valuable. (The Old Weather project is now hard at work digitizing those old ship logs.) Still: some websites just shouldn't last forever. Does anyone in the future really need to see old drunken college photos or inadvisable Facebook rants? Meanwhile, activists and law enforcement are trying to stop web publishers from posting nude photos of people without their consent--a practice known as "revenge porn." These same preservation tools that could make it harder for governments to censor the web could make it harder for people to scrub content from the web that shouldn't be there anyway. People like Snapchat for a reason. 'The walled garden is very sweet. But the jungle outside is always more appealing.' Cerf suggests possible technical workarounds to this problem. Web publishers, for example, could specify whether other people can automatically archive their sites. Bennet says the IPFS team has been considering a feature that would enable the original publisher of a page to un-publish it by sending a beacon to all other servers hosting a page asking for its removal. The IPFS servers could also host blacklists to remove copyrighted material. Still, those blacklists themselves become a reminder of the things we're trying to forget. But the biggest problem facing the decentralized web is probably neither technical or legal. And that's getting people to care in the first place. At a time when people spend most of their time in closed-off platforms like Facebook and Snapchat, so much of what humans digitally produce stays locked up anyway. Bringing people back to the open web is going to mean creating user experiences that are fun enough and easy enough to persuade people to venture out of the confines of today's app-centric Internet. But Tim Berners-Lee, the creator of the original web, isn't worried. After all, the open web already beat out walled gardens with names like America Online, Compuserve, and Prodigy. "You can make the walled garden very very sweet," Berners-Lee said at the summit. "But the jungle outside is always more appealing in the long term." Contributor X Andy Greenberg Will Knight Reece Rogers Will Knight Peter Guest Peter Guest Steven Levy K.G. Orphanides Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Great Wall of Facebook: The Social Network's Plan to Dominate the Internet — and Keep Google Out | WIRED"

"https://www.wired.com/techbiz/it/magazine/17-07/ff_facebookwall"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons WIRED Staff Business Great Wall of Facebook: The Social Network's Plan to Dominate the Internet — and Keep Google Out Save this story Save Save this story Save Instead of working together to reach the promised land of online brand advertising, Facebook and Google are racing to see who can get there first. * Illustration: Brent Humphreys * Larry Page should have been in a good mood. It was the fall of 2007, and Google's cofounder was in the middle of a five-day tour of his company's European operations in Zurich, London, Oxford, and Dublin. The trip had been fun, a chance to get a ground-floor look at Google's ever-expanding empire. But this week had been particularly exciting, for reasons that had nothing to do with Europe; Google was planning a major investment in Facebook, the hottest new company in Silicon Valley. Originally Google had considered acquiring Facebook—a prospect that held no interest for Facebook's executives—but an investment was another enticing option, aligning the Internet's two most important companies. Facebook was more than a fast-growing social network. It was, potentially, an enormous source of personal data. Internet users behaved differently on Facebook than anywhere else online: They used their real names, connected with their real friends, linked to their real email addresses, and shared their real thoughts, tastes, and news. Google, on the other hand, knew relatively little about most of its users other than their search histories and some browsing activity. But now, as Page took his seat on the Google jet for the two-hour flight from Zurich to London, something appeared to be wrong. He looked annoyed, one of his fellow passengers recalls. It turned out that he had just received word that the deal was off. Microsoft, Google's sworn enemy, would be making the investment instead— $240 million for a 1.6 percent stake in the company, meaning that Redmond valued Facebook at an astonishing $15 billion. As the 767 took off, Page tersely but calmly shared the news with the others on the plane and answered their questions for about 15 minutes. "Larry was clearly, clearly unhappy about it," the passenger says. Page soon got over it, but Facebook's rejection was still a blow to Google; it had never lost a deal this big and this publicly. But according to Facebookers involved in the transaction, Mountain View never had much of a chance—all things being equal, Microsoft was always the favored partner. Google's bid was used primarily as a stalking horse, a tool to amp up the bidding. Facebook executives weren't leaping at the chance to join with Google; they preferred to conquer it. "We never liked those guys," says one former Facebook engineer. "We all had that audacity, 'Anything Google does, we can do better.' No one talked about MySpace or the other social networks. We just talked about Google." Today, the Google-Facebook rivalry isn't just going strong, it has evolved into a full-blown battle over the future of the Internet—its structure, design, and utility. For the last decade or so, the Web has been defined by Google's algorithms—rigorous and efficient equations that parse practically every byte of online activity to build a dispassionate atlas of the online world. Facebook CEO Mark Zuckerberg envisions a more personalized, humanized Web, where our network of friends, colleagues, peers, and family is our primary source of information, just as it is offline. In Zuckerberg's vision, users will query this "social graph" to find a doctor, the best camera, or someone to hire—rather than tapping the cold mathematics of a Google search. It is a complete rethinking of how we navigate the online world, one that places Facebook right at the center. In other words, right where Google is now. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg All this brave talk might seem easy to dismiss as the swagger of an arrogant upstart. After all, being Google is a little like being heavyweight champion of the world—everyone wants a shot at your title. But over the past year, Facebook has gone from glass-jawed flyweight to legitimate contender. It has become one of the most popular online destinations. More than 200 million people —about one-fifth of all Internet users—have Facebook accounts. They spend an average of 20 minutes on the site every day. Facebook has stolen several well-known Google employees, from COO Sheryl Sandburg to chef Josef Desimone ; at least 9 percent of its staff used to work for the search giant. And since last December, Facebook has launched a series of ambitious initiatives, designed to make the social graph an even more integral part of a user's online experience. Even some Googlers concede that Facebook represents a growing threat. "Eventually, we are going to collide," one executive says. It is remarkable that the most powerful company on the Web would feel threatened by one that has yet to turn a profit. (Last year, one insider estimates, Facebook burned through $75 million plus the $275 million in revenue it brought in; Google made $4.2 billion on an astounding $15.8 billion in net revenue.) And even Facebook executives concede that Google has secured an insurmountable lead in search advertising—those little text ads that pop up next to search results—which accounts for about 90 percent of Google's net revenue. But they say they are going after an even bigger market: the expensive branding campaigns that so far have barely ventured online. Once, Google hoped an alliance with Facebook would help attract those huge ad budgets. Now, instead of working together to reach the promised land of online brand advertising, Facebook and Google are racing to see who can get there first. Like typical trash-talking youngsters, Facebook sources argue that their competition is old and out of touch. "Google is not representative of the future of technology in any way," one Facebook veteran says. "Facebook is an advanced communications network enabling myriad communication forms. It almost doesn't make sense to compare them." FACEBOOK'S 4-Step Plan for Online Domination Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Mark Zuckerberg has never thought of his company as a mere social network. He and his team are in the middle of a multiyear campaign to change how the Web is organized—with Facebook at the center. Here's how they hope to pull it off. 1. Build critical mass. In the eight months ending in April, Facebook has doubled in size to 200 million members, who contribute 4 billion pieces of info, 850 million photos, and 8 million videos every month. The result: a second Internet, one that includes users' most personal data and resides entirely on Facebook's servers. 2. Redefine search. Facebook thinks its members will turn to their friends—rather than Google's algorithms—to navigate the Web. It already drives an eyebrow-raising amount of traffic to outside sites, and that will only increase once Facebook Search allows users to easily explore one another's feeds. 3. Colonize the Web. Thanks to a pair of new initiatives—dubbed Facebook Connect and Open Stream—users don't have to log in to Facebook to communicate with their friends. Now they can access their network from any of 10,000 partner sites or apps, contributing even more valuable data to Facebook's servers every time they do it. __4. Sell targeted ads, everywhere. __ Facebook hopes to one day sell advertising across all of its partner sites and apps, not just on its own site. The company will be able to draw on the immense volume of personal data it owns to create extremely targeted messages. The challenge: not freaking out its users in the process. To understand Facebook's challenge to Google, consider my friend and neighbor Wayne, a PhD in computer science from UC Berkeley and a veteran of many big-time programming jobs. I know a lot about him because we are friends. I know even more because we are Facebook friends. On his online profile, I not only find the standard personal-blog-type information—his birthday, address, résumé, and pictures of his wife, son, and step-kids. I also discover that he likes to make beer, that he had dinner at one of my favorite restaurants last week, and that he likes to watch cartoons. Indeed, he has posted something about his life almost every day for the past two months—wondering whether his son's Little League game will get rained out, asking his friends what the impeller in his central heating unit does. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg But if I type Wayne's name into Google, I learn very little. I am directed to an old personal Web site, with links that have almost all expired, and a collection of computer-science papers he has written over the years. That's about it. Hardly any of Wayne's Facebook information turns up on a Google search, because all of it, along with similar details about the other 200 million Facebook users, exists on the social network's roughly 40,000 servers. Together, this data comprises a mammoth amount of activity, almost a second Internet. By Facebook's estimates, every month users share 4 billion pieces of information—news stories, status updates, birthday wishes, and so on. They also upload 850 million photos and 8 million videos. But anyone wanting to access that stuff must go through Facebook; the social network treats it all as proprietary data, largely shielding it from Google's crawlers. Except for the mostly cursory information that users choose to make public, what happens on Facebook's servers stays on Facebook's servers. That represents a massive and fast-growing blind spot for Google, whose long-stated goal is to "organize the world's information." Facebook isn't just kneecapping Google's search engine; it is also competing with it. Facebook encourages its 200 million members to use Microsoft's search engine, which it installed on its homepage late last year as part of the deal struck between the two companies. At press time, it was also planning to launch Facebook Search, allowing users to scour one another's feeds. Want to see what some anonymous schmuck thought about the Battlestar Galactica finale? Check out Google. Want to see what your friends had to say? Try Facebook Search. And it will not only be for searching within Facebook. Because Facebook friends post links to outside sites, you will be able to use it as a gateway to the Web—making it a direct threat to Google. Why settle for articles about the Chrysler bankruptcy that the Google News algorithm recommends when you can read what your friends suggest? Already, Facebook is starting to horn in on Google's role as the predominant driver of Web traffic. According to Hitwise, Facebook in recent months has sent more traffic than Google to Evite, video site Tagged.com, and gossip mills Perez Hilton.com and Dlisted. That trend should only grow with the advent of Facebook Search. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg These are just the latest moves in an ambitious campaign to make the social graph an integral, ubiquitous element of life online. In December, Facebook launched Connect , a network of more than 10,000 independent sites that lets users access their Facebook relationships without logging in to Facebook .com. Go to Digg, for instance, and see which stories friends recommended. Head to Citysearch and see which restaurants they have reviewed. Visit TechCrunch, Gawker, or the Huffington Post and read comments they have left. On Inauguration Day, millions of users logged in to CNN.com with their Facebook ID and discussed the proceedings with their friends in real time. In April, Facebook announced its Open Stream API , allowing developers to create mashups using Facebook's constantly updated stream of user activity. Previously, users who wanted to read their friends' News Feeds had to go to the Facebook site. Now developers can export that information to any site—or to freestanding applications, much as Twitter desktop clients do for Tweets. Connect and Open Stream don't just allow users to access their Facebook networks from anywhere online. They also help realize Facebook's longtime vision of giving users a unique, Web-wide online profile. By linking Web activity to Facebook accounts, they begin to replace the largely anonymous "no one knows you're a dog" version of online identity with one in which every action is tied to who users really are. To hear Facebook executives tell it, this will make online interactions more meaningful and more personal. Imagine, for example, if online comments were written by people using their real names rather than by anonymous trolls. "Up until now all the advancements in technology have said information and data are the most important thing," says Dave Morin , Facebook's senior platform manager. "The most important thing to us is that there is a person sitting behind that keyboard. We think the Internet is about people." But you don't build a competitor to Google with people alone. You need data. And Connect and Open Stream are intended to make Facebook a much more powerful force for collecting user information. Any time someone logs in to a site that uses Connect or Open Stream, they give Facebook the right to keep track of any activity that happens there—potentially contributing tons more personal data to Facebook's servers. Facebook Connect and Open Stream are also designed to make each user's friend network, which belongs to Facebook, even more valuable and crucial to the Web experience. Together, they aim to put Facebook users' social networks at the center of all they do online. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Mark Zuckerberg is notoriously cocky, even by the standards of Silicon Valley. Two years ago, he walked away from a reported nearly $1 billion offer from Yahoo for his company. He could have sold to Google or Microsoft for a lot more. His business cards once famously read: i'm ceo ... bitch . And he has described Facebook as a once-in-a-century communications revolution, implying that he is right up there with Gutenberg and Marconi. Still, you'd think he might play it a little cool when discussing Google, not wanting to antagonize the most powerful company on the Internet. But Zuckerberg doesn't pull any punches, describing Google as "a top-down way" of organizing the Web that results in an impersonal experience that stifles online activity. "You have a bunch of machines and algorithms going out and crawling the Web and bringing information back," he says. "That only gets stuff that is publicly available to everyone. And it doesn't give people the control that they need to be really comfortable." Instead, he says, Internet users will share more data when they are allowed to decide which information they make public and which they keep private. "No one wants to live in a surveillance society," Zuckerberg adds, "which, if you take that to its extreme, could be where Google is going." It's ironic to hear Zuckerberg paint Google as Big Brother. After all, many observers worry that Facebook itself has grown too controlling. Unlike Google, Facebook makes it difficult for users to export their contacts, mail, photos, and videos—a practice Web 2.0 evangelists say is a sign that the company values its proprietary data more than its users' experience. In November 2007, Facebook launched Beacon , a ham-fisted attempt to inject advertising into News Feeds. Users felt violated; after a month of protest, Zuckerberg publicly apologized and effectively shut Beacon down. Then, in February 2009, Facebook quietly changed its terms of service, appearing to give itself perpetual ownership of anything posted on the site, even after members closed their accounts. Users complained so vociferously—millions joined Facebook groups and signed online petitions protesting the change—that the company was forced to backtrack. The event left many people fearful of the amount of personal information they were ceding to a private, profit-hungry enterprise. "Do You Own Facebook?" a New York magazine cover story asked warily in April. "Or Does Facebook Own You?" (Facebook executives say that the company was merely updating the terms of service to match those of other sites and that there was no nefarious intent. They reinstated a version of the amendment after subjecting it to a vote of Facebook members.) Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Facebook aims to put its users' social networks at the center of all they do online. Photo: Brent Humphreys The drumbeat of controversy surrounding Facebook illustrates the catch-22 the social network faces: It has a massive storehouse of user data, but every time it tries to capitalize on that information, its members freak out. This isn't an academic problem; the company's future depends on its ability to master the art of behavioral targeting—selling customized advertising based on user profiles. In theory, this should be an irresistible opportunity for marketers; Facebook's performance advertising program allows them to design and distribute an ad to as narrow an audience as they would like. (It has also developed a program to create ads that are designed to be spread virally.) But as the Beacon debacle showed, there is a fine line between "targeted and useful" and "creepy and stalkerish"—and so far, not enough advertisers have been willing to walk that line. In a way, Facebook's dilemma extends from its success. Users see the site as sanctified space, a place to engage in intimate conversations with friends—not to be laser-beamed by weirdly personal advertising. But with initiatives like Connect and Open Stream, Facebook can sell ads beyond its own site. Just as Google's AdSense program sells ads on any participating Web site, Connect and Open Stream will eventually push Facebook-brokered advertising to any member site or app. But unlike with AdSense, Facebook's ads could be exquisitely tailored to their targets. "No one out there has the data that we have," says COO Sandberg. That's where the big-budget brand advertisers come in. Google has courted them for four years, to no avail. That's because, while search ads are great at delivering advertising to users who are seeking specific products, they are less effective at creating demand for stuff users don't yet know they want. Google has tried everything to lure brand advertisers—from buying and selling radio ads to purchasing YouTube. And it is easy to see why it keeps trying. Today, global online brand advertising accounts for just $50 billion a year. Offline brand advertising, meanwhile, accounts for an estimated $500 billion. Google's desire to crack the brand-advertising conundrum is so intense, some company executives have even considered swallowing their pride and pursuing another deal with Facebook. But whether or not it ultimately friends the social network, Google has clearly been influenced by it. On December 4, the same day that Facebook Connect launched, Google unveiled its own version, Friend Connect , which allows Web sites to link to accounts on any of the major social networks—including MySpace, LinkedIn, Ning, Hi5, and Bebo. In March, four months after Facebook reportedly offered $500 million in a failed bid for Twitter, reports surfaced that Google was holding similar talks. (A Google insider confirms the discussions.) It is easy to see the appeal: Twitter is growing even faster than Facebook—doubling its membership in March—and would give Google access to the kind of personal information that fills Facebook News Feeds. And Google recently announced Wave , a Web communications platform that encourages Facebook-like sharing and conversations. The company even seems to have conceded Zuckerberg's point about its impersonal search results. In April, Google announced a plan to allow individuals to create detailed profiles that would show up whenever anyone searches for their name. If they opt for this service—a big if—users gain greater control over how they are portrayed online, which will give them the incentive to share with Google the kind of personal information they had previously shared only with Facebook. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Google has even shown a willingness to join Facebook in gingerly tapping the third rail of Internet marketing—behavioral targeting. The search giant has long assured its users that it would never use their personal information to deliver targeted advertising, relying instead on aggregate data or search activity that preserves anonymity. ("There is a line with users that you don't want to cross," Google CEO Eric Schmidt said in the wake of the Beacon controversy.) But in March, Google started its own behavioral targeting campaign—tracking users' browsing to deliver more-customized ads. Users have the option to either edit their profiles or opt out entirely. In September 2007, Gideon Yu was hired as Facebook's CFO. Before that, the 38-year-old had been CFO at YouTube, where he negotiated its acquisition by Google. He'd also put in four years as Yahoo's treasurer and was one of its top dealmakers. Facebook announced the hire with much fanfare. "I consider it kind of a coup that we were able to recruit him here," Zuckerberg told the Wall Street Journal. "He's just excellent." Nineteen months later, Yu was gone. It was a short tenure—not unprecedented for a private-company CFO. But Zuckerberg turned Yu's departure into a kerfuffle by publicly trashing him, saying that the job had simply outgrown him and that Facebook now needed a CFO with "substantial public company experience." To many, the performance was a stark reminder that the Facebook CEO, while undeniably ambitious and brilliant, was still just 24 years old. (He's 25 now.) Zuckerberg's youth has given Googlers some confidence. After all, even under the most sage and steady leadership, Facebook would be confronted with a difficult challenge: turning a massive user base into a sustainable business. (Just ask Friendster, MySpace, YouTube, and Twitter.) Through Google's own experience with YouTube, they have seen how expensive it can be to keep up with exploding user growth. They inked a disastrous $900 million partnership with MySpace in 2006, a failure that taught them how hard it is to make money from social networking. And privately, they don't think Facebook's staff has the brainpower to succeed where they have failed. "If they found a way to monetize all of a sudden, sure, that would be a problem," says one highly placed Google executive. "But they're not going to." Facebook's naysayers have a point. But before they get too complacent, they might remember another upstart that figured out a new way to organize the Internet. For five years, it worked on building its user base and perfecting its product, resisting pleas from venture capitalists to figure out how to make money. It was only after it had made itself an essential part of everyone's online life that its business path became clear—and it quickly grew to become one of the world's most powerful and wealthy companies. The name of that company, of course, was Google. Contributing editor Fred Vogelstein ( [email protected] ) wrote about Google in issue 17.02. Related Q&A: Interview with Facebook Founder and CEO Mark Zuckerberg Facebook, Google Go Persian, Helping Iran’s Activists Future of Social Media: The Walls Come Crumbling Down Topics IT magazine-17.07 Tech Biz Paresh Dave Reece Rogers Peter Guest Steven Levy Will Knight Paresh Dave Reece Rogers Deidre Olsen Facebook X Pinterest YouTube Instagram Tiktok More From WIRED Subscribe Newsletters Mattresses Reviews FAQ Wired Staff Coupons Black Friday Editorial Standards Archive Contact Advertise Contact Us Customer Care Jobs Press Center RSS Accessibility Help Condé Nast Store Do Not Sell My Personal Info © 2023 Condé Nast. All rights reserved. Use of this site constitutes acceptance of our User Agreement and Privacy Policy and Cookie Statement and Your California Privacy Rights. WIRED may earn a portion of sales from products that are purchased through our site as part of our Affiliate Partnerships with retailers. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Condé Nast. Ad Choices Select international site United States LargeChevron UK Italia Japón Czech Republic & Slovakia "

"Sharing & publication policy"

"https://openai.com/api/policies/sharing-publication"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Sharing & publication policy Updated November 14, 2022 Contents Social media, livestreaming, and demonstrations Content co-authored with the OpenAI API Research Social media, livestreaming, and demonstrations To mitigate the possible risks of AI-generated content, we have set the following policy on permitted sharing. Posting your own prompts or completions to social media is generally permissible, as is livestreaming your usage or demonstrating our products to groups of people. Please adhere to the following: Manually review each generation before sharing or while streaming. Attribute the content to your name or your company. Indicate that the content is AI-generated in a way no user could reasonably miss or misunderstand. Do not share content that violates our Content Policy or that may offend others. If taking audience requests for prompts, use good judgment; do not input prompts that might result in violations of our Content Policy. If you would like to ensure the OpenAI team is aware of a particular completion, you may email us or use the reporting tools within Playground. Recall that you are interacting with the raw model, which means we do not filter out biased or negative responses. (Also, you can read more about implementing our free Moderation endpoint here.) Content co-authored with the OpenAI API Creators who wish to publish their first-party written content (e.g., a book, compendium of short stories) created in part with the OpenAI API are permitted to do so under the following conditions: The published content is attributed to your name or company. The role of AI in formulating the content is clearly disclosed in a way that no reader could possibly miss, and that a typical reader would find sufficiently easy to understand. Topics of the content do not violate OpenAI’s Content Policy or Terms of Use , e.g., are not related to adult content, spam, hateful content, content that incites violence, or other uses that may cause social harm. We kindly ask that you refrain from sharing outputs that may offend others. For instance, one must detail in a Foreword or Introduction (or some place similar) the relative roles of drafting, editing, etc. People should not represent API-generated content as being wholly generated by a human or wholly generated by an AI, and it is a human who must take ultimate responsibility for the content being published. Here is some stock language you may use to describe your creative process, provided it is accurate: Research We believe it is important for the broader world to be able to evaluate our research and products, especially to understand and improve potential weaknesses and safety or bias problems in our models. Accordingly, we welcome research publications related to the OpenAI API. If you have any questions about research publications based on API access or would like to give us advanced notice of a publication (though not required), please email us at [email protected]. In some cases, we may want to highlight your work internally and/or externally. In others, such as publications that pertain to security or misuse of the API, we may want to take appropriate actions to protect our users. If you notice any safety or security issues with the API in the course of your research, we ask that you please submit these immediately through our Coordinated Vulnerability Disclosure Program. Researcher Access Program There are a number of research directions we are excited to explore with the OpenAI API. If you are interested in the opportunity for subsidized access, please provide us with details about your research use case on the Researcher Access Program application. In particular, we consider the following to be especially important directions, though you are free to craft your own direction: Alignment : How can we understand what objective, if any, a model is best understood as pursuing? How do we increase the extent to which that objective is aligned with human preferences, such as via prompt design or fine-tuning? Fairness and representation : How should performance criteria be established for fairness and representation in language models? How can language models be improved in order to effectively support the goals of fairness and representation in specific, deployed contexts? Interdisciplinary research : How can AI development draw on insights from other disciplines such as philosophy, cognitive science, and sociolinguistics? Interpretability and transparency : How do these models work, mechanistically? Can we identify what concepts they’re using, or extract latent knowledge from the model, make inferences about the training procedure, or predict surprising future behavior? Misuse potential : How can systems like the API be misused? What sorts of “red teaming” approaches can we develop to help us and other AI developers think about responsibly deploying technologies like this? Model exploration : Models like those served by the API have a variety of capabilities which we have yet to explore. We’re excited by investigations in many areas including model limitations, linguistic properties, commonsense reasoning, and potential uses for many other problems. Robustness : Generative models have uneven capability surfaces, with the potential for surprisingly strong and surprisingly weak areas of capability. How robust are large generative models to “natural” perturbations in the prompt, such as phrasing the same idea in different ways or with or without typos? Can we predict the kinds of domains and tasks for which large generative models are more likely to be robust (or not robust), and how does this relate to the training data? Are there techniques we can use to predict and mitigate worst-case behavior? How can robustness be measured in the context of few-shot learning (e.g., across variations in prompts)? Can we train models so that they satisfy safety properties with a very high level of reliability, even under adversarial inputs? Please note that due to a high volume of requests, it takes time for us to review these applications and not all research will be prioritized for subsidy. We will only be in touch if your application is selected for subsidy. Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Andrew Ng: How to be an innovator | MIT Technology Review"

"https://www.technologyreview.com/2023/09/12/1078367/andrew-ng-innovator-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Andrew Ng: How to be an innovator Tips for aspiring innovators on trying, failing, and the future of AI. By Andrew Ng archive page Nico Ortega This essay is part of MIT Technology Review’s 2023 Innovators Under 35 package. Meet this year’s honorees. Innovation is a powerful engine for uplifting society and fueling economic growth. Antibiotics, electric lights, refrigerators, airplanes, smartphones—we have these things because innovators created something that didn’t exist before. MIT Technology Review’s Innovators Under 35 list celebrates individuals who have accomplished a lot early in their careers and are likely to accomplish much more still. Having spent many years working on AI research and building AI products, I’m fortunate to have participated in a few innovations that made an impact, like using reinforcement learning to fly helicopter drones at Stanford, starting and leading Google Brain to drive large-scale deep learning, and creating online courses that led to the founding of Coursera. I’d like to share some thoughts about how to do it well, sidestep some of the pitfalls, and avoid building things that lead to serious harm along the way. AI is a dominant driver of innovation today As I have said before, I believe AI is the new electricity. Electricity revolutionized all industries and changed our way of life, and AI is doing the same. It’s reaching into every industry and discipline, and it’s yielding advances that help multitudes of people. AI—like electricity—is a general-­purpose technology. Many innovations, such as a medical treatment, space rocket, or battery design, are fit for one purpose. In contrast, AI is useful for generating art, serving web pages that are relevant to a search query, optimizing shipping routes to save fuel, helping cars avoid collisions, and much more. The advance of AI creates opportunities for everyone in all corners of the economy to explore whether or how it applies to their area. Thus, learning about AI creates disproportionately many opportunities to do something that no one else has ever done before. For instance, at AI Fund, a venture studio that I lead, I’ve been privileged to participate in projects that apply AI to maritime shipping , relationship coaching , talent management , education , and other areas. Because many AI technologies are new, their application to most domains has not yet been explored. In this way, knowing how to take advantage of AI gives you numerous opportunities to collaborate with others. Looking ahead, a few developments are especially exciting. Prompting: While ChatGPT has popularized the ability to prompt an AI model to write, say, an email or a poem, software developers are just beginning to understand that prompting enables them to build in minutes the types of powerful AI applications that used to take months. A massive wave of AI applications will be built this way. Vision transformers: Text trans­formers—language models based on the transformer neural network architecture, which was invented in 2017 by Google Brain and collaborators—have revolutionized writing. Vision transformers, which adapt transformers to computer vision tasks such as recognizing objects in images, were introduced in 2020 and quickly gained widespread attention. The buzz around vision transformers in the technical community today reminds me of the buzz around text transformers a couple of years before ChatGPT. A similar revolution is coming to image processing. Visual prompting, in which the prompt is an image rather than a string of text, will be part of this change. AI applications: The press has given a lot of attention to AI’s hardware and software infrastructure and developer tools. But this emerging AI infrastructure won’t succeed unless even more valuable AI businesses are built on top of it. So even though a lot of media attention is on the AI infrastructure layer, there will be even more growth in the AI application layer. These areas offer rich opportunities for innovators. Moreover, many of them are within reach of broadly tech-savvy people, not just people already in AI. Online courses, open-source software, software as a service, and online research papers give everyone tools to learn and start innovating. But even if these technologies aren’t yet within your grasp, many other paths to innovation are wide open. Be optimistic, but dare to fail That said, a lot of ideas that initially seem promising turn out to be duds. Duds are unavoidable if you take innovation seriously. Here are some projects of mine that you probably haven’t heard of, because they were duds: I spent a long time trying to get aircraft to fly autonomously in formation to save fuel (similar to birds that fly in a V formation). In hindsight, I executed poorly and should have worked with much larger aircraft. I tried to get a robot arm to unload dishwashers that held dishes of all different shapes and sizes. In hindsight, I was much too early. Deep-learning algorithms for perception and control weren’t good enough at the time. About 15 years ago, I thought that unsupervised learning (that is, enabling machine-learning models to learn from unlabeled data) was a promising approach. I mistimed this idea as well. It’s finally working, though, as the availability of data and computational power has grown. It was painful when these projects didn’t succeed, but the lessons I learned turned out to be instrumental for other projects that fared better. Through my failed attempt at V-shape flying, I learned to plan projects much better and front-load risks. The effort to unload dishwashers failed, but it led my team to build the Robot Operating System (ROS), which became a popular open-source framework that’s now in robots from self-driving cars to mechanical dogs. Even though my initial focus on unsupervised learning was a poor choice, the steps we took turned out to be critical in scaling up deep learning at Google Brain. Society has a deep interest in the fruits of innovation. And that is a good reason to approach innovation with optimism. Innovation has never been easy. When you do something new, there will be skeptics. In my younger days, I faced a lot of skepticism when starting most of the projects that ultimately proved to be successful. But this is not to say the skeptics are always wrong. I faced skepticism for most of the unsuccessful projects as well. As I became more experienced, I found that more and more people would agree with whatever I said, and that was even more worrying. I had to actively seek out people who would challenge me and tell me the truth. Luckily, these days I am surrounded by people who will tell me when they think I’m doing something dumb! While skepticism is healthy and even necessary, society has a deep interest in the fruits of innovation. And that is a good reason to approach innovation with optimism. I’d rather side with the optimist who wants to give it a shot and might fail than the pessimist who doubts what’s possible. Take responsibility for your work As we focus on AI as a driver of valuable innovation throughout society, social responsibility is more important than ever. People both inside and outside the field see a wide range of possible harms AI may cause. These include both short-term issues, such as bias and harmful applications of the technology, and long-term risks, such as concentration of power and potentially catastrophic applications. It’s important to have open and intellectually rigorous conversations about them. In that way, we can come to an agreement on what the real risks are and how to reduce them. Over the past millennium, successive waves of innovation have reduced infant mortality, improved nutrition, boosted literacy, raised standards of living worldwide, and fostered civil rights including protections for women, minorities, and other marginalized groups. Yet innovations have also contributed to climate change, spurred rising inequality, polarized society, and increased loneliness. Related Story Li’s research could prevent AI models from failing catastrophically when they encounter unfamiliar scenarios. Clearly, the benefits of innovation come with risks, and we have not always managed them wisely. AI is the next wave, and we have an obligation to learn lessons from the past to maximize future benefits for everyone and minimize harm. This will require commitment from both individuals and society at large. At the social level, governments are moving to regulate AI. To some innovators, regulation may look like an unnecessary restraint on progress. I see it differently. Regulation helps us avoid mistakes and enables new benefits as we move into an uncertain future. I welcome regulation that calls for more transparency into the opaque workings of large tech companies; this will help us understand their impact and steer them toward achieving broader societal benefits. Moreover, new regulations are needed because many existing ones were written for a pre-AI world. The new regulations should specify the outcomes we want in important areas like health care and finance—and those we do not want. But avoiding harm shouldn’t be just a priority for society. It also needs to be a priority for each innovator. As technologists, we have a responsibility to understand the implications of our research and innovate in ways that are beneficial. Traditionally, many technologists adopted the attitude that the shape technology takes is inevitable and there’s nothing we can do about it, so we might as well innovate freely. But we know that’s not true. Avoiding harm shouldn’t be just a priority for society. It also needs to be a priority for each innovator. When innovators choose to work on differential privacy (which allows AI to learn from data without exposing personally identifying information), they make a powerful statement that privacy matters. That statement helps shape the social norms adopted by public and private institutions. Conversely, when innovators create Web3 cryptographic protocols to launder money, that too creates a powerful statement—in my view, a harmful one—that governments should not be able to trace how funds are transferred and spent. If you see something unethical being done, I hope you’ll raise it with your colleagues and supervisors and engage them in constructive conversations. And if you are asked to work on something that you don’t think helps humanity, I hope you’ll actively work to put a stop to it. If you are unable to do so, then consider walking away. At AI Fund, I have killed projects that I assessed to be financially sound but ethically unsound. I urge you to do the same. Now, go forth and innovate! If you’re already in the innovation game, keep at it. There’s no telling what great accomplishment lies in your future. If your ideas are in the daydream stage, share them with others and get help to shape them into something practical and successful. Start executing, and find ways to use the power of innovation for good. This essay is part of MIT Technology Review’s 2023 Innovators Under 35 package. Meet this year’s honorees. Andrew Ng is a renowned global AI innovator. He leads AI Fund, DeepLearning.AI, and Landing AI. hide by Andrew Ng Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"As AI models are released into the wild, this innovator wants to ensure they’re safe | MIT Technology Review"

"https://www.technologyreview.com/2023/09/12/1078351/sharon-li-ai-innovation"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts 2023 Innovator of the Year: As AI models are released into the wild, Sharon Li wants to ensure they’re safe Li’s research could prevent AI models from failing catastrophically when they encounter unfamiliar scenarios. By Melissa Heikkilä archive page Sara Stathas Sharon Li is MIT Technology Review’s 2023 Innovator of the Year. Meet the rest of this year's Innovators Under 35. As we launch AI systems from the lab into the real world, we need to be prepared for these systems to break in surprising and catastrophic ways. It’s already happening. Last year, for example, a chess-playing robot arm in Moscow fractured the finger of a seven-year-old boy. The robot grabbed the boy’s finger as he was moving a chess piece and let go only after nearby adults managed to pry open its claws. This did not happen because the robot was programmed to do harm. It was because the robot was overly confident that the boy’s finger was a chess piece. The incident is a classic example of something Sharon Li, 32, wants to prevent. Li, an assistant professor at the University of Wisconsin, Madison, is a pioneer in an AI safety feature called out-of-distribution (OOD) detection. This feature, she says, helps AI models determine when they should abstain from action if faced with something they weren’t trained on. Li developed one of the first algorithms on out-of-distribution detection for deep neural networks. Google has since set up a dedicated team to integrate OOD detection into its products. Last year, Li’s theoretical analysis of OOD detection was chosen from over 10,000 submissions as an outstanding paper by NeurIPS, one of the most prestigious AI conferences. We’re currently in an AI gold rush, and tech companies are racing to release their AI models. But most of today’s models are trained to identify specific things and often fail when they encounter the unfamiliar scenarios typical of the messy, unpredictable real world. Their inability to reliably understand what they “know” and what they don’t “know” is the weakness behind many AI disasters. Li’s work calls on the AI community to rethink its approach to training. “A lot of the classic approaches that have been in place over the last 50 years are actually safety unaware,” she says. Her approach embraces uncertainty by using machine learning to detect unknown data out in the world and design AI models to adjust to it on the fly. Out-of-distribution detection could help prevent accidents when autonomous cars run into unfamiliar objects on the road, or make medical AI systems more useful in finding a new disease. “In all those situations, what we really need [is a] safety-aware machine learning model that’s able to identify what it doesn’t know,” says Li. This approach could also aid today’s buzziest AI technology, large language models such as ChatGPT. These models are often confident liars, presenting falsehoods as facts. This is where OOD detection could help. Say a person asks a chatbot a question it doesn’t have an answer to in its training data. Instead of making something up, an AI model using OOD detection would decline to answer. Related Story Tips for aspiring innovators on trying, failing, and the future of AI. Li’s research tackles one of the most fundamental questions in machine learning, says John Hopcroft, a professor at Cornell University, who was her PhD advisor. Her work has also seen a surge of interest from other researchers. “What she is doing is getting other researchers to work,” says Hopcroft, who adds that she’s “basically created one of the subfields” of AI safety research. Now, Li is seeking a deeper understanding of the safety risks relating to large AI models, which are powering all kinds of new online applications and products. She hopes that by making the models underlying these products safer, we’ll be better able to mitigate AI’s risks. “The ultimate goal is to ensure trustworthy, safe machine learning,” she says. Sharon Li is one of MIT Technology Review’s 2023 Innovators Under 35. Meet the rest of this year’s honorees. hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Building ethical thinking into technology | MIT Technology Review"

"https://www.technologyreview.com/2023/09/12/1077673/ethical-questions-tech"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Building ethical thinking into technology A look at how ethical questions can be understood and addressed through technology. By Mat Honan archive page Robyn Kessler In his essay introducing this year’s class of Innovators Under 35, Andrew Ng argues that AI is a general-purpose technology , much like electricity, that will be built into everything else. Indeed, it’s true, and it’s already happening. AI is rapidly becoming a tool that powers all sorts of other tools, a technological underpinning for a range of applications and devices. It can helpfully suggest a paella recipe in a web app. It can predict a protein structure from an amino acid sequence. It can paint. It can drive a car. It can relentlessly replicate itself, hijack the electrical grid for unlimited processing power, and wipe out all life on Earth. Okay, so that last one is just a nightmare scenario courtesy of the AI pioneer Geoffrey Hinton , who posed it at an EmTech Digital event of ours earlier this year. But it speaks to another of Ng’s points, and to the theme of this issue. Ng challenges the innovators to take responsibility for their work; he writes, “As we focus on AI as a driver of valuable innovation throughout society, social responsibility is more important than ever.” In many ways, the young innovators we celebrate in this issue exemplify the ways we can build ethical thinking into technology development. That is certainly true for our Innovator of the Year, Sharon Li , who is working to make AI applications safer by causing them to abstain from acting when faced with something they have not been trained on. This could help prevent the AIs we build from taking all sorts of unexpected turns, and causing untold harms. This issue revolves around questions of ethics and how they can be addressed, understood, or intermediated through technology. Should relatively affluent Westerners have stopped lending money to small entrepreneurs in the developing world because the lending platform is highly compensating its top executives? How much control should we have over what we give away? These are just a few of the thorny questions Mara Kardas-Nelson explores about a lenders’ revolt against the microfinance nonprofit Kiva. Jessica Hamzelou interrogates the policies on access to experimental medical treatments that are sometimes a last resort for desperate patients and their families. Who should be able to use these unproven treatments, and what proofs of efficacy and (more important) safety should be required? In another life-and-death question, Arthur Holland Michel takes on computer-assisted warfare. How much should we base our lethal decision-making on analysis performed by artificial intelligence? How can we build those AI systems so that we are more likely to treat them as advisors than deciders? Rebecca Ackermann takes a look at the long evolution of the open-source movement (and the ways it has redefined freedom—free as in beer, free as in speech, free as in puppies—again and again. If open source is to be something we all benefit from, and indeed that many even profit from, how should we think about its upkeep and advancement? Who should be responsible for it? And on a more meta level, Gregory Epstein, a humanist chaplain at MIT and the president of Harvard’s organization of chaplains , who focuses on the intersection of technology and ethics, takes a deep look at All Tech Is Human , a nonprofit that promotes ethics and responsibility in tech. He wonders how its relationship with the technology industry should be defined as it grows and takes funding from giant corporations and multibillionaires. How can a group dedicated to openness and transparency, he asks, coexist with members and even leaders committed to tech secrecy? There is a lot more as well. I hope this issue makes you think, and gives you lots of ideas about the future. Thanks for reading, Mat Honan hide by Mat Honan Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"How culture drives foul play on the internet and how new “upcode” can protect us | MIT Technology Review"

"https://www.technologyreview.com/2023/08/23/1077693/crypto-foul-play"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts How culture drives foul play on the internet, and how new “upcode” can protect us Three new books explore the various scams, frauds, and hacks that plague online life. By Rebecca Ackermann archive page George Wylesol The world of online misdeeds is an eerie biome, crawling with Bored Apes, Fancy Bears , Shiba Inu coins, self-­replicating viruses, and whales. But the behavior driving fraud, hacks, and scams on the internet has always been familiar and very human. New technologies change little about the fact that illegal operations exist because some people are willing to act illegally and others fall for the stories they tell. Related Story The crypto industry is investing heavily in getting more people to buy in. That doesn't mean you have to. To wit: Crypto speculation looks a lot like online sports betting, which looks like offline sports betting; cyber hacking resembles classic espionage; spear phishers recall flesh-and-blood con artists. The perpetrators of these crimes lure victims with well-worn appeals to faith and promises of financial reward. In Fancy Bear Goes Phishing , Yale law professor Scott Shapiro argues that technological solutions can’t solve the problem because they can’t force people to play nice online. The best ways to protect ourselves from online tricks are social—public policies, legal and business incentives, and cultural shifts. Shapiro’s book arrives just in time for the last gasp of the latest crypto wave, as major players find themselves trapped in the nets of human institutions. In early June, the US Securities and Exchange Commission went after Binance and Coinbase, the two largest cryptocurrency exchanges in the world, a few months after charging the infamous Sam Bankman-Fried, founder of the massive crypto exchange FTX, with fraud. While Shapiro mentions crypto only as the main means of payment in online crime, the industry’s wild ride through finance and culture deserves its own hefty chapter in the narrative of internet fraud. It may be too early for deep analysis, but we do have first-person perspectives on crypto from actor Ben McKenzie (former star of the teen drama The O.C. ) and streetwear designer and influencer Bobby Hundreds, the authors of—respectively— Easy Money and NFTs Are a Scam/NFTs Are the Future. (More heavily reported books on the crypto era from tech reporter Zeke Faux and Big Short author Michael Lewis are in the works.) “If we are committing serious crimes like fraud, it is crucially important that we find ways to justify our behavior to others, and crucially, to ourselves.” McKenzie testified at the Senate Banking Committee’s hearing on FTX that he believes the cryptocurrency industry “represents the largest Ponzi scheme in history,” and Easy Money traces his own journey from bored pandemic dabbler to committed crypto critic alongside the industry’s rise and fall. Hundreds also writes a chronological account of his time in crypto—specifically in nonfungible tokens, or NFTs, digital representational objects that he has bought, sold, and “dropped” on his own and through The Hundreds , a “community-based streetwear brand and media company.” For Hundreds, NFTs have value as cultural artifacts, and he’s not convinced that their time should be over (although he acknowledges that between 2019 and the writing of his book, more than $100 million worth of NFTs have been stolen, mostly through phishing scams). “Whether or not NFTs are a scam poses a philosophical question that wanders into moral judgments and cultural practices around free enterprise, mercantilism, and materialism,” he writes. For all their differences (a lawyer, an actor, and a designer walk into a bar …), Shapiro, McKenzie, and Hundreds all explore characters, motivations, and social dynamics much more than they do technical innovations. Online crime is a human story, these books collectively argue, and explanations of why it happens, why it works, and how we can stay safe are human too. To articulate how internet crime comes to be, Shapiro offers a new paradigm for the relationship between humanity and technology. He relabels technical computer code “downcode” and calls everything human surrounding and driving it “upcode.” From “the inner operations of the human brain” to “the outer social, political, and institutional forces that define the world,” upcode is the teeming ecosystem of humans and human systems behind the curtain of technology. Shapiro argues that upcode is responsible for all of technology’s impacts—positive and negative—and downcode is only its product. Technical tools like the blockchain, firewalls, or two-factor authentication may be implemented as efforts to ensure safety online, but they cannot address the root causes upstream. For any technologist or crypto enthusiast who believes computer code to be law and sees human error as an annoying hiccup, this idea may be disconcerting. But crime begins and ends with humans, Shapiro argues, so upcode is where we must focus both our blame for the problem and our efforts to improve online safety. McKenzie and Hundreds deal with crypto and NFTS almost entirely at the upcode level: neither has training in computer science, and both examine the industry through personal lenses. For McKenzie, it’s the financial realm, where friends encouraged him to invest in tokens to compensate for being out of work during the pandemic. For Hundreds, it’s the art world, which has historically been inaccessible to most and inhospitable for many—and is what led him to gravitate toward streetwear as a creative outlet in the first place. Hundreds saw NFTs as a signal of a larger positive shift toward Web3, a nebulous vision of a more democratized form of the internet where creative individuals could get paid for their work and build communities of fans and artists without relying on tech companies. The appeal of Web3 and NFTs is based in cultural and economic realities; likewise, online scams happen because buggy upcode—like social injustice, runaway capitalism, and corporate monopolies—creates the conditions. Constructing downcode guardrails to allow in only “good” intentions won’t solve online crime because bad acts are not so easily dismissed as the work of bad actors. The people who perpetrate scams, fraud, and hacks—or even participate in the systems around it, like speculative markets—often subscribe to a moral rubric as they act illegally. In Fancy Bear , Shapiro cites the seminal research of Sarah Gordon , the first to investigate the psychology of people who wrote computer viruses when this malware first popped up in the 1990s. Of the 64 respondents to her global survey, all but one had developmentally appropriate moral reasoning based on ethics, according to a framework created by the psychologist Lawrence Kohlberg: that is, these virus writers made decisions based on a sense of right and wrong. More recent research from Alice Hutchings, the director of the University of Cambridge’s Cybercrime Centre, also found hackers as a group to be “moral agents, possessing a sense of justice, purpose, and identity.” Many hackers find community in their work; others, like Edward Snowden, who leaked classified information from the US National Security Agency in 2013, cross legal boundaries for what they believe to be expressly moral reasons. Bitcoin , meanwhile, may be a frequent agent of crime but was in fact created to offer a “trustless” way to avoid relying on banks after the housing crisis and government bailouts of the 2000s left many wondering if traditional financial institutions could be trusted with consumer interests. The definition of crime is also upcode, shaped by social contracts as well as legal ones. In NFTs Are a Scam/NFTs Are the Future , Hundreds interviews the renowned tech investor and public speaker Gary Vaynerchuk, or “Gary Vee,” a figure he calls the “face of NFTs.” It was Vee’s “zeal and belief” that convinced Hundreds to create his own NFT collection, Adam Bomb Squad. Vee tells Hundreds that critics “may be right” when they call NFTs a scam. But while some projects may be opportunistic rackets, he hopes the work he makes is the variety that endures. Vee might be lying here, but at face value, he professes a belief in a greater good that he and everyone he recruits (including the thousands of attendees at his NFT convention ) can help build—even if there’s harm along the way. McKenzie spends much of two chapters in Easy Money describing his personal encounters with FTX’s Bankman-Fried, who was widely called the “ King of Crypto ” before his fall. Bankman-Fried professes to believe in crypto’s positive potential; indeed, he has claimed on the record many times that he wanted to do good with his work, despite knowing at points that it was potentially fraudulent. McKenzie struggles to understand this point of view. “If we are committing serious crimes like fraud,” he speculates, “it is crucially important that we find ways to justify our behavior to others and crucially, to ourselves.” While this rationalization certainly doesn’t excuse any crimes, it explains how people can perpetrate eye-boggling fraud again and again, even inventing new ways to scam. The human upcode that makes each of us see ourselves as the protagonist of our story is powerful, even and maybe especially when billions of dollars are at stake. Technological innovation does not change our fundamental behavior as humans, but technology has brought speed and spread to the gambling table. A single perpetrator can reach more victims faster now that the global world is connected. Despite his research, McKenzie did gamble on crypto—he shorted tokens on a specific, and incorrect, timeline. He doesn’t disclose how much he lost, but it was an amount that “provokes an uncomfortable conversation with your spouse.” He’s hardly the only savvy individual in history to fall for a risky pitch; our brains make it painfully easy to get scammed, another reason why solutions that rely entirely on computer code don’t work. “The human mind is riddled with upcode that causes us to make biased predictions and irrational choices,” Shapiro writes. Take the “representativeness heuristic,” which leads us to judge something by how much it resembles an existing mental image—even if that may lead us to overlook crucial information. If an animal looks like a duck and quacks like a duck, the representativeness heuristic tells us it can swim. Phishing scams rely on this rush to pattern matching. For example, Fancy Bear, the titular Russian hacking group of Shapiro’s book, used a visually and tonally convincing message to attempt to hack into Hillary Clinton campaign staffers’ email accounts in 2016. It worked. Also coming into play for scams, fraud, and hacks are the “availability heuristic,” which leads us to remember sensational events regardless of their frequency, and the “affect heuristic,” which leads us to emphasize our feelings about a decision over the facts, inflating “our expectations about outcomes we like”—such as winning a huge payout on a gamble. When Hundreds was concerned about whether NFTs were a good investment, he reached out to a friend whose belief was steadfast and found himself calmed. “It was that sense of conviction that separated the losers from the winners,” he writes, even when the facts might have supported stepping back. The marketing pitch of communal faith and reward, the enticement to join a winning team, feeds a human social instinct—especially as more offline modes of connection are faltering. It’s telling that after the SEC brought charges against Coinbase, the company responded by issuing a pro-crypto NFT , imploring its community to offer support for the struggling industry by minting it. (Coinbase and the minting platform Zora promise to donate the mint fees they’ll receive from consumers to pro-crypto advocacy.) The crypto industry rose to power on this kind of faith-based relationship, and it continues to appeal to some: more than 135,000 of the Coinbase tokens have been minted since the SEC suit was announced. Beyond money, “we’re just as motivated by identity and community (or its upside-down cousin, tribalism),” writes Hundreds, “and the most fervent contemporary movements and trends masterfully meld them all together. The only thing that feels as good as getting rich is doing so by rallying around an impassioned cause with a band of like-minded friends.” Technological innovation does not change our fundamental behavior as humans, but technology has brought speed and spread to the gambling table. A single perpetrator can reach more victims faster now that the global world is connected. The risks are higher now, as clearly demonstrated by the headline-exploding results of the 2016 Clinton email hack, the billions lost by investors in the volatile crypto industry, and billions more lost through crypto hacks and scams. Shapiro argues that the efforts of the antivirus and antihacking industry to code guardrails into our online systems have failed. Fraud goes on. Instead, we must reexamine the upcode that has fostered and supported online crimes: “our settled moral and political convictions on what we owe one another and how we should respect security and privacy.” For Shapiro, effectively addressing online fraud, hacks, and scams requires political, economic, and social shifts such as creating incentives for businesses to protect customers and penalties for data breaches, supporting potential hackers in finding community outside of crime, and developing government and legal policies to prevent illicit payment through mechanisms like cryptocurrencies. Shapiro admits that shifting upcode this way will likely take generations, but the work has already started. The SEC’s recent moves against crypto exchanges are promising steps, as are the FTC’s public warnings against scammy AI claims and generative AI fraud. Growing public awareness about the importance of data privacy and security will help too. But while some humans are working on evolving our social systems, others will continue to hunt online for other people’s money. In our lifetimes, fraud, hacks, and scams will likely always find a home on the internet. But being aware of the upcode all around us may help us find safer paths through the online jungle. Rebecca Ackermann is a writer and artist in San Francisco. hide by Rebecca Ackermann Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Computing What’s next for the world’s fastest supercomputers Scientists have begun running experiments on Frontier, the world’s first official exascale machine, while facilities worldwide build other machines to join the ranks. By Sophia Chen archive page AI-powered 6G networks will reshape digital interactions The convergence of AI and communication technologies will create 6G networks that make hyperconnectivity and immersive experiences an everyday reality for consumers. By MIT Technology Review Insights archive page The power of green computing Sustainable computing practices have the power to both infuse operational efficiencies and greatly reduce energy consumption, says Jen Huffstetler, chief product sustainability officer at Intel. By MIT Technology Review Insights archive page How this Turing Award–winning researcher became a legendary academic advisor Theoretical computer scientist Manuel Blum has guided generations of graduate students into fruitful careers in the field. By Sheon Han archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The beautiful complexity of the US radio spectrum | MIT Technology Review"

"https://www.technologyreview.com/2023/08/23/1077686/radio-spectrum-visualized"

"Featured Topics Newsletters Events Podcasts The beautiful complexity of the US radio spectrum The United States Frequency Allocation Chart shows how the nation’s precious radio frequencies are carefully shared. by Jon Keegan archive page Somewhere above you right now, a plane is broadcasting its coordinates on 1090 megahertz. A satellite high above Earth is transmitting weather maps on 1694.1 MHz. On top of all that, every single phone and Wi-Fi router near you blasts internet traffic through the air over radio waves. A carefully regulated radio spectrum is what makes it possible for these signals to get to the right place intact. The Federal Communication Commis-sion and the National Telecommunications and Information Administration share the task of managing radio frequencies for US airwaves. The NTIA manages all federal radio uses (including military use), while the FCC manages everything else. It is an incredibly complex system, and to help with the job of explaining the importance of managing this invisible natural resource, the NTIA publishes the United States Frequency Allocation Chart (which you can order as a wall chart for $6). The US government lays claim to a large chunk of spectrum for military use, communications, and transportation. FM radio operates between 88 and 108.0 MHz, and AM radio operates between 540 and 1700 kilohertz. Using licenses, amateur radio operators are granted slices where they can communicate safely, as are businesses and other institutions. Civil aviation, maritime navigation, satellite communications, radio astronomy, cellular voice, and data all lay claim to colorful plots on this chart. The chart uses 33 color-coded categories to visualize the information in a crazy quilt of blocks (some wide, some narrow), spread from 9 kHz (very low frequency) all the way to 300 GHz (extremely high frequency). It does suffer from scale distortions, not unlike a map of Earth. Eric Rosenberg, a telecommunications specialist at NTIA, says a lot of the choices about what service goes where come down to physics and the environment where the service will be used: “You can’t just pick up a block and say, okay, we’re gonna move these radars over here.” The chart is always extremely popular, Rosenberg says; fans include lawmakers in Congress. Last updated in 2016, it is due for another revision. “We’re getting to the point where we really feel that we need to redo it,” he says. “Again, it’s a very large project.” ν A version of this story appeared on Beautiful Public Data ( beautifulpublicdata.com ), a newsletter by Jon Keegan (KE3GAN). by Jon Keegan Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Deep Dive Computing What’s next for the world’s fastest supercomputers Scientists have begun running experiments on Frontier, the world’s first official exascale machine, while facilities worldwide build other machines to join the ranks. By Sophia Chen archive page AI-powered 6G networks will reshape digital interactions The convergence of AI and communication technologies will create 6G networks that make hyperconnectivity and immersive experiences an everyday reality for consumers. By MIT Technology Review Insights archive page The power of green computing Sustainable computing practices have the power to both infuse operational efficiencies and greatly reduce energy consumption, says Jen Huffstetler, chief product sustainability officer at Intel. By MIT Technology Review Insights archive page How this Turing Award–winning researcher became a legendary academic advisor Theoretical computer scientist Manuel Blum has guided generations of graduate students into fruitful careers in the field. By Sheon Han archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Why Venice’s salt marshes could help save the city | MIT Technology Review"

"https://www.technologyreview.com/2023/08/22/1077661/venice-salt-marshes"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Why salt marshes could help save Venice Scientists see the sinking city as a laboratory for environmental solutions. By Catherine Bennett archive page Jane da Mosto and Alessandro Gasparotto survey Venice’s central lagoon from a restored salt marsh. Courtesy Photo Venice, Italy, is suffering from a combination of subsidence—the city’s foundations slowly sinking into the mud on which they are built—and rising sea levels. In the worst-case scenario, it could disappear underwater by the year 2100. Alessandro Gasparotto, an environmental engineer, is one of the many people trying to keep that from happening. Standing on a large mudflat in the center of the Venetian lagoon, he pushes a hollow three-foot-high metal cylinder called a piezometer into the thick black mud. This instrument will measure how groundwater moves through the sediment as the lagoon’s tides rise and fall. Knowing what’s happening under the mud is crucial for understanding whether, and how, vegetation can grow and eventually transform this barren landscape of mud into a salt marsh. Gasparotto’s work with salt marshes is part of a project steered by the NGO We Are Here Venice (WAHV) and funded by the EU through the WaterLANDS research program, which is restoring wetlands across Europe. The Venice chapter has been granted €2 million over five years to investigate whether artificial mudflats—the deposits that result when the lagoon is dredged to create shipping channels—can be turned back into the marshes that once thrived in this area and become a functioning part of the lagoon ecosystem again. “The history of the city of Venice has always been intertwined with the history of the lagoon,” explains Andrea D’Alpaos, a geoscientist at the University of Padova. The health of Venice depends on the health of the lagoon system, and vice versa. This relationship is not only economic—protecting the lagoon ecosystem bolsters fishing yields, for example—but also infrastructural. Salt marshes have a buffering effect on tidal currents, attenuating the force of waves and reducing the water’s erosive effect on Venice’s buildings. But the marshes have been declining for centuries. This is due in part to waterway mismanagement going as far back as the 1500s, when Venetians diverted rivers out of the lagoon, starving it of sediment that would naturally be borne in on their currents. The building of breakwaters at three inlets on the Adriatic Sea and the excavation of an enormous shipping canal in the late 1900s further eroded the marshland. And while the city has been the beneficiary of thousands of euros in restoration and prevention work—most notably the €6.2 billion MOSE (the Italian acronym for “Experimental Electromechanical Module”), a colossal (and extremely effective) system of mobile sea barriers designed to keep the Adriatic’s floodwaters from the city—the marshes have been overlooked. Related Story A previously unrevealed program would use cameras, computer vision, and machine learning to track the carbon stored in the biomass of the oceans. Construction of MOSE began in 2003, but delays, cost overruns and a corruption scandal stalled its completion. It was activated for the first time, successfully preventing a flood, in 2020. Paradoxically, it is the MOSE technology, which protects the city, that is damaging the lagoon ecosystem. “When the MOSE system is raised, it stops storm surges and prevents Venice flooding,” D’Alpaos says. “Storm surges are bad for Venice, but they are good for marshes; 70% of sediment that reaches the marsh is delivered during storm surges.” These excessively high tides, D’Alpaos continues, are happening more often. The problem, he says, is that “if you close the lagoon too often or for too long, you prevent sediment reaching marshes.” In the more than 20 years that he has been studying the lagoon, he says, he’s seen marshes disappearing at an alarming rate: “The marshes are drowning. Two centuries ago, the Venice lagoon had 180 square kilometers [69 square miles] of marshes. Now we only have 43 square kilometers.” One of the sites the We Are Here Venice team is working is on a natural salt marsh, hugged on one side by a kidney-­shaped platform of infill dredged from the lagoon. In places where the mud is dry, the ground has separated into patches that conjure small tectonic plates, littered with bone-white crab claws picked clean and dropped by gulls flying overhead. Three orange sticks mark the spot where a fence between the salt marsh and the infill will be removed to allow water exchange and the movement of sediment, making the two ecosystems “speak to one another,” as Jane da Mosto, the executive director and cofounder of WAHV, describes it. Tramping over the island in rubber boots, releasing gobbets of black mud at every step, da Mosto explains that “all of this represents a kind of natural capital.” Not only do the marshes store carbon, but “these environments also support fish habitats and a huge bird population,” she adds. Even the samphire, an edible marshland plant, “could be cultivated like a crop.” Marshes are also more efficient carbon sinks than forests, because marshland plants that store carbon are gradually buried under sediment as the tide washes over them, trapping the carbon for as long as centuries. Da Mosto sees the city as something of a laboratory for environmental solutions with wider applications. “Venice is a mirror on the world,” she says. “If the city remains an example of all the world’s problems, as it is now, then there’s no point trying to keep it alive. But we should be able to show how to turn infills into ecologically productive salt marshes and how to transform an economy based on mass tourism into an economy based on its natural capital.” Catherine Bennett is a freelance journalist based in Paris. hide by Catherine Bennett Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Climate change and energy Think that your plastic is being recycled? Think again. Plastic is cheap to make and shockingly profitable. It’s everywhere. And we’re all paying the price. By Douglas Main archive page 15 Climate Tech Companies to Watch By Amy Nordrum archive page 2023 Climate Tech Companies to Watch: Blue Frontier and its energy-efficient AC The startup's AC units suck moisture out of the air for more efficient cooling. By Amy Nordrum archive page Oyster fight: The humble sea creature could hold the key to restoring coastal waters. Developers hate it. Revitalizing oyster farms and wild oyster reefs could undo decades of environmental destruction on our coasts By Anna Kramer archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The ice cores that will let us look 1.5-million-years into the past | MIT Technology Review"

"https://www.technologyreview.com/2023/08/21/1077657/ice-core-earth-history"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts The ice cores that will let us look 1.5 million years into the past Scientists are drilling deep into the Antarctic ice to better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles. By Christian Elliott archive page An ice core sample Courtesy Photo Moving quickly and carefully in two layers of gloves, Florian Krauss sets a cube of ice into a gold-plated cylinder that glows red in the light of the aiming laser. He steps back to admire the machine, covered with wires and gauges, that turns polar ice into climate data. If this were a real slice of precious million-year-old ice from Antarctica and not just a test cube, he’d next seal the extraction vessel under a vacuum and power on the 150-watt main laser, slowly causing the entire ice sample to sublimate directly into gas. For Krauss, a PhD student at the University of Bern in Switzerland, this would unlock its secrets, exposing the concentrations of greenhouse gases like carbon dioxide trapped within. To better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles, scientists have long turned to ice cores drilled in Antarctica, where snow layers accumulate and compact over hundreds of thousands of years, trapping samples of ancient air in a lattice of bubbles that serve as tiny time capsules. By analyzing those bubbles and the ice’s other contents, like dust and water isotopes, scientists can connect greenhouse-gas concentrations with temperatures going back 800,000 years. Europe’s Beyond EPICA (European Project for Ice Coring in Antarctica) initiative, now in its third year, hopes to eventually retrieve the oldest core yet, dating back 1.5 million years. This would extend the climate record all the way back to the Mid-Pleistocene Transition, a mysterious period that marked a major change in the frequency of Earth’s climatic oscillations—cycles of repeating glacial and warm periods. Successfully drilling a core that old—a years-long endeavor—might be the easy part. Next, scientists must painstakingly free the trapped air from that ice. Krauss and his colleagues are developing an innovative new way to do that. “We’re not interested in the ice itself—we’re just interested in the air samples included, so we needed to find a new way to extract the air from the ice,” he says. Related Story The intervention may break down methane, mimicking a phenomenon that could have amplified ice ages. But scientists say far more basic research still needs to be done. Melting isn’t an option because carbon dioxide easily dissolves into water. Traditionally, scientists have used mechanical extraction methods, grinding up samples of individual layers of ice to free the air. But grinding wouldn’t be effective for the Beyond EPICA ice in the university’s storage freezer, which is kept at 50 °C below zero. The oldest ice at the very bottom of the core will be so compressed, and the individual annual layers so thin, that bubbles won’t be visible—they’ll have been pressed into the lattice of ice crystals, forming a new phase called clathrate. “At the very bottom, we expect 20,000 years of climate history compressed in only one meter of ice,” says Hubertus Fischer, head of the past climate and ice core science group at Bern. That’s a hundredth the thickness of any existing ice core record. The new method Krauss and Fischer are developing is called deepSLice. (A pizza menu is taped to the side of the device right under the laser warning labels, a gift from a pizzeria in Australia with the same name.) DeepSLice has two parts. The Laser-Induced Sublimation Extraction Device, or LISE, fills half a room in the team’s lab space. LISE aims a near-infrared laser continuously at a 10-centimeter slice of ice core so that it turns directly from solid to gas under extremely low pressure and temperature. The sublimated gas then freezes into six metal dip tubes cooled to 15 K (-258 °C), each containing the air from one centimeter of ice core. Finally the samples are loaded into a custom-made absorption spectrometer based on quantum cascade laser technology, which shoots photons through the gas sample to measure concentrations of carbon dioxide, methane, and nitrous oxide simultaneously. Another big advantage of this system is that it takes a lot less ice (and work) than the old method of analysis, in which scientists measured methane by melting ice (it doesn’t dissolve into water) and measured carbon dioxide by grinding ice. DeepSLice offers “a unique capability that nobody else has,” says Christo Buizert, an ice core scientist at Oregon State University and the ice analysis lead for COLDEX (the Center for Oldest Ice Exploration)—the US equivalent of Beyond EPICA, which is currently in a “friendly race” with the Europeans to drill a continuous core down to 1.5-million-­year-old ice. “What they’re trying to do, sublimating ice—people have been trying this for a long time, but it’s one of the most challenging ways to extract gases from ice,” Buizert says. “It’s a very promising way, because you get 100% of the gases out, but it’s very difficult to do. So the fact that they’ve managed to get it working is very impressive.” Krauss and Fischer still have about three years before they get their hands on that section of critical ice. There are still kinks to iron out, like how to recapture the samples from the spectrometer for additional analysis, but they think they’ll be ready when it finally arrives in freezer containers on a ship from Antarctica via Italy. “Our latest results showed us we are on a good track, and actually, we achieved the precision we wanted to,” Krauss says. “So I’m sure it’s going to be ready.” Christian Elliott is a science and environmental reporter based in Chicago. hide by Christian Elliott Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Climate change and energy Think that your plastic is being recycled? Think again. Plastic is cheap to make and shockingly profitable. It’s everywhere. And we’re all paying the price. By Douglas Main archive page 15 Climate Tech Companies to Watch By Amy Nordrum archive page 2023 Climate Tech Companies to Watch: Blue Frontier and its energy-efficient AC The startup's AC units suck moisture out of the air for more efficient cooling. By Amy Nordrum archive page Oyster fight: The humble sea creature could hold the key to restoring coastal waters. Developers hate it. Revitalizing oyster farms and wild oyster reefs could undo decades of environmental destruction on our coasts By Anna Kramer archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. 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"This UK startup engineered a clever way to reuse waste heat from cloud computing | MIT Technology Review"

"https://www.technologyreview.com/2023/08/18/1077548/computer-waste-heat"

"Featured Topics Newsletters Events Podcasts This startup has engineered a clever way to reuse waste heat from cloud computing Heata is now using these busy servers to heat water for homes. Luigi Avantaggiato by Luigi Avantaggiato archive page Using heat generated by computers to provide free hot water was an idea born not in a high-tech laboratory, but in a battered country workshop deep in the woods of Godalming, England. “The idea of using the wasted heat of computing to do something else has been hovering in the air for some time,” explains Chris Jordan, a 48-year-old physicist, “but only now does technology allow us to do it adequately. “This is where I prototyped the thermal conductor that carries heat from computer processors to the cylinder filled with water,” he says, opening his workshop door to reveal a 90-liter electric boiler. “We ran the first tests, and we understood that it could work.” Jordan is cofounder and chief technology officer of Heata , an English startup that has created an innovative cloud network where computers are attached to the boilers in people’s homes. Related Story Here’s where hundreds of billions of dollars for climate technology is going. Next to the boiler is a computer tagged with a sticker that reads: “This powerful computer server is transferring the heat from its processing into the water in your cylinder.” A green LED light indicates that the boiler is running, Jordan explains. “The machine receives the data and processes it. Thus we are able to transfer the equivalent of 4.8 kilowatt-hours of hot water, about the daily amount used by an average family.” When you sign up with Heata, it places a server in your home, where it connects via your Wi-Fi network to similar servers in other homes—all of which process data from companies that pay it for cloud computing services. Each server prevents one ton of carbon dioxide equivalent per year from being emitted and saves homeowners an average of £250 on hot water annually, a considerable discount in a region where 13% of the inhabitants struggle to afford heat. The Heata trial, funded by a grant from Innovate UK, a national government agency, has been active in Surrey County for more than a year. To date, 80 units have been installed, and another 30 are slated to have a boiler to heat by the end of October. Heata’s solution is “particularly elegant,” says Mike Pitts, deputy challenge director of Innovate UK, calling it a way to “use electricity twice—providing services to a rapidly growing industry (cloud computing) and providing domestic hot water.” The startup is now part of Innovate UK’s Net Zero Cohort, having been identified as a key part of the push to achieve an economy where carbon emissions are either eliminated or balanced out by other technologies. Heata’s process is simple yet introduces a radical shift toward sustainable management of data centers: instead of being cooled with fans, which is expensive and energy intensive, computers are cooled by a patented thermal bridge that transports the heat from the processors toward the shell of the boiler. And rather than operating with a data center located in an energy-intensive location, Heata works as an intermediary for computing: it receives workloads and distributes them to local homes for processing. Businesses that need to process data are using the Heata network as a sustainable alternative to traditional computing. The company has created what Heata’s designer and cofounder Mike Paisley describes as a diffuse data center. Rather than cooling a building that holds many servers, he explains, “our model of sustainability moves data processing [to] where there is need for heat, exploiting thermal energy waste to provide free hot water to those who need it, transforming a calculation problem into a social and climatic advantage.” The people involved in the Heata experiment are diverse in age and household composition, and their reasons for participating are varied: a need to save on bills, a love for the environment, an interest in helping combat climate change, and fascination with seeing a computer heat the water. Among the satisfied customers is Helen Whitcroft, mayor of Surrey Heath. “We started reducing our carbon footprint many years ago by installing photovoltaic panels,” she says. “We recently bought batteries to store the energy we produce. Curiosity also moved us: it didn’t seem possible that a computer could heat water, but it works.” Luigi Avantaggiato is an Italian documentary photographer. by Luigi Avantaggiato Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Deep Dive Climate change and energy Think that your plastic is being recycled? Think again. Plastic is cheap to make and shockingly profitable. It’s everywhere. And we’re all paying the price. By Douglas Main archive page 15 Climate Tech Companies to Watch By Amy Nordrum archive page 2023 Climate Tech Companies to Watch: Blue Frontier and its energy-efficient AC The startup's AC units suck moisture out of the air for more efficient cooling. By Amy Nordrum archive page Oyster fight: The humble sea creature could hold the key to restoring coastal waters. Developers hate it. Revitalizing oyster farms and wild oyster reefs could undo decades of environmental destruction on our coasts By Anna Kramer archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The future of open source is still very much in flux | MIT Technology Review"

"https://www.technologyreview.com/2023/08/17/1077498/future-open-source"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts The future of open source is still very much in flux Free and open software have transformed the tech industry. But we still have a lot to work out to make them healthy, equitable enterprises. By Rebecca Ackermann archive page Saiman Chow When Xerox donated a new laser printer to the MIT Artificial Intelligence Lab in 1980, the company couldn’t have known that the machine would ignite a revolution. The printer jammed. And according to the 2002 book Free as in Freedom , Richard M. Stallman, then a 27-year-old programmer at MIT, tried to dig into the code to fix it. He expected to be able to: he’d done it with previous printers. The early decades of software development generally ran on a culture of open access and free exchange , where engineers could dive into each other’s code across time zones and institutions to make it their own or squash a few bugs. But this new printer ran on inaccessible proprietary software. Stallman was locked out—and enraged that Xerox had violated the open code-sharing system he’d come to rely on. A few years later, in September 1983, Stallman released GNU , an operating system designed to be a free alternative to one of the dominant operating systems at the time: Unix. Stallman envisioned GNU as a means to fight back against the proprietary mechanisms, like copyright, that were beginning to flood the tech industry. The free-software movement was born from one frustrated engineer’s simple, rigid philosophy: for the good of the world, all code should be open, without restriction or commercial intervention. Forty years later, tech companies are making billions on proprietary software , and much of the technology around us—from ChatGPT to smart thermostats —is inscrutable to everyday consumers. In this environment, Stallman’s movement may look like a failed values experiment crushed under the weight of commercial reality. But in 2023, the free and open-source software movement is not only alive and well; it has become a keystone of the tech industry. Today, 96% of all code bases incorporate open-source software. GitHub, the biggest platform for the open-source community, is used by more than 100 million developers worldwide. The Biden administration’s Securing Open Source Software Act of 2022 publicly recognized open-source software as critical economic and security infrastructure. Even AWS, Amazon’s money-making cloud arm, supports the development and maintenance of open-source software ; it committed its portfolio of patents to an open use community in December of last year. Over the last two years, while public trust in private technology companies has plummeted , organizations including Google , Spotify , the Ford Foundation , Bloomberg , and NASA have established new funding for open-source projects and their counterparts in open science efforts—an extension of the same values applied to scientific research. The fact that open-source software is now so essential means that long-standing leadership and diversity issues in the movement have become everyone’s problems. Many open-source projects began with “benevolent dictator for life” ( BDFL ) models of governance, where original founders hang on to leadership for years—and not always responsibly. Stallman and some other BDFLs have been criticized by their own communities for misogynistic or even abusive behavior. Stallman stepped down as president of the Free Software Foundation in 2019 (although he returned to the board two years later). Overall, open-source participants are still overwhelmingly white, male, and located in the Global North. Projects can be overly influenced by corporate interests. Meanwhile, the people doing the hard work of keeping critical code healthy are not consistently funded. In fact, many major open-source projects still operate almost completely on volunteer steam. Related Story Greater access to the code behind generative models is fueling innovation. But if top companies get spooked, they could close up shop. Challenges notwithstanding, there’s plenty to celebrate in 2023, the year of GNU’s 40th birthday. The modern open-source movement persists as a collaborative haven for transparent ways of working within a highly fragmented and competitive industry. Selena Deckelmann, chief product and technology officer at the Wikimedia Foundation, says the power of open source lies in its “idea that people anywhere can collaborate together on software, but also on many [more] things.” She points out that tools to put this philosophy into action, like mailing lists , online chat, and open version control systems, were pioneered in open-source communities and have been adopted as standard practice by the wider tech industry. “We found a way for people from all over the world, regardless of background, to find a common cause to collaborate with each other,” says Kelsey Hightower, an early contributor to Kubernetes , an open-source system for automating app deployment and management, who recently retired from his role as a distinguished engineer at Google Cloud. “I think that is pretty unique to the world of open source.” The 2010s backlash against tech’s unfettered growth, and the recent AI boom, have focused a spotlight on the open-source movement’s ideas about who has the right to use other people’s information online and who benefits from technology. Clement Delangue, CEO of the open-source AI company Hugging Face, which was recently valued at $4 billion , testified before Congress in June of 2023 that “ethical openness” in AI development could help make organizations more compliant and transparent, while allowing researchers beyond a few large tech companies access to technology and progress. “We’re in a unique cultural moment,” says Danielle Robinson, executive director of Code for Science and Society, a nonprofit that provides funding and support for public-interest technology. “People are more aware than ever of how capitalism has been influencing what technologies get built, and whether you have a choice to interact with it.” Once again, free and open-source software have become a natural home for the debate about how technology should be. Free as in freedom The early days of the free-software movement were fraught with arguments about the meaning of “free.” Stallman and the Free Software Foundation (FSF), founded in 1985, held firm to the idea of four freedoms: people should be allowed to run a program for any purpose, study how it works from the source code and change it to meet their needs, redistribute copies, and distribute modified versions too. Stallman saw free software as an essential right: “Free as in free speech, not free beer,” as his apocryphal slogan goes. He created the GNU General Public License, what’s known as a “copyleft” license, to ensure that the four freedoms were protected in code built with GNU. Linus Torvalds, the Finnish engineer who in 1991 created the now ubiquitous Unix alternative Linux, didn’t buy into this dogma. Torvalds and others, including Microsoft’s Bill Gates , believed that the culture of open exchange among engineers could coexist with commerce, and that more-restrictive licenses could forge a path toward both financial sustainability and protections for software creators and users. It was during a 1998 strategic meeting of free-software advocates—which notably did not include Stallman—that this pragmatic approach became known as “open source.” (The term was coined and introduced to the group not by an engineer, but by the futurist and nano­technology scholar Christine Peterson. ) Karen Sandler, executive director of the Software Freedom Conservancy, a nonprofit that advocates for free and open-source software, saw firsthand how the culture shifted from orthodoxy to a big-tent approach with room for for-profit entities when she worked as general counsel at the Software Freedom Law Center in the early 2000s. “The people who were ideological—some of them stayed quite ideological. But many of them realized, oh, wait a minute, we can get jobs doing this. We can do well by doing good,” Sandler remembers. By leveraging the jobs and support that early tech companies were offering, open-source contributors could sustain their efforts and even make a living doing what they believed in. In that manner, companies using and contributing to free and open software could expand the community beyond volunteer enthusiasts and improve the work itself. “How could we ever make it better if it’s just a few radical people?” Sandler says. As the tech industry grew around private companies like Sun Microsystems, IBM, Microsoft, and Apple in the late ’90s and early ’00s, new open-source projects sprang up, and established ones grew roots. Apache emerged as an open-source web server in 1995. Red Hat, a company offering enterprise companies support for open-source software like Linux, went public in 1999. GitHub, a platform originally created to support version control for open-source projects, launched in 2008 , the same year that Google released Android, the first open-source phone operating system. The more pragmatic definition of the concept came to dominate the field. Meanwhile, Stallman’s original philosophy persisted among dedicated groups of believers—where it still lives today through nonprofits like FSF, which only uses and advocates for software that protects the four freedoms. “If a company only ends up just sharing, and nothing more, I think that should be celebrated.” As open-source software spread, a bifurcation of the tech stack became standard practice, with open-source code as the support structure for proprietary work. Free and open-source software often served in the underlying foundation or back-end architecture of a product, while companies vigorously pursued and defended copyrights on the user-facing layers. Some estimate that Amazon’s 1999 patent on its one-click buying process was worth $2.4 billion per year to the company until it expired. It relied on Java , an open-source programming language, and other open-source software and tooling to build and maintain it. Today, corporations not only depend on open-source software but play an enormous role in funding and developing open-source projects: Kubernetes (initially launched and maintained at Google) and Meta’s React are both robust sets of software that began as internal solutions freely shared with the larger technology community. But some people, like the Software Freedom Conservancy’s Karen Sandler, identify an ongoing conflict between profit-­driven corporations and the public interest. “Companies have become so savvy and educated with respect to open-source software that they use a ton of it. That’s good,” says Sandler. At the same time, they profit from their proprietary work—which they sometimes attempt to pass off as open too, a practice the scholar and organizer Michelle Thorne dubbed “openwashing” in 2009. For Sandler, if companies don’t also make efforts to support user and creator rights, they’re not pushing forward the free and open-source ethos. And she says for the most part, that’s indeed not happening: “They’re not interested in giving the public any appreciable rights to their software.” Others, including Kelsey Hightower, are more sanguine about corporate involvement. “If a company only ends up just sharing, and nothing more, I think that should be celebrated,” he says. “Then if for the next two years you allow your paid employees to work on it, maintaining the bugs and issues, but then down the road it’s no longer a priority and you choose to step back, I think we should thank [the company] for those years of contributions.” In stark contrast, FSF, now in its 38th year, holds firm to its original ideals and opposes any product or company that does not support the ability for users to view, modify, and redistribute code. The group today runs public action campaigns like “End Software Patents,” publishing articles and submitting amicus briefs advocating the end of patents on software. The foundation’s executive director, Zoë Kooyman, hopes to continue pushing the conversation toward freedom rather than commercial concerns. “Every belief system or form of advocacy needs a far end,” she says. “That’s the only way to be able to drive the needle. [At FSF], we are that far end of the spectrum, and we take that role very seriously.” Free as in puppy Forty years on from the release of GNU, there is no singular open-source community, “any more than there is an ‘urban community,’” as researcher and engineer Nadia Asparouhova (formerly Eghbal) writes in her 2020 book Working in Public: The Making and Maintenance of Open Source Software. There’s no singular definition, either. The Open Source Initiative (OSI) was founded in 1998 to steward the meaning of the phrase, but not all modern open-source projects adhere to the 10 specific criteria OSI laid out, and other definitions appear across communities. Scale, technology, social norms, and funding also range widely from project to project and community to community. For example, Kubernetes has a robust, organized community of tens of thousands of contributors and years of Google investment. Salmon is a niche open-source bioinformatics research tool with fewer than 5 0 contributors, supported by grants. OpenSSL , which encrypts an estimated 66% of the web, is currently maintained by 18 engineers compensated through donations and elective corporate contracts. The major discussions now are more about people than technology: What does healthy and diverse collaboration look like? How can those who support the code get what they need to continue the work? “How do you include a voice for all the people affected by the technology you build?” asks James Vasile, an open-source consultant and strategist who sits on the board of the Electronic Frontier Foundation. “These are big questions. We’ve never grappled with them before. No one was working on this 20 years ago, because that just wasn’t part of the scene. Now it is, and we [in the open-source community] have the chance to consider these questions.” “We need designers, ethnographers, social and cultural experts. We need everyone to be playing a role in open source.” “Free as in puppy,” a phrase that can be traced back to 2006 , has emerged as a valuable definition of “free” for modern open-source projects—one that speaks to the responsibilities of creators and users to each other and the software, in addition to their rights. Puppies need food and care to survive; open-source code needs funding and “maintainers,” individuals who consistently respond to requests and feedback from a community, fix bugs, and manage the growth and scope of a project. Many open-source projects have become too big, complicated, or important to be governed by one person or even a small group of like-minded individuals. And open-source contributors have their own needs and concerns, too. A person who’s good at building may not be good at maintaining; someone who creates a project may not want to or be able to run it indefinitely. In 2018, for instance, Guido van Rossum, the creator of the open-source programming language Python, stepped down from leadership after almost 30 years, exhausted from the demands of the mostly uncompensated role. “I’m tired,” he wrote in his resignation message to the community, “and need a very long break.” Supporting the people who create, maintain, and use free and open-source software requires new roles and perspectives. Whereas the movement in its early days was populated almost exclusively by engineers communicating across message boards and through code, today’s open-source projects invite participation from new disciplines to handle logistical work like growth and advocacy, as well as efforts toward greater inclusion and belonging. “We’ve shifted from open source being about just the technical stuff to the broader set of expertise and perspectives that are required to make effective open-source projects,” says Michael Brennan, senior program officer with the Technology and Society program at the Ford Foundation, which funds research into open internet issues. “We need designers, ethnographers, social and cultural experts. We need everyone to be playing a role in open source if it’s going to be effective and meet the needs of the people around the world.” One powerful source of support arrived in 2008 with the launch of GitHub. While it began as a version control tool, it has grown into a suite of services, standards, and systems that is now the “highway system” for most open-source development, as Asparouhova puts it in Working in Public. GitHub helped lower the barrier to entry, drawing wider contribution and spreading best practices such as community codes of conduct. But its success has also given a single platform vast influence over communities dedicated to decentralized collaboration. Demetris Cheatham, until recently GitHub’s senior director for diversity and inclusion strategy, took that responsibility very seriously. To find out where things stood, the company partnered with the Linux Foundation in 2021 on a survey and resulting report on diversity and inclusion within open source. The data showed that despite a pervasive ethos of collaboration and openness (more than 80% of the respondents reported feeling welcome), communities are dominated by contributors who are straight, white, male, and from the Global North. In response, Cheatham, who is now the company’s chief of staff, focused on ways to broaden access and promote a sense of belonging. GitHub launched All In for Students, a mentorship and education program with 30 students drawn primarily from historically Black colleges and universities. In its second year, the program expanded to more than 400 students. Representation has not been the only stumbling block to a more equitable open-source ecosystem. The Linux Foundation report showed that only 14% of open-source contributors surveyed were getting paid for their work. While this volunteer spirit aligns with the original vision of free software as a commerce-free exchange of ideas, free labor presents a major access issue. Additionally, 30% of respondents in the survey did not trust that codes of conduct would be enforced—suggesting they did not feel they could count on a respectful working environment. “We’re at another inflection point now where codes of conduct are great, but they’re only a tool,” says Code for Science and Society’s Danielle Robinson. “I’m starting to see larger cultural shifts toward rethinking extractive processes that have been a part of open source for a long time.” Getting maintainers paid and connecting contributors with support are now key to opening up open source to a more diverse group of participants. With that in mind, this year GitHub established resources specifically for maintainers, including workshops and a hub of DEI tools. And in May, the platform launched a new project to connect large, well-resourced open-source communities with smaller ones that need help. Cheatham says it’s crucial to the success of any of these programs that they be shared for free with the broader community. “We’re not inventing anything new at all. We’re just applying open-source principles to diversity, equity, and inclusion,” she says. GitHub’s influence over open source may be large, but it is not the only group working to get maintainers paid and expand open-source participation. The Software Freedom Conservancy’s Outreachy diversity initiative offers paid internships ; as of 2019, 92% of past Outreachy interns have identified as women and 64% as people of color. Open-source fundraising platforms like Open Collective and Tidelift have also emerged to help maintainers tap into resources. The philanthropic world is stepping up too. The Ford Foundation, the Sloan Foundation, Omidyar Network , and the Chan Zuckerberg Initiative, as well as smaller organizations like Code for Science and Society, have all recently begun or expanded their efforts to support open-source research, contributors, and projects—including specific efforts promoting inclusion and diversity. Govind Shivkumar from Omidyar Network told MIT Technology Review that philanthropy is well positioned to establish funding architecture that could help prove out open-source projects, making them less risky prospects for future governmental funding. In fact, research supported by the Ford Foundation’s Digital Infrastructure Fund contributed to Germany’s recent creation of a national fund for open digital infrastructure. Momentum has also been building in the US. In 2016 the White House began requiring at least 20% of government-­developed software to be open source. Last year’s Securing Open Source Software Act passed with bipartisan support, establishing a framework for attention and investment at the federal level toward making open-source software stronger and more secure. The fast-approaching future Open source contributes valuable practices and tools, but it may also offer a competitive advantage over proprietary efforts. A document leaked in May from Google argued that open-source communities had pushed, tested, integrated, and expanded the capabilities of large language models more thoroughly than private efforts could’ve accomplished on their own: “Many of the new ideas [in AI development] are from ordinary people. The barrier to entry for training and experimentation has dropped from the total output of a major research organization to one person, an evening, and a beefy laptop.” The recently articulated concept of Time till Open Source Alternative (TTOSA)—the time between the release of a proprietary product and an open-source equivalent—also speaks to this advantage. One researcher estimated the average TTOSA to be seven years but noted that the process has been speeding up thanks to easy-to-use services like GitHub. At the same time, much of our modern world now relies on underfunded and rapidly expanding digital infrastructure. There has long been an assumption within open source that bugs can be identified and solved quickly by the “many eyes” of a wide community—and indeed this can be true. But when open-source software affects millions of users and its maintenance is handled by handfuls of underpaid individuals, the weight can be too much for the system to bear. In 2021, a security vulnerability in a popular open-source Apache library exposed an estimated hundreds of millions of devices to hacking attacks. Major players across the industry were affected, and large parts of the internet went down. The vulnerability’s lasting impact is hard to quantify even now. Related Story Volunteer-run projects like Log4J keep the internet running. The result is unsustainable burnout, and a national security risk when they go wrong. Other risks emerge from open-source development without the support of ethical guardrails. Proprietary efforts like Google’s Bard and OpenAI’s ChatGPT have demonstrated that AI can perpetuate existing biases and may even cause harm —while also not providing the transparency that could help a larger community audit the technology, improve it, and learn from its mistakes. But allowing anyone to use, modify, and distribute AI models and technology could accelerate their misuse. One week after Meta began granting access to its AI model LLaMA, the package leaked onto 4chan , a platform known for spreading misinformation. LLaMA 2, a new model released in July, is fully open to the public, but the company has not disclosed its training data as is typical in open-source projects—putting it somewhere in between open and closed by some definitions, but decidedly not open by OSI’s. (OpenAI is reportedly working on an open-source model as well but has not made a formal announcement.) “There are always trade-offs in the decisions you make in technology,” says Margaret Mitchell, chief ethics scientist at Hugging Face. “I can’t just be wholeheartedly supportive of open source in all cases without any nuances or caveats.” Mitchell and her team have been working on open-source tools to help communities safeguard their work, such as gating mechanisms to allow collaboration only at the project owner’s discretion, and “model cards” that detail a model’s potential biases and social impacts—information researchers and the public can take into consideration when choosing which models to work with. Open-source software has come a long way since its rebellious roots. But carrying it forward and making it into a movement that fully reflects the values of openness, reciprocity, and access will require careful consideration, financial and community investment, and the movement’s characteristic process of self-improvement through collaboration. As the modern world becomes more dispersed and diverse, the skill sets required to work asynchronously with different groups of people and technologies toward a common goal are only growing more essential. At this rate, 40 years from now technology might look more open than ever—and the world may be better for it. Rebecca Ackermann is a writer, designer, and artist based in San Francisco. hide by Rebecca Ackermann Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Computing What’s next for the world’s fastest supercomputers Scientists have begun running experiments on Frontier, the world’s first official exascale machine, while facilities worldwide build other machines to join the ranks. By Sophia Chen archive page AI-powered 6G networks will reshape digital interactions The convergence of AI and communication technologies will create 6G networks that make hyperconnectivity and immersive experiences an everyday reality for consumers. By MIT Technology Review Insights archive page The power of green computing Sustainable computing practices have the power to both infuse operational efficiencies and greatly reduce energy consumption, says Jen Huffstetler, chief product sustainability officer at Intel. By MIT Technology Review Insights archive page How this Turing Award–winning researcher became a legendary academic advisor Theoretical computer scientist Manuel Blum has guided generations of graduate students into fruitful careers in the field. By Sheon Han archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Tech is broken—can collective action fix it? | MIT Technology Review"

"https://www.technologyreview.com/2023/08/16/1077490/collective-action-tech-work"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Tech is broken—can collective action fix it? With Collective Action School, Xiaowei Wang hopes to redefine what it means to work in tech. By Patrick Sisson archive page Christie Hemm Klok For Silicon Valley venture capitalists and founders, any inconvenience big or small is a problem to be solved—even death itself. And a new genre of products and services known as “death tech,” intended to help the bereaved and comfort the suffering, shows that the tech industry will try to address literally anything with an app. Xiaowei Wang, a technologist, author, and organizer based in Oakland, California, finds that disturbing. “It’s so gross to view people like that—to see situations and natural facts of life like dying as problems,” Wang said during lunch and beers on the back patio of an Oakland brewery in late March. To research a forthcoming book on the use of tech in end-of-life care, Wang has trained as a “death doula” and will soon start working at a hospice. This approach to exploring technology, grounded in its personal and political implications, exemplifies a wider vision for fellow tech workers and the industry at large—a desire that it grant more power and agency to those with diverse backgrounds, become more equitable instead of extractive, and aim to reduce structural inequalities rather than seeking to enrich shareholders. To realize this vision, Wang has launched a collaborative learning project called Collective Action School in which tech workers can begin to confront their own impact on the world. The hope is to promote more labor organizing within the industry and empower workers who may feel intimidated to challenge gigantic corporations. Wang came to prominence as an editor at Logic magazine, an independent publication created in 2016 amid early Trump-era anxiety and concerns about the growing powers of technology. Dismissing utopian narratives of progress for prescient analysis of tech’s true role in widening inequity and concentrating political power, the founders—who also included Ben Tarnoff, Jim Fingal, Christa Hartsock, and Moira Weigel—vowed to stop having “stupid conversations about important things.” (In January, it was relaunched as “the first Black, Asian, and Queer tech magazine,” with Wang and J. Khadijah Abdurahman as co-editors.) Collective Action School, initially known as Logic School, is an outgrowth of the magazine. It’s emerged at a time when scandals and layoffs in the tech industry, combined with crypto’s troubles and new concerns about bias in AI , have made Big Tech’s failings all the more visible. In courses offered via Zoom, Wang and other instructors guide roughly two dozen tech workers, coders, and project managers through texts on labor organizing, intersectional feminist theory, and the political and economic implications of Big Tech. Its second cohort has now completed the program At our lunch, Wang was joined by three former students who helped run that last session: Derrick Carr, a senior software engineer; Emily Chao, a former trust and safety engineer at Twitter; and Yindi Pei, a UX designer. All shared a desire to create something that could lead to more concrete change than existing corporate employee resource groups, which they say often seem constrained and limited. And while Big Tech may obsess over charismatic founders, Collective Action School runs in a collective fashion. “I enjoy operating under the radar,” Wang said. Wang, who uses the pronoun “they,” moved from China to Somerville, Massachusetts, in 1990, at age four. Drawn to science and technology at a young age, they made friends in early online chat rooms and built rockets and studied oceanography at science camps. They also started questioning social norms early on; their mom tells of getting a call from the middle school principal, explaining that Wang had started a petition for a gender-inclusive class dress code. Years later, they enrolled at Harvard to study design and landscape architecture—at one point lofting a kite over the skies in Beijing to track pollution levels. A few years after graduating in 2008, Wang moved to the Bay Area. They worked at the nonprofit Meedan Labs, which develops open-source tools for journalists, and the mapping software company Mapbox, a rapidly scaling “rocket ship” where an employee—sometimes Wang—had to be on call, often overnight, to patch any broken code. Unsatisfied, Wang left in 2017 to focus on writing, speaking, and research, earning a PhD in geography at Berkeley. Related Story A record number of tech worker unions formed in the US last year. They’re part of a global effort. “The person who did my [Mapbox] exit interview told me, ‘You have this problem where you see injustice and you can’t stand it,’” Wang says. “She told me, ‘Sometimes you need to put that to bed if you want to stay in this industry.’ I can’t.” Many in tech, Wang says, have a fundamental belief in constant improvement through corporate innovation; for these people, technology means “you push a button and something in your life is solved.” But Wang, who practices Buddhism and reads tarot cards, sees things differently, believing that life is all about natural cycles humans can’t control and should accept with humility. For Wang, tech can be rural communities hacking open-source software, or simply something that brings pure joy. At Logic, Wang penned a popular column, Letter from Shenzhen , which included scenes from their family’s hometown of ​​Guangzhou, China, and the explosion of innovation in the country. It led to a book titled Blockchain Chicken Farm : And Other Stories of Tech in China’s Countryside , a striking exploration of technology’s impact on rural China. During the book editing process, Wang went on a Buddhist retreat, where a teacher remarked that we’re all “ looking at the sky through a straw ,” limited to our own small portholes of perception. This insight, says Wang, helped frame the final draft. But it also became a metaphor for an entire approach to research and writing on technology: focused, careful consideration of many viewpoints, and the capacity to imagine something better. Collective Action School, funded in part by the Omidyar Network and a grant from the arts and coding nonprofit Processing Foundation, came together in 2020 as tech worker activism was on the rise. Kickstarter employees’ union drive in 2020 was followed by efforts at Alphabet , Amazon, and Apple, as well as industry-wide campaigns such as Collective Action in Tech (led in part by former Logic editor Tarnoff) and the Tech Workers Coalition. But because Wang avoids the spotlight and believes that only strong communities can remedy the tech industry’s ills, the school is organized in a more experimental way. Collective Action School offers an antithesis to the “golden ticket” mentality of tech work, with an approach that’s more focused on collective action and culture. Each cohort begins with a “week zero” meeting to get acquainted as a group. Then, for 13 weeks, participants attend sessions covering labor movements, the political economy of innovation, and the impact of technology on marginalized groups. The funding covers all tuition costs for all students. As Pei, one of the co-organizers, puts it, the school offers an antithesis to the “golden ticket” mentality of tech work, with an approach that’s more focused on collective action and culture. Each week, participants read from a lengthy syllabus and welcome a guest speaker. Past guests include Clarissa Redwine from the Kickstarter union’s oral history project, former Google employees Alex Hanna and Timnit Gebru of the Distributed AI Research Institute, and Erin McElroy, cofounder of the Anti-Eviction Mapping Project. Then they work on a final project; one of the first was Looking Glass , which used augmented reality to highlight the lost Black history of Pittsburgh. For developing it, creator Adrian Jones was named the school’s “community technologist,” a role that comes with a one-year grant to expand the idea. Chao, who formerly worked for Twitter, released a zine about trust and safety issues, and Pei has been working on an affordable housing website for San Francisco. The organizers see Collective Action School as a community-building project, and open-source syllabus, that can grow with each new cohort. Eventually, the aim is to expand the reach of the school with chapters based in other areas, adding in-person meetings and creating a larger network of workers sharing similar values and aims. That strategy fills a need within larger tech and labor organizing, says Gershom Bazerman, who volunteers with the Tech Workers Coalition and Emergency Workplace Organizing Committee. Tech workers have long been told they’re unique, but recent political fights between workers and leadership—with employees pushing back against contributing to projects used by the US military or immigration enforcement—have set off a wave of ground-up organizing informed by social concerns. Groups like Collective Action School can be a “bridge” between workers seeking such change. While the readings and interactions aren’t creating a utopia, they are creating a space for students to learn, meet, and commit to more change. Wang hopes they find solidarity and, ideally, bring these ideas and experience back to their companies and coworkers (or find the resources and momentum to move to a job or field more aligned with their values). Some in this year’s cohort live and work in the Global South and have faced layoffs, so classmates created a cost-of-living support fund to help. Carr has called the experience an “antidote to a specific accumulated toxin” that comes from working in Big Tech. That may be true, but Collective Action School, along with other recent organizing efforts, also sets out to redefine the experience of working within the industry. “We’re not saying we’re making the perfect safe learning space,” says Wang. “We had a container in which we could have fun, learn from each other, and then grow. I think that’s really rare and special. It’s like committing to each other.” Patrick Sisson, a Chicago expat living in Los Angeles, covers technology and urbanism. hide by Patrick Sisson Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Inside the messy ethics of making war with machines | MIT Technology Review"

"https://www.technologyreview.com/2023/08/16/1077386/war-machines"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Inside the messy ethics of making war with machines AI is making its way into decision-making in battle. Who’s to blame when something goes wrong? By Arthur Holland Michel archive page Yoshi Sodeoka In a near-future war—one that might begin tomorrow, for all we know—a soldier takes up a shooting position on an empty rooftop. His unit has been fighting through the city block by block. It feels as if enemies could be lying in silent wait behind every corner, ready to rain fire upon their marks the moment they have a shot. Through his gunsight, the soldier scans the windows of a nearby building. He notices fresh laundry hanging from the balconies. Word comes in over the radio that his team is about to move across an open patch of ground below. As they head out, a red bounding box appears in the top left corner of the gunsight. The device’s computer vision system has flagged a potential target—a silhouetted figure in a window is drawing up, it seems, to take a shot. The soldier doesn’t have a clear view, but in his experience the system has a superhuman capacity to pick up the faintest tell of an enemy. So he sets his crosshair upon the box and prepares to squeeze the trigger. In different war, also possibly just over the horizon, a commander stands before a bank of monitors. An alert appears from a chatbot. It brings news that satellites have picked up a truck entering a certain city block that has been designated as a possible staging area for enemy rocket launches. The chatbot has already advised an artillery unit, which it calculates as having the highest estimated “kill probability,” to take aim at the truck and stand by. According to the chatbot, none of the nearby buildings is a civilian structure, though it notes that the determination has yet to be corroborated manually. A drone, which had been dispatched by the system for a closer look, arrives on scene. Its video shows the truck backing into a narrow passage between two compounds. The opportunity to take the shot is rapidly coming to a close. For the commander, everything now falls silent. The chaos, the uncertainty, the cacophony—all reduced to the sound of a ticking clock and the sight of a single glowing button: “APPROVE FIRE ORDER.” To pull the trigger—or, as the case may be, not to pull it. To hit the button, or to hold off. Legally—and ethically—the role of the soldier’s decision in matters of life and death is preeminent and indispensable. Fundamentally, it is these decisions that define the human act of war. Related Story Automation can help us make hard choices, but it can’t do it alone. It should be of little surprise, then, that states and civil society have taken up the question of intelligent autonomous weapons—weapons that can select and fire upon targets without any human input—as a matter of serious concern. In May, after close to a decade of discussions, parties to the UN’s Convention on Certain Conventional Weapons agreed, among other recommendations, that militaries using them probably need to “limit the duration, geographical scope, and scale of the operation” to comply with the laws of war. The line was nonbinding, but it was at least an acknowledgment that a human has to play a part—somewhere, sometime—in the immediate process leading up to a killing. But intelligent autonomous weapons that fully displace human decision-making have (likely) yet to see real-world use. Even the “autonomous” drones and ships fielded by the US and other powers are used under close human supervision. Meanwhile, intelligent systems that merely guide the hand that pulls the trigger have been gaining purchase in the warmaker’s tool kit. And they’ve quietly become sophisticated enough to raise novel questions—ones that are trickier to answer than the well-­covered wrangles over killer robots and, with each passing day, more urgent: What does it mean when a decision is only part human and part machine? And when, if ever, is it ethical for that decision to be a decision to kill? For a long time, the idea of supporting a human decision by computerized means wasn’t such a controversial prospect. Retired Air Force lieutenant general Jack Shanahan says the radar on the F4 Phantom fighter jet he flew in the 1980s was a decision aid of sorts. It alerted him to the presence of other aircraft, he told me, so that he could figure out what to do about them. But to say that the crew and the radar were coequal accomplices would be a stretch. That has all begun to change. “What we’re seeing now, at least in the way that I see this, is a transition to a world [in] which you need to have humans and machines … operating in some sort of team,” says Shanahan. The rise of machine learning, in particular, has set off a paradigm shift in how militaries use computers to help shape the crucial decisions of warfare—up to, and including, the ultimate decision. Shanahan was the first director of Project Maven, a Pentagon program that developed target recognition algorithms for video footage from drones. The project, which kicked off a new era of American military AI, was launched in 2017 after a study concluded that “deep learning algorithms can perform at near-­human levels.” (It also sparked controversy—in 2018, more than 3,000 Google employees signed a letter of protest against the company’s involvement in the project.) With machine-learning-based decision tools, “you have more apparent competency, more breadth” than earlier tools afforded, says Matt Turek, deputy director of the Information Innovation Office at the Defense Advanced Research Projects Agency. “And perhaps a tendency, as a result, to turn over more decision-making to them.” A soldier on the lookout for enemy snipers might, for example, do so through the Assault Rifle Combat Application System, a gunsight sold by the Israeli defense firm Elbit Systems. According to a company spec sheet, the “AI-powered” device is capable of “human target detection” at a range of more than 600 yards, and human target “identification” ( presumably, discerning whether a person is someone who could be shot ) at about the length of a football field. Anna Ahronheim-Cohen, a spokesperson for the company, told MIT Technology Review, “The system has already been tested in real-time scenarios by fighting infantry soldiers.” Another gunsight, built by the company Smartshooter, is advertised as having similar capabilities. According to the company’s website, it can also be packaged into a remote-controlled machine gun like the one that Israeli agents used to assassinate the Iranian nuclear scientist Mohsen Fakhrizadeh in 2020. Decision support tools that sit at a greater remove from the battlefield can be just as decisive. The Pentagon appears to have used AI in the sequence of intelligence analyses and decisions leading up to a potential strike, a process known as a kill chain—though it has been cagey on the details. In response to questions from MIT Technology Review, Laura McAndrews, an Air Force spokesperson, wrote that the service “is utilizing a human-­machine teaming approach.” The range of judgment calls that go into military decision-making is vast. And it doesn’t always take artificial super-intelligence to dispense with them by automated means. Other countries are more openly experimenting with such automation. Shortly after the Israel-Palestine conflict in 2021, the Israel Defense Forces said it had used what it described as AI tools to alert troops of imminent attacks and to propose targets for operations. The Ukrainian army uses a program, GIS Arta, that pairs each known Russian target on the battlefield with the artillery unit that is, according to the algorithm, best placed to shoot at it. A report by The Times, a British newspaper, likened it to Uber’s algorithm for pairing drivers and riders, noting that it significantly reduces the time between the detection of a target and the moment that target finds itself under a barrage of firepower. Before the Ukrainians had GIS Arta, that process took 20 minutes. Now it reportedly takes one. Russia claims to have its own command-and-control system with what it calls artificial intelligence, but it has shared few technical details. Gregory Allen, the director of the Wadhwani Center for AI and Advanced Technologies and one of the architects of the Pentagon’s current AI policies, told me it’s important to take some of these claims with a pinch of salt. He says some of Russia’s supposed military AI is “stuff that everyone has been doing for decades,” and he calls GIS Arta “just traditional software.” The range of judgment calls that go into military decision-making, however, is vast. And it doesn’t always take artificial super-­intelligence to dispense with them by automated means. There are tools for predicting enemy troop movements, tools for figuring out how to take out a given target, and tools to estimate how much collateral harm is likely to befall any nearby civilians. None of these contrivances could be called a killer robot. But the technology is not without its perils. Like any complex computer, an AI-based tool might glitch in unusual and unpredictable ways; it’s not clear that the human involved will always be able to know when the answers on the screen are right or wrong. In their relentless efficiency, these tools may also not leave enough time and space for humans to determine if what they’re doing is legal. In some areas, they could perform at such superhuman levels that something ineffable about the act of war could be lost entirely. Eventually militaries plan to use machine intelligence to stitch many of these individual instruments into a single automated network that links every weapon, commander, and soldier to every other. Not a kill chain, but—as the Pentagon has begun to call it—a kill web. In these webs, it’s not clear whether the human’s decision is, in fact, very much of a decision at all. Rafael, an Israeli defense giant, has already sold one such product, Fire Weaver, to the IDF (it has also demonstrated it to the US Department of Defense and the German military). According to company materials, Fire Weaver finds enemy positions, notifies the unit that it calculates as being best placed to fire on them, and even sets a crosshair on the target directly in that unit’s weapon sights. The human’s role, according to one video of the software, is to choose between two buttons: “Approve” and “Abort.” Let’s say that the silhouette in the window was not a soldier, but a child. Imagine that the truck was not delivering warheads to the enemy, but water pails to a home. Of the DoD’s five “ ethical principles for artificial intelligence ,” which are phrased as qualities, the one that’s always listed first is “Responsible.” In practice, this means that when things go wrong, someone—a human, not a machine—has got to hold the bag. Of course, the principle of responsibility long predates the onset of artificially intelligent machines. All the laws and mores of war would be meaningless without the fundamental common understanding that every deliberate act in the fight is always on someone. But with the prospect of computers taking on all manner of sophisticated new roles, the age-old precept has newfound resonance. Of the Department of Defense’s 5 “ethical principles for artificial intelligence,” which are phrased as qualities, the one that’s always listed first is “Responsible.” “Now for me, and for most people I ever knew in uniform, this was core to who we were as commanders: that somebody ultimately will be held responsible,” says Shanahan, who after Maven became the inaugural director of the Pentagon’s Joint Artificial Intelligence Center and oversaw the development of the AI ethical principles. This is why a human hand must squeeze the trigger, why a human hand must click “Approve.” If a computer sets its sights upon the wrong target, and the soldier squeezes the trigger anyway, that’s on the soldier. “If a human does something that leads to an accident with the machine—say, dropping a weapon where it shouldn’t have—that’s still a human’s decision that was made,” Shanahan says. But accidents happen. And this is where things get tricky. Modern militaries have spent hundreds of years figuring out how to differentiate the unavoidable, blameless tragedies of warfare from acts of malign intent, misdirected fury, or gross negligence. Even now, this remains a difficult task. Outsourcing a part of human agency and judgment to algorithms built, in many cases, around the mathematical principle of optimization will challenge all this law and doctrine in a fundamentally new way, says Courtney Bowman, global director of privacy and civil liberties engineering at Palantir, a US-headquartered firm that builds data management software for militaries, governments, and large companies. “It’s a rupture. It’s disruptive,” Bowman says. “It requires a new ethical construct to be able to make sound decisions.” This year, in a move that was inevitable in the age of ChatGPT, Palantir announced that it is developing software called the Artificial Intelligence Platform, which allows for the integration of large language models into the company’s military products. In a demo of AIP posted to YouTube this spring, the platform alerts the user to a potentially threatening enemy movement. It then suggests that a drone be sent for a closer look, proposes three possible plans to intercept the offending force, and maps out an optimal route for the selected attack team to reach them. And yet even with a machine capable of such apparent cleverness, militaries won’t want the user to blindly trust its every suggestion. If the human presses only one button in a kill chain, it probably should not be the “I believe” button, as a concerned but anonymous Army operative once put it in a DoD war game in 2019. In a program called Urban Reconnaissance through Supervised Autonomy (URSA), DARPA built a system that enabled robots and drones to act as forward observers for platoons in urban operations. After input from the project’s advisory group on ethical and legal issues, it was decided that the software would only ever designate people as “persons of interest.” Even though the purpose of the technology was to help root out ambushes, it would never go so far as to label anyone as a “threat.” This, it was hoped, would stop a soldier from jumping to the wrong conclusion. It also had a legal rationale, according to Brian Williams, an adjunct research staff member at the Institute for Defense Analyses who led the advisory group. No court had positively asserted that a machine could legally designate a person a threat, he says. (Then again, he adds, no court had specifically found that it would be illegal, either, and he acknowledges that not all military operators would necessarily share his group’s cautious reading of the law.) According to Williams, DARPA initially wanted URSA to be able to autonomously discern a person’s intent; this feature too was scrapped at the group’s urging. Bowman says Palantir’s approach is to work “engineered inefficiencies” into “points in the decision-­making process where you actually do want to slow things down.” For example, a computer’s output that points to an enemy troop movement, he says, might require a user to seek out a second corroborating source of intelligence before proceeding with an action (in the video, the Artificial Intelligence Platform does not appear to do this). “If people of interest are identified on a screen as red dots, that’s going to have a different subconscious implication than if people of interest are identified on a screen as little happy faces.” In the case of AIP, Bowman says the idea is to present the information in such a way “that the viewer understands, the analyst understands, this is only a suggestion.” In practice, protecting human judgment from the sway of a beguilingly smart machine could come down to small details of graphic design. “If people of interest are identified on a screen as red dots, that’s going to have a different subconscious implication than if people of interest are identified on a screen as little happy faces,” says Rebecca Crootof, a law professor at the University of Richmond, who has written extensively about the challenges of accountability in human-in-the-loop autonomous weapons. In some settings, however, soldiers might only want an “I believe” button. Originally, DARPA envisioned URSA as a wrist-worn device for soldiers on the front lines. “In the very first working group meeting, we said that’s not advisable,” Williams told me. The kind of engineered inefficiency necessary for responsible use just wouldn’t be practicable for users who have bullets whizzing by their ears. Instead, they built a computer system that sits with a dedicated operator, far behind the action. But some decision support systems are definitely designed for the kind of split-second decision-­making that happens right in the thick of it. The US Army has said that it has managed, in live tests, to shorten its own 20-minute targeting cycle to 20 seconds. Nor does the market seem to have embraced the spirit of restraint. In demo videos posted online, the bounding boxes for the computerized gunsights of both Elbit and Smartshooter are blood red. Other times, the computer will be right and the human will be wrong. If the soldier on the rooftop had second-guessed the gunsight, and it turned out that the silhouette was in fact an enemy sniper, his teammates could have paid a heavy price for his split second of hesitation. This is a different source of trouble, much less discussed but no less likely in real-world combat. And it puts the human in something of a pickle. Soldiers will be told to treat their digital assistants with enough mistrust to safeguard the sanctity of their judgment. But with machines that are often right, this same reluctance to defer to the computer can itself become a point of avertable failure. Aviation history has no shortage of cases where a human pilot’s refusal to heed the machine led to catastrophe. These (usually perished) souls have not been looked upon kindly by investigators seeking to explain the tragedy. Carol J. Smith, a senior research scientist at Carnegie Mellon University’s Software Engineering Institute who helped craft responsible AI guidelines for the DoD’s Defense Innovation Unit, doesn’t see an issue: “If the person in that moment feels that the decision is wrong, they’re making it their call, and they’re going to have to face the consequences.” For others, this is a wicked ethical conundrum. The scholar M.C. Elish has suggested that a human who is placed in this kind of impossible loop could end up serving as what she calls a “moral crumple zone.” In the event of an accident—regardless of whether the human was wrong, the computer was wrong, or they were wrong together—the person who made the “decision” will absorb the blame and protect everyone else along the chain of command from the full impact of accountability. In an essay, Smith wrote that the “lowest-paid person” should not be “saddled with this responsibility,” and neither should “the highest-paid person.” Instead, she told me, the responsibility should be spread among everyone involved, and the introduction of AI should not change anything about that responsibility. In practice, this is harder than it sounds. Crootof points out that even today, “there’s not a whole lot of responsibility for accidents in war.” As AI tools become larger and more complex, and as kill chains become shorter and more web-like, finding the right people to blame is going to become an even more labyrinthine task. Those who write these tools, and the companies they work for, aren’t likely to take the fall. Building AI software is a lengthy, iterative process, often drawing from open-source code, which stands at a distant remove from the actual material facts of metal piercing flesh. And barring any significant changes to US law, defense contractors are generally protected from liability anyway, says Crootof. Related Story Companies say they want ethical AI. But those working in the field say that ambition comes at their expense. Any bid for accountability at the upper rungs of command, meanwhile, would likely find itself stymied by the heavy veil of government classification that tends to cloak most AI decision support tools and the manner in which they are used. The US Air Force has not been forthcoming about whether its AI has even seen real-world use. Shanahan says Maven’s AI models were deployed for intelligence analysis soon after the project launched, and in 2021 the secretary of the Air Force said that “AI algorithms” had recently been applied “for the first time to a live operational kill chain,” with an Air Force spokesperson at the time adding that these tools were available in intelligence centers across the globe “whenever needed.” But Laura McAndrews, the Air Force spokesperson, saidthat in fact these algorithms “were not applied in a live, operational kill chain” and declined to detail any other algorithms that may, or may not, have been used since. The real story might remain shrouded for years. In 2018, the Pentagon issued a determination that exempts Project Maven from Freedom of Information requests. Last year, it handed the entire program to the National Geospatial-Intelligence Agency,which is responsible for processing ​America’s vast intake of secret aerial surveillance. Responding to questions about whether the algorithms are used in kill chains, Robbin Brooks, an NGA spokesperson, told MIT Technology Review, “We can’t speak to specifics of how and where Maven is used.” In one sense, what’s new here is also old. We routinely place our safety—indeed, our entire existence as a species—in the hands of other people. Those decision-­makers defer, in turn, to machines that they do not entirely comprehend. In an exquisite essay on automation published in 2018, at a time when operational AI-enabled decision support was still a rarity, former Navy secretary Richard Danzig pointed out that if a president “decides” to order a nuclear strike, it will not be because anyone has looked out the window of the Oval Office and seen enemy missiles raining down on DC but, rather, because those missiles have been detected, tracked, and identified—one hopes correctly—by algorithms in the air defense network. As in the case of a commander who calls in an artillery strike on the advice of a chatbot, or a rifleman who pulls the trigger at the mere sight of a red bounding box, “the most that can be said is that ‘a human being is involved,’” Danzig wrote. “This is a common situation in the modern age,” he wrote. “Human decisionmakers are riders traveling across obscured terrain with little or no ability to assess the powerful beasts that carry and guide them.” There can be an alarming streak of defeatism among the people responsible for making sure that these beasts don’t end up eating us. During a number of conversations I had while reporting this story, my interlocutor would land on a sobering note of acquiescence to the perpetual inevitability of death and destruction that, while tragic, cannot be pinned on any single human. War is messy, technologies fail in unpredictable ways, and that’s just that. “In warfighting,” says Bowman of Palantir, “[in] the application of any technology, let alone AI, there is some degree of harm that you’re trying to—that you have to accept, and the game is risk reduction.” It is possible, though not yet demonstrated, that bringing artificial intelligence to battle may mean fewer civilian casualties, as advocates often claim. But there could be a hidden cost to irrevocably conjoining human judgment and mathematical reasoning in those ultimate moments of war—a cost that extends beyond a simple, utilitarian bottom line. Maybe something just cannot be right, should not be right, about choosing the time and manner in which a person dies the way you hail a ride from Uber. To a machine, this might be suboptimal logic. But for certain humans, that’s the point. “One of the aspects of judgment, as a human capacity, is that it’s done in an open world,” says Lucy Suchman, a professor emerita of anthropology at Lancaster University, who has been writing about the quandaries of human-machine interaction for four decades. The parameters of life-and-death decisions—knowing the meaning of the fresh laundry hanging from a window while also wanting your teammates not to die—are “irreducibly qualitative,” she says. The chaos and the noise and the uncertainty, the weight of what is right and what is wrong in the midst of all that fury—not a whit of this can be defined in algorithmic terms. In matters of life and death, there is no computationally perfect outcome. “And that’s where the moral responsibility comes from,” she says. “You’re making a judgment.” The gunsight never pulls the trigger. The chatbot never pushes the button. But each time a machine takes on a new role that reduces the irreducible, we may be stepping a little closer to the moment when the act of killing is altogether more machine than human, when ethics becomes a formula and responsibility becomes little more than an abstraction. If we agree that we don’t want to let the machines take us all the way there, sooner or later we will have to ask ourselves: Where is the line? Arthur Holland Michel writes about technology. He is based in Barcelona and can be found, occasionally, in New York. This story originally stated that Mohsen Fakhrizadeh was killed in 2021. It has been updated with the correct year—2020. hide by Arthur Holland Michel Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. 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"The rise of the tech ethics congregation | MIT Technology Review"

"https://www.technologyreview.com/2023/08/15/1077369/tech-ethics-congregation"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts The rise of the tech ethics congregation In a world where tech has become a transcendent force, people are always looking for guidance. By Greg M. Epstein Matchull Summers Just before Christmas last year, a pastor preached a gospel of morals over money to several hundred members of his flock. Wearing a sport coat, angular glasses, and wired earbuds, he spoke animatedly into his laptop from his tiny glass office inside a co-working space, surrounded by six whiteboards filled with his feverish brainstorming. Sharing a scriptural parable familiar to many in his online audience—a group assembled from across 48 countries, many in the Global South—he explained why his congregation was undergoing dramatic growth in an age when the life of the spirit often struggles to compete with cold, hard, capitalism. “People have different sources of motivation [for getting involved in a community],” he sermonized. “It’s not only money. People actually have a deeper purpose in life.” Many of the thousands of people who’d been joining his community were taking the time and energy to do so “because they care about the human condition, and they care about the future of our democracy,” he argued. “That is not academic,” he continued. “That is not theoretical. That is talking about future generations, that’s talking about your happiness, that’s talking about how you see the world. This is big … a paradigm shift.” The leader in question was not an ordained minister, nor even a religious man. His increasingly popular community is not—technically—a church, synagogue, or temple. And the scripture he referenced wasn’t from the Bible. It was Microsoft Encarta vs. Wikipedia—the story of how a movement of self-­motivated volunteers defeated an army of corporate-funded professionals in a crusade to provide information, back in the bygone days of 2009. “If you’re young,” said the preacher, named David Ryan Polgar, “you’ll need to google it.” Polgar, 44, is the founder of All Tech Is Human , a nonprofit organization devoted to promoting ethics and responsibility in tech. Founded in 2018, ATIH is based in Manhattan but hosts a growing range of in-person programming—social mixers, mentoring opportunities, career fairs, and job-seeking resources—in several other cities across the US and beyond, reaching thousands. Such numbers would delight most churches. Like other kinds of congregations, ATIH focuses on relationship-­building: the staff invests much of its time, for example, in activities like curating its “Responsible Tech Organization” list, which names over 500 companies in which community members can get involved, and growing its responsible-tech talent pool, a list of nearly 1,400 individuals interested in careers in the field. Such programs, ATIH says, bring together many excellent but often disconnected initiatives, all in line with the ATIH mission “to tackle wicked tech & society issues and co-create a tech future aligned with the public interest.” The organization itself doesn’t often get explicitly political with op-eds or policy advocacy. Rather, All Tech Is Human’s underlying strategy is to quickly expand the “responsible-tech ecosystem.” In other words, its leaders believe there are large numbers of individuals in and around the technology world, often from marginalized backgrounds, who wish tech focused less on profits and more on being a force for ethics and justice. These people will be a powerful force, Polgar believes, if—as the counterculture icon Timothy Leary famously exhorted—they can “find the others.” If that sounds like reluctance to take sides on hot-button issues in tech policy, or to push for change directly, Polgar calls it an “agnostic” business model. And such a model has real strengths, including the ability to bring tech culture’s opposing tribes together under one big tent. Related Story Companies say they want ethical AI. But those working in the field say that ambition comes at their expense. But as we’ll see, attempts to stay above the fray can cause more problems than they solve. Meanwhile, All Tech Is Human is growing so fast, with over 5,000 members on its Slack channel as of this writing, that if it were a church, it would soon deserve the prefix “mega.” The group has also consistently impressed me with its inclusiveness: the volunteer and professional leadership of women and people of color is a point of major emphasis, and speaker lineups are among the most heterogeneous I’ve seen in any tech-related endeavor. Crowds, too, are full of young professionals from diverse backgrounds who participate in programs out of passion and curiosity, not hope of financial gain. Well, at least attendees don’t go to ATIH for direct financial gain; as is true with many successful religious congregations, the organization serves as an intentional incubator for professional networking. Still, having interviewed several dozen attendees, I’m convinced that many are hungry for communal support as they navigate a world in which tech has become a transcendent force, for better or worse. Growth has brought things to a turning point. ATIH now stands to receive millions of dollars—including funds from large foundations and tech philanthropist demigods who once ignored it. And Polgar now finds himself in a networking stratosphere with people like Canadian prime minister Justin Trudeau, among other prominent politicos. Will the once-humble community remain dedicated to centering people on the margins of tech culture? Or will monied interests make it harder to fight for the people Christian theologians might call “the least of these”? Techno-solutionism and related ideas can function as a kind of theology, justifying harm in the here and now with the promise of a sweet technological hereafter. I first started looking into ATIH in late 2021, while researching my forthcoming book Tech Agnostic: How Technology Became the World’s Most Powerful Religion, and Why It Desperately Needs a Reformation (MIT Press, 2024). The book project began because I’d been coming across a striking number of similarities between modern technological culture and religion, and the parallels felt important, given my background. I am a longtime (nonreligious) chaplain at both Harvard and MIT. After two decades immersed in the world of faith, back in 2018 I gave up on what had been my dream: to build a nonprofit “godless congregation” for the growing population of atheists, agnostics, and the religiously unaffiliated. Having started that work just before social media mavens like Mark Zuckerberg began to speak of “ connecting the world ,” I ultimately lost faith in the notion of building community around either religion or secularism when I realized that technology had overtaken both. Indeed, tech seems to be the dominant force in our economy, politics, and culture, not to mention a daily obsession that can increasingly look like an addiction from which some might plausibly seek the help of a higher power to recover. Tech culture has long been known for its prophets (Jobs, Gates, Musk, et al.), and tech as a whole is even increasingly oriented around moral and ethical messages, such as Google’s infamous “Don’t be evil.” The tech-as-religion comparison I’ve found myself drawing is often unflattering to tech leaders and institutions. Techno-solutionism and related ideas can function as a kind of theology, justifying harm in the here and now with the promise of a sweet technological hereafter; powerful CEOs and investors can form the center of a kind of priestly hierarchy, if not an outright caste system; high-tech weapons and surveillance systems seem to threaten an apocalypse of biblical proportions. When I discovered ATIH, I was pleasantly surprised to find a potentially positiveexample of the sort of dynamic I was describing. I am the sort of atheist who admits that certain features of religion can offer people real benefits. And ATIH seemed to be succeeding precisely because it genuinely operated like a secular, tech-­ethics-focused version of a religious congregation. “It does work that way,” Polgar acknowledged in February 2022, in the first of our several conversations on the topic. Since then, I’ve continued to admire ATIH’s communal and ethical spirit, while wondering whether communities devoted explicitly to tech ethics might just help bring about a reformation that saves tech from itself. Along with admiration, I’ve also sought to determine whether ATIH is worthy of our faith. Why a congregation? I discovered ATIH’s events in late 2021, first through the online Responsible Tech University Summit, a day-long program dedicated to exploring the intersections of tech ethics and campus life. (One of ATIH’s signature programs is its Responsible Tech University Network , which involves, among other things, a growing group of over 80 student “university ambassadors” who represent the organization on their campuses.) All the organization’s programs are organized around typical tech ethics themes, like “the business case for AI ethics,” but participants attend as much for the community as for the topic at hand. Sarah Husain, who’d worked on Twitter’s Trust and Safety team until it was eliminated by Elon Musk, told me at a May 2022 event that several colleagues in her field had spoken highly of ATIH, recommending she attend. Chana Deitsch, an undergraduate business student who participates in ATIH’s mentorship program, says it not only helps with job leads and reference letters but provides a sense of confidence and belonging. Alex Sarkissian, formerly a Deloitte consultant and now a Buddhist chaplaincy student, feels that the organization has potential “to be a kind of spiritual community for me in addition to my sangha [Buddhist congregation].” I’ve encountered mainly earnest and insightful members like these, people who come together for serious mutual support and ethical reflection and—non-trivially—funaround a cause I’ve come to hold dear. Granted, few ATIH participants, in my observation, hold C-level tech positions, which could undermine the organization’s claims that it has the ability to unite stakeholders toward effectual action … or perhaps it simply signifies a populism that could eventually put sympathizers in high places? Despite my skepticism toward both theology and technology, ATIH has often given me the feeling that I’ve found my own tech tribe. Growing pains Polgar is a nerdily charismatic former lawyer who has been developing the ideas and networks from which the organization sprouted for over a decade. As a young professor of business law at a couple of small, under-resourced colleges in Connecticut in the early 2010s, he began pondering the ethics of technologies that had recently emerged as dominant and ubiquitous forces across society and culture. Adopting the title “tech ethicist,” he began to write a series of missives on digital health and the idea of “co-creating a better tech future.” His 2017 Medium post “All Tech Is Human,” about how technology design should be informed by more than robotic rationality or utility, generated enthusiastic response and led to the formal founding of the organization a year later. The ATIH concept took a while to catch on, Polgar told me. He worked unpaid for three years and came “close to quitting.” But his background inspired perseverance. Born in 1979 in Cooperstown, New York, Polgar was a philosophical kid who admired Nikola Tesla and wanted to be an inventor. “Why can’t I start something big,” he remembers thinking back then, “even from a little place like this?” Despite their growing influence, Polgar and the organization continue to emphasize their outsider status. ATIH, he argues, is building its following in significant part with people who, for their interest in ethical approaches to technology, feel as unjustly ignored as he and many of his upstate peers felt in the shadow of New York City. ATIH’s model, says the organization’s head of partnerships, Sandra Khalil, is to offer not a “sage on the stage” but, rather, a “guide on the side.” Khalil, a veteran of the US Departments of State and Homeland Security, also came to the organization with an outsider’s pugnacity, feeling “severely underutilized” in previous roles as a non-lawyer intent on “challenging the status quo.” Polgar, however, hardly shrinks from opportunities to influence tech discourse, whether through media interviews with outlets like the BBC World News or by joining advisory boards like TikTok’s content advisory council. ATIH admits, in its “ Ten Principles ,” that it draws both from grassroots models, which it says “have ideas but often lack power,” and from “top-down” ones, which can “lack a diversity of ideas” but “have power.” The organization does not ask for or accept membership fees from participants, relying instead on major donations solicited by Polgar and his team, who control decision-making. There hasn’t seemed to be a significant call for more democracy—yet. The founder as a god? Part of why I’m insisting ATIH is a congregation is that the group assembled around Polgar demonstrates a religious zeal for organizing and relationship-building as tools for advancing positive moral values. Case in point: Rebekah Tweed, ATIH’s associate director, once worked in an actual church, as a youth pastor; now she applies a skill set my field calls “pastoral care” to creating mutually supportive space for ethically minded techies. In 2020, Tweed volunteered on ATIH’s first major public project, the Responsible Tech Guide, a crowdsourced document that highlighted the hundreds of people and institutions working in the field. After she formally joined the organization, it landed its first big-time donation: $300,000 over two years from the Ford Foundation, to pay her salary as well as Polgar’s. They were its first full-time employees. Polgar was repeatedly rebuffed in early attempts to recruit large gifts, but of late, the growing ATIH team has received significant support from sources including Melinda French Gates’s Pivotal Ventures and about half a million dollars each from Schmidt Futures (the philanthropic fund of former Google CEO Eric Schmidt) and the Patrick J. McGovern Foundation (yet another tech billionaire’s fortune). Can an organization that serves a truly inclusive audience afford to get in bed with Fortune 500 companies and/or multibillionaires who will inevitably be motivated by a desire to seem ethical? The question is: Can an organization that serves a truly inclusive audience, emphasizing humanity and ethics in its own name, afford to get in bed with Fortune 500 companies like Google and Microsoft and/or multibillionaires who will inevitably be motivated by a desire to seem ethical and responsible, even when they decidedly are not? Or rather, can it afford not to do so, when growth means the organization’s staff can grow (and earn a living wage)? And could such tensions someday cause a full-blown schism in the ATIH community? The potential challenges first came to light for me at a May 2022 summit in New York. For the first time in several large ATIH events I had personally observed, the meeting featured an invited speaker employed by one of the world’s largest tech companies: Harsha Bhatlapenumarthy, a governance manager at Meta and also a volunteer leader in a professional association called Trust and Safety. Bhatlapenumarthy—whose panel was called “Tech Policy & Social Media: Where are we headed?”—avoided addressing any of her employer’s recent controversies. Instead of offering any meaningful comment in response to Meta’s troubles over its handling of things from pro-anorexia content to election misinformation, she spoke only vaguely about its ethical responsibilities. The company, she said, was focused on “setting the content moderator up for success.” Which is an interesting way to describe a situation in which Meta had, for example, recently been sued for union busting and human trafficking by content moderators in Kenya. Several attendees were taken aback that Bhatlapenumarthy’s advocacy for her powerful employer went essentially unchallenged during the panel. Among them was Yael Eisenstat, Facebook’s former global head of election integrity operations for political advertising and the summit’s closing speaker. In a fireside chat immediately following the panel in which Bhatlapenumarthy participated, Eisenstat, who’d been a whistleblower against her former employer, eloquently dismissed Bhatlapenumarthy’s non-remarks. “I believe [Meta] doesn’t want this on their platform,” she said, referring to violent and deceptive content, “but they will not touch their business model.” Eisenstat added that she would feel “more encouraged” if companies would stop “holding up the founder as a god.” Eisenstat added to me later, by private message, that “sending a more junior-level employee to speak one-directionally about Meta’s vision of responsible tech is somewhat disingenuous.” In inviting such a speaker, couldn’t ATIH reasonably be understood to be implicated in the offense? If Bhatlapenumarthy’s presence as a seeming mouthpiece for Big Tech talking points had been an isolated incident, I might have ignored it. But a few months later, I found myself wondering if a concerning pattern was emerging. Digital Sunday school In September 2022, I attended Building a Better Tech Future for Children, an ATIH event cohosted with the Joan Ganz Cooney Center at Sesame Workshop, a nonprofit research and innovation lab associated with the legendary children’s TV show Sesame Street. This struck me as a shrewd partnership for ATIH: every congregation needs a Sunday school. A community organization aspiring to the advancement of humanity and the betterment of the world will inevitably turn its thoughts to educating the next generation according to its values. After a keynote from Elizabeth Milovidov, senior manager for digital child safety at the Lego Group, on designing digital experiences with children’s well-being in mind came a panel featuring speakers from influential players such as the Omidyar Network and TikTok, as well as young activists. The group discussed the risks and harms facing young people online, and the general tone was optimistic that various efforts to protect them would be successful, particularly if built upon one another. “Digital spaces can be a positive source in the lives of young people,” said the moderator, Mina Aslan. Related Story Technology is changing how we read—and that means we need to rethink how we teach. Also on the panel was Harvard Medical School professor Michael Rich, a self-proclaimed “mediatrician”—a portmanteau of “media’’ and “pediatrician.” Rich made good points—for example, stressing the importance of asking kids what they’re hoping for from tech, not just talking about the risks they confront. But one comment triggered my spider-sense: when he said that today’s tech is like his generation’s cigarettes, in that you can’t just tell kids “Don’t do it.” The analogy between tobacco and social media is at best a bizarre one to draw. Millions of young people became smokers not just through peer pressure, but because for decades, Big Tobacco’s whole business model was built on undue corporate influence and even outright lying, including paying influential doctors and scientists to downplay the death they dealt. Surely ATIH’s leadership would want to avoid any hint that such practices would be acceptable in tech? Tobacco eventually became among the most heavily regulated industries in history, with results including, famously, the US surgeon general’s warnings on tobacco ads and packages. Now the current surgeon general, Vivek Murthy, has warned there is “growing evidence” that social media is “associated with harm to young people’s mental health.” But on the panel (and in his commentary elsewhere), Rich only briefly acknowledged such potential harms, forgoing talk of regulating social media for the idea of cultivating “resilience” in the industry’s millions of young customers. To be clear, I agree with Rich that it is a losing strategy to expect young people to completely abstain from social media. But I fear that tech and our broader society alike are not taking nearly enough ethical responsibility for protecting children from what can be powerful engines of harm. And I was disappointed to see Rich’s relatively sanguine views not only expressed but centered at an ATIH meeting. How much responsibility? How much responsibility should a “responsible tech” organization like ATIH take—or not—for inviting speakers with corporate ties, especially when it is not fully open with its audience about such ties? How obligated is ATIH to publicly interrogate the conclusions of such speakers? Rich’s response to questions I’d asked after his panel was, essentially, that parents ought to channel their energies into making “better choices” around tech, which—conveniently for some of the doctor’s corporate sponsors—lays the responsibility for children’s safety on the parents instead of the tech industry. His lab, I later learned, raised nearly $6 million in 2022, at least partly through grants from Meta, TikTok, and Amazon. When TikTok CEO Shou Chew testified before the US Congress in March 2023, he cited Rich’s lab—and only Rich’s lab—as an example of how TikTok used science and medicine to protect minors. Does this represent a conflict of interest—and therefore a serious ethical failing on the part of both Rich and ATIH for platforming him? I don’t know. I do worry, though, that there’s something inhumane in Rich’s emphasis on building kids’ “resilience” rather than interrogating why they should have to be so resilient against tech in the first place. What kind of institution does ATIH want to be? One that pushes back against the powerful, or one that upholds a corporate-friendly version of diversity, allowing its wealthy sponsors to remain comfortable at (almost) all times? As the Gospel of Matthew says, no man (or organization of “humans”) can serve two masters. Asking around ATIH’s network about my concerns, I found ambivalence. “I do believe it is possible to do research sponsored by companies ethically,” said Justin Hendrix, an occasional ATIH participant and editor of Tech Policy Press, a wonky journal in which academics and others tend to critique established tech narratives. “But it is right to scrutinize it for signs of impropriety.” “I see your concern,” Polgar later told me when I asked him about my apprehensions. Raising his brow with a look of surprise when I wondered aloud whether Rich’s funding sources might have affected the commentary he offered for ATIH’s audience, Polgar made clear he did not agree with all the doctor’s views. He also admitted it is his “worst fear” that his organization might be co-opted by funding opportunities that make it harder “to be a speaker of truth.” “Don’t become a parody of yourself,” he said, seeming to turn the focus of his homily inward. Team human Several months after the Sesame Workshop event, I attended a crowded mixer at ATIH’s now-regular monthly venue, the Midtown Manhattan offices of the VC firm Betaworks, with a very different kind of speaker: the tech critic Douglas Rushkoff, a freethinker who has often spoken of the need for a kind of secular faith in our common humanity in the face of tech capitalism’s quasi-religious extremism. Polgar is a longtime admirer of his work. “All tech bros are human,” Rushkoff cracked, launching into an enthusiastically received talk. Fresh off a publicity tour for a book about tech billionaires buying luxury bunkers to escape a potential doomsday of their own making, Rushkoff provided a starkly antiauthoritarian contrast to the speakers I’d taken issue with at the earlier events. Ultimately, I don’t know whether ATIH will succeed in its attempts to serve what Rushkoff would call “team human” rather than becoming an accessory to the overwhelming wealth tech can generate by seeming to make humanity commodifiable and, ultimately, redundant. I do, however, continue to believe that building a more humane tech future will require communal support, because none of us can do it alone. I chose the theme of tech agnosticism for my book in part because I am often reminded that I truly don’t know—and neither do you—when or where tech’s enormous powers might actually do the good they purport to do. But I suspect we’re going to need a lot more of what Neil Postman’s 1992 book Technopoly , an early exploration of the theme of tech-as-­religion and a precursor to the techlash, called “loving resistance fighters.” While I lack prophetic abilities to know whether Polgar and co. will help spark such a resistance, the potential is genuinely there. In a participatory congregation, one can always worry about co-­option, as even Polgar himself admits he does; but isn’t it also the responsibility of each of us to actively help keep our communities accountable to their own ethical values? Let’s maintain our skepticism, while hoping the ethical tech congregation gives us continued reason to keep the faith. Greg M. Epstein serves as the humanist chaplain at Harvard University and MIT and as the convener for ethical life at MIT’s Office of Religious, Spiritual, and Ethical Life. hide by Greg M. Epstein Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Humans and technology Why embracing complexity is the real challenge in software today In the midst of industry discussions about productivity and automation, it’s all too easy to overlook the importance of properly reckoning with complexity. 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"What happened to microfinance company Kiva? | MIT Technology Review"

"https://www.technologyreview.com/2023/08/14/1077351/microfinance-money-making"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts What happened to the microfinance organization Kiva? A group of strikers argue that the organization seems more focused on making money than creating change. Are they right? By Mara Kardas-Nelson archive page Andrea D'Aquino One morning in August 2021, as she had nearly every morning for about a decade, Janice Smith opened her computer and went to Kiva.org, the website of the San Francisco–based nonprofit that helps everyday people make microloans to borrowers around the world. Smith, who lives in Elk River, Minnesota, scrolled through profiles of bakers in Mexico, tailors in Uganda, farmers in Albania. She loved the idea that, one $25 loan at a time, she could fund entrepreneurial ventures and help poor people help themselves. But on this particular morning, Smith noticed something different about Kiva’s website. It was suddenly harder to find key information, such as the estimated interest rate a borrower might be charged—information that had been easily accessible just the day before and felt essential in deciding who to lend to. She showed the page to her husband, Bill, who had also become a devoted Kiva lender. Puzzled, they reached out to other longtime lenders they knew. Together, the Kiva users combed through blog posts, press releases, and tax filings, but they couldn’t find a clear explanation of why the site looked so different. Instead, they learned about even bigger shifts—shifts that shocked them. Kiva connects people in wealthier communities with people in poorer ones through small, crowdfunded loans made to individuals through partner companies and organizations around the world. The individual Kiva lenders earn no interest; money is given to microfinance partners for free, and only the original amount is returned. Once lenders get their money back, they can choose to lend again and again. It’s a model that Kiva hopes will foster a perennial cycle of microfinance lending while requiring only a small outlay from each person. This had been the nonprofit’s bread and butter since its founding in 2005. But now, the Smiths wondered if things were starting to change. The Smiths and their fellow lenders learned that in 2019 the organization had begun charging fees to its lending partners. Kiva had long said it offered zero-interest funding to microfinance partners, but the Smiths learned that the recently instituted fees could reach 8%. They also learned about Kiva Capital, a new entity that allows large-scale investors— Google is one —to make big investments in microfinance companies and receive a financial return. The Smiths found this strange: thousands of everyday lenders like them had been offering loans return free for more than a decade. Why should Google now profit off a microfinance investment? Combined, Kiva’s top 10 executives made nearly $3.5 million in 2020. In 2021, nearly half of Kiva’s revenue went to staff salaries. The Kiva users noticed that the changes happened as compensation to Kiva’s top employees increased dramatically. In 2020, the CEO took home over $800,000. Combined, Kiva’s top 10 executives made nearly $3.5 million in 2020. In 2021, nearly half of Kiva’s revenue went to staff salaries. Considering all the changes, and the eye-popping executive compensation, “the word that kept coming up was ‘shady,’” Bill Smith told me. “Maybe what they did was legal,” he said, “but it doesn’t seem fully transparent.” He and Janice felt that the organization, which relied mostly on grants and donations to stay afloat, now seemed more focused on how to make money than how to create change. Kiva, on the other hand, says the changes are essential to reaching more borrowers. In an interview about these concerns, Kathy Guis, Kiva’s vice president of investments , told me, “All the decisions that Kiva has made and is now making are in support of our mission to expand financial access.” In 2021, the Smiths and nearly 200 other lenders launched a “lenders’ strike.” More than a dozen concerned lenders (as well as half a dozen Kiva staff members) spoke to me for this article. They have refused to lend another cent through Kiva, or donate to the organization’s operations, until the changes are clarified—and ideally reversed. When Kiva was founded in 2005, by Matt Flannery and Jessica Jackley , a worldwide craze for microfinance—sometimes called microcredit—was at its height. The UN had dubbed 2005 the “International Year of Microcredit” ; a year later, in 2006, Muhammad Yunus and the Grameen Bank he had founded in the 1980s won the Nobel Peace Prize for creating, in the words of the Nobel Committee, “economic and social development from below.” On a trip to East Africa, Flannery and Jackley had a lightbulb moment: Why not expand microfinance by helping relatively wealthy individuals in places like the US and Europe lend to relatively poor businesspeople in places like Tanzania and Kenya? They didn’t think the loans Kiva facilitated should come from grants or donations: the money, they reasoned, would then be limited, and eventually run out. Instead, small loans—as little as $25—would be fully repayable to lenders. Connecting wealthier individuals to poorer ones was the “peer-to-peer” part of Kiva’s model. The second part—the idea that funding would be sourced through the internet via the Kiva.org website—took inspiration from Silicon Valley. Flannery and another Kiva cofounder, Premal Shah, both worked in tech— Flannery for TiVo , Shah for PayPal. Kiva was one of the first crowdfunding platforms, launched ahead of popular sites like GoFundMe. Related Story Digital technology is poised to change our relationship with money and, for some countries, the ability to manage their economies. But Kiva is less direct than other crowdfunding sites. Although lenders “choose” borrowers through the website, flipping through profiles of dairy farmers and fruit sellers, money doesn’t go straight to them. Instead, the loans that pass through Kiva are bundled together and sent to one of the partnering microfinance institutions. After someone in the US selects, say, a female borrower in Mongolia, Kiva funds a microfinance organization there, which then lends to a woman who wants to set up a business. Even though the money takes a circuitous route, the premise of lending to an individual proved immensely effective. Stories about Armenian bakers and Moroccan bricklayers helped lenders like the Smiths feel connected to something larger, something with purpose and meaning. And because they got their money back, while the feel-good rewards were high, the stakes were low. “It’s a loan, not a donation,” the website still emphasizes today. The organization covered its operating expenses with funding from the US government and private foundations and companies, as well as donations from individual lenders, who could add a tip on top of their loan to support Kiva’s costs. This sense of individual connection and the focus on facilitating loans rather than donations was what initially drew Janice Smith. She first heard of microfinance through Bill Clinton’s book Giving , and then again through Oprah Winfrey—Kiva.org was included as one of “Oprah’s Favorite Things” in 2010. Smith was particularly enticed by the idea that she could re-lend the same $25 again and again: “I loved looking through borrower profiles and feeling like I was able to help specific people. Even when I realized that the money was going to a [microfinance lender]”—not directly to a borrower—“it still gave me a feeling of a one-on-one relationship with this person.” Kiva’s easy-to-use website and focus on repayments helped further popularize the idea of small loans to the poor. For many Americans, if they’ve heard of microfinance at all, it’s because they or a friend or family member have lent through the platform. As of 2023, according to a Kiva spokesperson, 2.4 million people from more than 190 countries have done so, ultimately reaching more than 5 million borrowers in 95 countries. The spokesperson also pointed to a 2022 study of 18,000 microfinance customers, 88% of whom said their quality of life had improved since accessing a loan or another financial service. A quarter said the loans and other services had increased their ability to invest and grow their business. But Kiva has also long faced criticism, especially when it comes to transparency. There was the obvious issue that the organization suggests a direct connection between Kiva.org users and individual borrowers featured on the site, a connection that does not actually exist. But there were also complaints that the interest rates borrowers pay were not disclosed. Although Kiva initially did not charge fees to the microfinance institutions it funneled money through, the loans to the individual borrowers do include interest. The institutions Kiva partners with use that to cover operational costs and, sometimes, make a profit. Critics were concerned about this lack of disclosure given that interest rates on microfinance loans can reach far into the double digits— for more than a decade , some have even soared above 100%. (Microlenders and their funders have long argued that interest rates are needed to make funding sustainable.) A Kiva spokesperson stressed that the website now mentions “average cost to borrower,” which is not the interest rate a borrower will pay but a rough approximation. Over the years, Kiva has focused on partnering with “impact-first” microfinance lenders—those that charge low interest rates or focus on loans for specific purposes, such as solar lights or farming. Critics also point to studies showing that microfinance has a limited impact on poverty, despite claims that the loans can be transformative for poor people. For those who remain concerned about microfinance overall, the clean, easy narrative Kiva promotes is a problem. By suggesting that someone like Janice Smith can “make a loan, change a life,” skeptics charge, the organization is effectively whitewashing a troubled industry accused of high-priced loans and harsh collection tactics that have reportedly led to suicides, land grabs , and a connection to child labor and indebted servitude. Over her years of lending through Kiva.org, Smith followed some of this criticism, but she says she was “sucked in” from her first loan. She was so won over by the mission and the method that she soon became, in her words, a “Kivaholic.” Lenders can choose to join “teams” to lend together, and in 2015 she launched one, called Together for Women. Eventually, the team would include nearly 2,500 Kiva lenders—including one who, she says, put his “whole retirement” into Kiva, totaling “millions of dollars.” Smith soon developed a steady routine. She would open her computer first thing in the morning, scroll through borrowers, and post the profiles of those she considered particularly needy to her growing team, encouraging support from other lenders. In 2020, several years into her “Kivaholicism,” Kiva invited team captains like her to join regular calls with its staff, a way to disseminate information to some of the most active members. At first, these calls were cordial. But in 2021, as lenders like Smith noticed changes that concerned them, the tone of some conversations changed. Lenders wanted to know why the information on Kiva’s website seemed less accessible. And then, when they didn’t get a clear answer, they pushed on everything else, too: the fees to microfinance partners, the CEO salaries. In 2021 Smith’s husband, Bill, became captain of a new team calling itself Lenders on Strike, which soon had nearly 200 concerned members. The name sent a clear message: “We’re gonna stop lending until you guys get your act together and address the stuff.” Even though they represented a small fraction of those who had lent through Kiva, the striking members had been involved for years, collectively lending millions of dollars—enough, they thought, to get Kiva’s attention. On the captains’ calls and in letters, the strikers were clear about a top concern: the fees now charged to microfinance institutions Kiva works with. Wouldn’t the fees make the loans more expensive to the borrowers? Individual Kiva.org lenders still expected only their original money back, with no return on top. If the money wasn’t going to them, where exactly would it be going? On one call, the Smiths recall, staffers explained that the fees were a way for Kiva to expand. Revenue from the fees—potentially millions of dollars—would go into Kiva’s overall operating budget, covering everything from new programs to site visits to staff salaries. Some lenders were disappointed to learn that loans don’t go directly to the borrowers featured on Kiva’s website. Instead, they are pooled together with others’ contributions and sent to partner institutions to distribute. But on a different call with striking lenders, they recall that Kiva’s Kathy Guis acknowledged that the fees could be bad for poor borrowers. The higher cost might be passed down to them; borrowers might see their own interest rates, sometimes already steep, rise even more. When I spoke to Guis in June 2023, she told me those at Kiva “haven’t observed” a rise in borrowers’ rates as a direct result of the fees. Because the organization essentially acts as a middleman, it would be hard to trace this. “Kiva is one among a number of funding sources,” Guis explained—often, in fact, a very small slice of a microlender’s overall funding. “And cost of funds is one among a number of factors that influence borrower pricing.” A Kiva spokesperson said the average fee is 2.53%, with fees of 8% charged on only a handful of “longer-­term, high-risk loans.” The strikers weren’t satisfied: it felt deeply unfair to have microfinance lenders, and maybe ultimately borrowers, pay for Kiva’s operations. More broadly, they took issue with new programs the revenue was being spent on. Kiva Capital, the new return-seeking investment arm that Google has participated in, was particularly concerning. Several strikers told me that it seemed strange, if not unethical, for an investor like Google to be able to make money off microfinance loans when everyday Kiva lenders had expected no return for more than a decade—a premise that Kiva had touted as key to its model. A Kiva spokesperson told me investors “are receiving a range of returns well below a commercial investor’s expectations for emerging-market debt investments,” but did not give details. Guis said that thanks in part to Kiva Capital, Kiva “reached 33% more borrowers and deployed 33% more capital in 2021.” Still, the Smiths and other striking lenders saw the program less as an expansion and more as a departure from the Kiva they had been supporting for years. Another key concern, strikers told me, is Kiva US , a separate program that offers zero-interest loans to small businesses domestically. Janice Smith had no fundamental problem with the affordable rates, but she found it odd that an American would be offered 0% interest while borrowers in poorer parts of the world were being charged up to 70%, according to the estimates posted on Kiva’s website. “I don’t see why poor people in Guatemala should basically be subsidizing relatively rich people here in Minnesota,” she told me. Guis disagreed, telling me, “I take issue with the idea that systematically marginalized communities in the US are less deserving.” She said that in 2022, nearly 80% of the businesses that received US loans were “owned by Black, Indigenous, and people of color.” After months of discussions, the strikers and Kiva staff found themselves at loggerheads. “They feel committed to fees as a revenue source, and we feel committed to the fact that it’s inappropriate,” Bill Smith told me. Guis stressed that Kiva had gone through many changes throughout its 18 years—the fees, Kiva Capital, and Kiva US being just a few. “You have to evolve,” she said. The fees and the returns-oriented Kiva Capital felt strange enough. But what really irked the Lenders on Strike was how much Kiva executives were being paid for overseeing those changes. Lenders wanted to know why, according to Kiva’s tax return , roughly $3.5 million had been spent on executive compensation in 2020—nearly double the amount a few years previously. Bill Smith and others I spoke to saw a strong correlation: at the same time Kiva was finding new ways to make money, Kiva’s leadership was bringing home more cash. The concerned lenders weren’t the only ones to see a connection. Several employees I spoke to pointed to questionable decisions made under the four-year tenure of Neville Crawley, who was named CEO in 2017 and left in 2021. Crawley made approximately $800,000 in 2020, his last full year at the organization, and took home just under $750,000 in 2021 , even though he left the position in the middle of the year. When I asked Kathy Guis why Crawley made so much for about six months of work, she said she couldn’t answer but would pass that question along to the board. Afterward, I received a written response that did not specifically address CEO compensation, instead noting in part, “As part of Kiva’s commitment to compensation best practices, we conduct regular org-wide compensation fairness research, administer salary surveys, and consult market data from reputable providers.” Chris Tsakalakis, who took over from Crawley, earned more than $350,000 in 2021 , for about half a year of work. (His full salary and that of Vishtal Ghotge, his successor and Kiva’s newest CEO, are not yet publicly available in Kiva’s tax filings, nor would Kiva release these numbers to us when we requested them.) In 2021 , nearly $20 million of Kiva’s $42 million in revenue went to salaries, benefits, and other compensation. According to the striking lenders, Kiva’s board explained that as a San Francisco–based organization, it needed to attract top talent in a field, and a city, dominated by tech, finance, and nonprofits. The last three CEOs have had a background in business and/or tech; Kiva’s board is stacked with those working at the intersection of tech, business, and finance and headed by Julie Hanna, an early investor in Lyft and other Silicon Valley companies. This was especially necessary, the board argued, as Kiva began to launch new programs like Kiva Capital, as well as Protocol, a blockchain-­enabled credit bureau launched in Sierra Leone in 2018 and then closed in 2022. Someone taking home nearly a million dollars a year was steering the ship, not the lenders and their $25 loans. The Smiths and other striking lenders didn’t buy the rationale. The leaders of other microlenders—including Kiva partners—make far less. For example, the president and CEO of BRAC USA, a Kiva partner and one of the largest nonprofits in the world, made just over $300,00 in 2020—not only less than what Kiva’s CEO earns, but also below what Kiva’s general counsel, chief investment officer, chief strategy officer, executive vice president of engineering, and chief officer for strategic partnerships were paid in 2021, according to public filings. Julie Hanna, the executive chair of Kiva’s board, made $140,000 for working 10 hours a week in 2021. Premal Shah, one of the founders, took home roughly $320,000 as “senior consultant” in 2020. Even among other nonprofits headquartered in expensive American cities, Kiva’s CEO salary is high. For example, the head of the Sierra Club, based in Oakland, made $500,000 in 2021. Meanwhile, the executive director of Doctors Without Borders USA, based in New York City, had a salary of $237,000 in 2020 , the same year that the Kiva top executive made roughly $800,000—despite 2020 revenue of $558 million, compared with Kiva’s $38 million. The striking lenders kept pushing—on calls, in letters, on message boards—and the board kept pushing back. They had given their rationale, about the salaries and all the other changes, and as one Kiva lender told me, it was clear “there would be no more conversation.” Several strikers I spoke to said it was the last straw. This was, they realized, no longer their Kiva. Someone taking home nearly a million dollars a year was steering the ship, not them and their $25 loans. The Kiva lenders’ strike is concentrated in Europe and North America. But I wanted to understand how the changes, particularly the new fees charged to microfinance lenders, were viewed by the microfinance organizations Kiva works with. So I spoke to Nurhayrah Sadava, CEO of VisionFund Mongolia, who told me she preferred the fees to the old Kiva model. Before the lending fees were introduced, money was lent from Kiva to microfinance organizations in US dollars. The partner organizations then paid the loan back in dollars too. Given high levels of inflation, instability, and currency fluctuations in poorer countries, that meant partners might effectively pay back more than they had taken out. Related Story In Kenya, and elsewhere in Africa, the rapid spread of smartphones and mobile money has come with a stubbornly persistent vice: online gambling. But with the fees, Sadava told me, Kiva now took on the currency risk, with partners paying a little more up front. Sadava saw this as a great deal, even if it looked “shady” to the striking lenders. What’s more, the fees—around 7% to 8% in the case of VisionFund Mongolia—were cheaper than the organization’s other options: their only alternatives were borrowing from microfinance investment funds primarily based in Europe, which charged roughly 20%, or another VisionFund Mongolia lender, which charges the organization 14.5%. Sadava told me that big international donors aren’t interested in funding their microfinance work. Given the context, VisionFund Mongolia was happy with the new arrangement. Sadava says the relatively low cost of capital allowed them to launch “resourcefulness loans” for poor businesswomen, who she says pay 3.4% a month. VisionFund Mongolia’s experience isn’t necessarily representative—it became a Kiva partner after the fees were instituted, and it works in a country where it is particularly difficult to find funding. Still, I was surprised by how resoundingly positive Sadava was about the new model, given the complaints I’d heard from dozens of aggrieved Kiva staffers and lenders. That got me thinking about something Hugh Sinclair, a longtime microfinance staffer and critic, told me a few years back: “The client of Kiva is the American who gets to feel good, not the poor person.” In a way, by designing the Kiva.org website primarily for the Western funder, not the faraway borrower, Kiva created the conditions for the lenders’ strike. For years, Kiva has encouraged the feeling of a personal connection between lenders and borrowers, a sense that through the organization an American can alter the trajectory of a life thousands of miles away. It’s not surprising, then, that the changes at Kiva felt like an affront. (One striker cried when he described how much faith he had put into Kiva, only for Kiva to make changes he saw as morally compromising.) They see Kiva as their baby. So they revolted. By designing the Kiva.org website primarily for the Western funder, not the faraway borrower, Kiva created the conditions for the lenders’ strike. Kiva now seems somewhat in limbo. It’s still advertising its old-school, anyone-­can-be-a-lender model on Kiva.org, while also making significant operational changes (a private investing arm, the promise of blockchain-enabled technology) that are explicitly inaccessible to everyday Americans—and employing high-flying CEOs with CVs and pedigrees that might feel distant, if not outright off-putting, to them. If Kiva’s core premise has been its accessibility to people like the Smiths, it is now actively undermining that premise, taking a chance that expansion through more complicated means will be better for microfinance than honing the simplistic image it’s been built on. Several of the striking lenders I spoke to were primarily concerned that the Kiva model had been altered into something they no longer recognized. But Janice Smith, and several others, had broader concerns: not just about Kiva, but about the direction the whole microfinance sector was taking. In confronting her own frustrations with Kiva, Smith reflected on criticisms she had previously dismissed. “I think it’s an industry where, depending on who’s running the microfinance institution and the interaction with the borrowers, it can turn into what people call a ‘payday loan’ sort of situation,” she told me. “You don’t want people paying 75% interest and having debt collectors coming after them for the rest of their lives.” Previously, she trusted that she could filter out the most predatory situations through the Kiva website, relying on information like the estimated interest rate to guide her decisions. As information has become harder to come by, she’s had a harder time feeling confident in the terms the borrowers face. In January 2022, Smith closed the 2,500-strong Together for Women group and stopped lending through Kiva. Dozens of other borrowers, her husband included, have done the same. While these defectors represent a tiny fraction of the 2 million people who have used the website, they were some of its most dedicated lenders: of the dozen I spoke to, nearly all had been involved for nearly a decade, some ultimately lending tens of thousands of dollars. For them, the dream of “make a loan, change a life” now feels heartbreakingly unattainable. Smith calls the day she closed her team “one of the saddest days of my life.” Still, the decision felt essential: “I don’t want to be one of those people that’s more like an impact investor who is trying to make money off the backs of the poorer.” “I understand that I’m in the minority here,” she continued. “This is the way [microfinance is] moving. So clearly people feel it’s something that’s acceptable to them, or a good way to invest their money. I just don’t feel like it’s acceptable to me.” Mara Kardas-Nelson is the author of a forthcoming book on the history of microfinance, We Are Not Able to Live in the Sky (Holt, 2024). Correction: An earlier version of this story misstated a phrase found on the Kiva website as "It’s not a charity, it’s a loan." The correct phrase is “It’s a loan, not a donation.” hide by Mara Kardas-Nelson Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. 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"Next slide please: A brief history of the corporate presentation | MIT Technology Review"

"https://www.technologyreview.com/2023/08/11/1077232/corporate-presentations-history"

"Featured Topics Newsletters Events Podcasts Next slide, please: A brief history of the corporate presentation From million-dollar slide shows to Steve Jobs’s introduction of the iPhone, a bit of show business never hurt plain old business. To celebrate the launch of the 1987 Saab 9000 CD sedan, an audience of 2,500 was treated to an hourlong operetta involving 26-foot-tall projection screens, a massive chorus, the entire Stockholm Philharmonic, and some 50 performers. Douglas Mesney/Incredible slidemakers by Claire L. Evans archive page It’s 1948, and it isn’t a great year for alcohol. Prohibition has come and gone, and booze is a buyer’s market again. That much is obvious from Seagram’s annual sales meeting, an 11-city traveling extravaganza designed to drum up nationwide sales. No expense has been spared: there’s the two-hour, professionally acted stage play about the life of a whiskey salesman. The beautiful anteroom displays. The free drinks. But the real highlight is a slideshow. To call the Seagram-Vitarama a slideshow is an understatement. It’s an experience : hundreds of images of the distilling process, set to music, projected across five 40-by-15-foot screens. “It is composed of pictures, yet it is not static,” comments one awed witness. “The overall effect is one of magnificence.” Inspired by an Eastman Kodak exhibit at the 1939 World’s Fair, the Seagram-Vitarama is the first A/V presentation ever given at a sales meeting. It will not be the last. In the late ’40s, multimedia was a novelty. But by the early 1960s, nearly all companies with national advertising budgets were using multimedia gear—16-­millimeter projectors, slide projectors, filmstrip projectors, and overheads—in their sales training and promotions, for public relations, and as part of their internal communications. Many employed in-house A/V directors, who were as much showmen as technicians. Because although presentations have a reputation for being tedious, when they’re done right, they’re theater. The business world knows it. Ever since the days of the Vitarama, companies have leveraged the dramatic power of images to sell their ideas to the world. Next slide, please The sound of slides clacking is deafening. But it doesn’t matter, because the champagne is flowing and the sound system is loud. The 2,500 dignitaries and VIPs in the audience are being treated to an hourlong operetta about luxury travel. Onstage, a massive chorus, the entire Stockholm Philharmonic, and some 50 dancers and performers are fluttering around a pair of Saab 9000CD sedans. Stunning images of chrome details, leather seats, and open roads dance across a 26-foot-tall screen behind them. The images here are all analog: nearly 7,000 film slides, carefully arranged in a grid of 80 Kodak projectors. It’s 1987, and slideshows will never get any bigger than this. Before PowerPoint, and long before digital projectors, 35-millimeter film slides were king. Bigger, clearer, and less expensive to produce than 16-millimeter film, and more colorful and higher-resolution than video, slides were the only medium for the kinds of high-impact presentations given by CEOs and top brass at annual meetings for stockholders, employees, and salespeople. Known in the business as “multi-image” shows, these presentations required a small army of producers, photographers, and live production staff to pull off. First the entire show had to be written, storyboarded, and scored. Images were selected from a library, photo shoots arranged, animations and special effects produced. A white-gloved technician developed, mounted, and dusted each slide before dropping it into the carousel. Thousands of cues were programmed into the show control computers—then tested, and tested again. Because computers crash. Projector bulbs burn out. Slide carousels get jammed. “When you think of all the machines, all the connections, all the different bits and pieces, it’s a miracle these things even played at all,” says Douglas Mesney , a commercial photographer turned slide producer whose company Incredible Slidemakers produced the 80-­projector Saab launch. Now 77 years old, he’s made a retirement project of archiving the now-forgotten slide business. Mesney pivoted to producing multi-image shows in the early 1970s after an encounter with an impressive six-screen setup at the 1972 New York Boat Show. He’d been shooting spreads for Penthouse and car magazines, occasionally lugging a Kodak projector or two to pitch meetings for advertising clients. “All of a sudden you look at six projectors and what they can do, and you go, Holy mackerel ,” he remembers. “All of a sudden you look at six projectors and what they can do, and you go, Holy mackerel. ” Six was just the beginning. At the height of Mesney's career, his shows called for up to 100 projectors braced together in vertiginous rigs. With multiple projectors pointing toward the same screen, he could create seamless panoramas and complex animations, all synchronized to tape. Although the risk of disaster was always high, when he pulled it off, his shows dazzled audiences and made corporate suits look like giants. Mesney’s clients included IKEA, Saab, Kodak, and Shell; he commanded production budgets in the hundreds of thousands of dollars. And in the multi-image business, that was cheap. Larger A/V staging companies, like Carabiner International, charged up to $1 million to orchestrate corporate meetings, jazzing up their generic multi-­image “modules” with laser light shows, dance numbers, and top-shelf talent like Hall & Oates, the Allman Brothers, and even the Muppets. “I liken it to being a rock-and-roll roadie, but I never went on the tour bus,” explains Susan Buckland, a slide programmer who spent most of her career behind the screen at Carabiner. From its incorporation in 1976 to the mid-1980s, the Association for Multi-Image, a trade association for slide producers, grew from zero to 5,000 members. At its peak, the multi-image business employed some 20,000 people and supported several festivals and four different trade magazines. One of these ran a glowing profile of Douglas Mesney in 1980; when asked for his prognosis about the future of slides, he replied: “We could make a fortune or be out of business in a year.” He wasn’t wrong. Related Story The future of computing depends in part on how we reckon with its past. At the time, some 30 manufacturers of electronic slide programming devices vied for the multi-image dollar. To meet the demand for high-impact shows, the tech had quickly evolved from manual dissolve units and basic control systems—programmed with punched paper tape, and then audiocassette—to dedicated slide control computers like the AVL Eagle I, which could drive 30 projectors at once. The Eagle, which came with word processing and accounting software, was a true business computer—so much so that when Eagle spun off from its parent company, Audio Visual Labs, in the early ’80s, it became one of Silicon Valley’s most promising computer startups. Eagle went public in the summer of 1983, making its president, Dennis R. Barnhart, an instant multimillionaire. Only hours after the IPO, Barnhart plowed his brand-new cherry-red Ferrari through a guardrail near the company’s headquarters in Los Gatos, California, flipped through the air, crashed into a ravine, and died. The slide business would soon follow. Douglas Mesney likes to say that if you never saw a slide show, you never will. The machines to show them have been landfilled. The slides themselves were rarely archived. Occasionally a few boxes containing an old multi-image “module” will turn up in a storage unit, and occasionally those will even be undamaged. But with the exception of a few hobbyists and retired programmers, the know-how to restore and stage multi-image slideshows is scarce. This leaves former slide professionals at a loss. “All of us are devastated that none of the modules survived,” says Susan Buckland. “Basically, I don’t have a past, because I can’t explain it.” The entire industry, which existed at an unexpected intersection of analog and high-tech artistry, came and went in a little over 20 years. Presentations, like porn, have always pushed technology forward; in the multi-­image days, producers like Mesney took the slide as far as it could go, using every tool available to create bigger and bolder shows. Mesney claims to have set the land speed record for a slide presentation with a three-minute-long, 2,400-slide show, but even at top speed, slides are static. The computers that controlled them, however, were not—and it wasn’t long before they evolved beyond the medium. “Back then, computers were fast enough to tell slides what to do, but they weren’t fast enough to actually create the images themselves,” explains Steven Michelsen, a former slide programmer who restores and runs old multi-image shows in his Delaware garage. “It took another 10 or 15 years until you could run a show straight from your computer and have the images look worth looking at,” he adds. The last slide projector ever made rolled off the assembly line in 2004. The inside of its casing was signed by factory workers and Kodak brass before the unit was handed over to the Smithsonian. Toasts and speeches were made, but by then they were eulogies, because PowerPoint had already eaten the world. Inventing PowerPoint The Hotel Regina is an Art Nouveau marvel overlooking the Tuileries Garden and the Louvre. But on this day in 1992, its Old World meeting rooms have been retrofitted with advanced video technology. The color projector in the back of the room, the size of a small refrigerator, cost upwards of $100,000 and takes an hour to warm up. A team of technicians has spent the better part of the last 48 hours troubleshooting to ensure that nothing goes wrong when Robert Gaskins, the fastidious architect of a new piece of software called PowerPoint 3.0, walks into the room. He’ll be carrying a laptop under his arm, and when he reaches the lectern, he’ll pick up a video cable, plug it in, and demonstrate for the first time something that has been reproduced billions of times since: a video presentation, running straight off a laptop, in full color. The audience, full of Microsoft associates from across Europe, will go bananas. They “grasped immediately what the future would bring for their own presentations,” Gaskins later wrote. “There was deafening applause.” It’s hard now to imagine deafening applause for a PowerPoint—almost as hard as it is to imagine anyone but Bob Gaskins standing at this particular lectern, ushering in the PowerPoint age. Presentations are in his blood. His father ran an A/V company, and family vacations usually included a trip to the Eastman Kodak factory. During his graduate studies at Berkeley, he tinkered with machine translation and coded computer-generated haiku. He ran away to Silicon Valley to find his fortune before he could finalize his triple PhDs in English, linguistics, and computer science, but he brought with him a deep appreciation for the humanities, staffing his team with like-minded polyglots, including a disproportionately large number of women in technical roles. Because Gaskins ensured that his offices—the only Microsoft division, at the time, in Silicon Valley—housed a museum-worthy art collection, PowerPoint’s architects spent their days among works by Frank Stella, Richard Diebenkorn, and Robert Motherwell. Gaskins’s 1984 proposal for PowerPoint, written when he was VP of product development at the Sunnyvale startup Forethought, is a manifesto in bullet points. It outlines the slumbering, largely-hidden-from-view $3.5 billion business presentation industry and its enormous need for clear, effective slides. It lists technology trends—laser printers, color graphics, “WYSIWYG” software—that point to an emerging desktop presentation market. It’s a stunningly prescient document throughout. But Gaskins italicized only one bullet point in the whole thing. User benefits: Allows the content-originator to control the presentation. This is Gaskins’s key insight: a presentation’s message is inevitably diluted when its production is outsourced. In the early ’80s, he meant that literally. The first two versions of PowerPoint were created to help executives produce their own overhead transparencies and 35-millimeter slides, rather than passing the job off to their secretaries or a slide bureau. PowerPoint had become shorthand for the stupefying indignities of office life—a 2001 New Yorker profile summed it up as “software you impose on other people.” “In the ’50s, ’60s, and early ’70s, information flow was narrow,” explains Sandy Beetner, former CEO of Genigraphics, a business graphics company that was, for several decades, the industry leader in professional presentation graphics. Their clients were primarily Fortune 500 companies and government agencies with the resources to produce full-color charts, 3D renderings, and other high-tech imagery on those slides. Everyone else was limited to acetate overheads and— gasp —words. “Prior to PowerPoint,” she says, “people communicated in black and white. There was just so much missed in that environment.” Beetner oversaw Genigraphics’ national network service bureaus, which were located in every major American city and staffed 24 hours a day, 365 days a year, by graphic artists prepared to produce, polish, and print slides. The company was so vital to presentational culture that Gaskins negotiated a deal to make Genigraphics the official 35-millimeter slide production service for PowerPoint 2.0; a “Send to Genigraphics” menu command was baked into PowerPoint until 2003. This, incidentally, was around the same time that Kodak stopped making Carousel projectors. Gaskins retired from Microsoft in 1993 and moved to London. He returned to the States 10 years later, an expert in antique concertinas. By then, PowerPoint had become shorthand for the stupefying indignities of office life. A 2001 New Yorker profile summed it up as “software you impose on other people”; the statistician Edward Tufte, known for his elegant monographs about data visualization, famously blamed the 2003 Columbia shuttle disaster on a bum PowerPoint slide. Gaskins’s software, Tufte argued, produces relentlessly sequential, hierarchical, sloganeering, over-managed presentations, rife with “chartjunk” and devoid of real meaning. No wonder software corporations loved it. Robert Gaskins is remarkably sympathetic to these views, not least because Tufte’s mother, the Renaissance scholar Virginia Tufte, mentored him as an undergraduate in the English department at the University of Southern California. In a reflection written on the 20th anniversary of PowerPoint’s introduction, Gaskins acknowledged that “more business and academic talks look like poor attempts at sales presentations,” a phenomenon he blamed as much on a “mass failure of taste” as on PowerPoint itself, a tool so powerful it collapsed all preexisting contexts. Not everything’s a sales presentation; nor should it be. But PowerPoint made it easy to add multimedia effects to informal talks, empowering lay users to make stylistic decisions once reserved for professionals. To paraphrase an early PowerPoint print ad: now the person making the presentation made the presentation. That those people weren’t always particularly good at it didn’t seem to matter. What did matter was that presentations were no longer reserved for year-end meetings and big ideas worthy of the effort and expense required to prepare color slides. “The scalability of information and audience that PowerPoint brought to the party was pretty incredible,” says Beetner, whose company has survived as a ghost in the machine, in the form of PowerPoint templates and clip art. “It opened up the channels dramatically, and pretty quickly. There isn’t a student alive, at any level, that hasn’t seen a PowerPoint presentation.” Indeed, PowerPoint is used in religious sermons; by schoolchildren preparing book reports; at funerals and weddings. In 2010, Microsoft announced that PowerPoint was installed on more than a billion computers worldwide. Related Story A participatory project explores the linguistic landscape of the US. At this scale, PowerPoint’s impact on how the world communicates has been immeasurable. But here’s something that can be measured: Microsoft grew tenfold in the years that Robert Gaskins ran its Graphics Business Unit, and it has grown 15-fold since. Technology corporations, like PowerPoint itself, have exploded. And so have their big presentations, which are no longer held behind closed doors. They’re now semi-public affairs, watched—willingly and enthusiastically—by consumers around the world. Nobody has to worry about slide carousels getting jammed anymore, but things still go haywire all the time, from buggy tech demos to poorly-thought-out theatrics. When everything works, a good presentation can drive markets and forge reputations. Of course, this particular evolution wasn’t exclusively Microsoft’s doing. Because perhaps the most memorable corporate presentation of all time—Steve Jobs’s announcement of the iPhone at Macworld 2007— wasn’t a PowerPoint at all. It was a Keynote. Claire L. Evans is a writer and musician exploring ecology, technology, and culture. by Claire L. Evans Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Deep Dive Business New approaches to the tech talent shortage Early-career programs enable tech companies to invest in the future workforce via upskilling and education. By MIT Technology Review Insights archive page Data analytics reveal real business value Sophisticated analytics tools mine insights from data, optimizing operational processes across the enterprise. By MIT Technology Review Insights archive page How a tiny Pacific Island became the global capital of cybercrime Despite having a population of just 1,400, until recently, Tokelau’s .tk domain had more users than any other country. Here’s why. By Jacob Judah archive page Europe’s best-selling Chinese EV maker has a surprising name Even an upper hand in EV technologies doesn't mean Chinese-made cars will succeed in Europe. But one brand has... By Zeyi Yang archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. 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"Who gets to decide who receives experimental medical treatments? | MIT Technology Review"

"https://www.technologyreview.com/2023/08/10/1077216/experimental-treatments"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Who gets to decide who receives experimental medical treatments? For many patients, pushing for access to unproven treatments is their best chance of survival. And that’s worth the risk. By Jessica Hamzelou archive page Selman Design Max was only a toddler when his parents noticed there was “something different” about the way he moved. He was slower than other kids his age, and he struggled to jump. He couldn’t run. Blood tests suggested he might have a genetic disease— one that affected a key muscle protein. Max’s dad, Tao Wang, a researcher for a climate philanthropy organization, says he and his wife were initially in denial. It took them a few months to take Max for the genetic test that confirmed their fears: he had Duchenne muscular dystrophy. Duchenne is a rare disease that tends to affect young boys. It’s progressive—those affected lose muscle function as they get older. There is no cure. Many people with the disorder require wheelchairs well before they reach their 20s. Most do not survive beyond their 30s. Max’s diagnosis hit Wang and his wife “like a tornado,” he says. But eventually one of his doctors mentioned a clinical trial that he was eligible for. The trial was for an experimental gene therapy designed to replace the missing muscle protein with a shortened, engineered version that might help slow his decline or even reverse it. Enrolling Max in the trial was a no-brainer for Wang. “We were willing to try anything that could change the course [of the disease] and give us some hope,” he says. That was more than two years ago. Today, Max is an active eight-year-old, says Wang. He runs, jumps, climbs stairs without difficulty, and even enjoys hiking. “He’s a totally different kid,” says Wang. The gene therapy he received was recently considered for accelerated approval by the US Food and Drug Administration. Such approvals, reserved for therapies targeting serious conditions that lack existing treatments, require less clinical trial data than standard approvals. While the process can work well, it doesn’t always. And in this case, the data is not particularly compelling. The drug failed a randomized clinical trial—it was found to be no better than a placebo. Still, many affected by Duchenne are clamoring for access to the treatment. At an FDA advisory committee meeting in May set up to evaluate its merits, multiple parents of children with Duchenne pleaded with the organization to approve the drug immediately—months before the results of another clinical trial were due. On June 22, the FDA granted conditional approval for the drug for four- and five-year-old boys. Between 2009 and 2022, 48 cancer drugs received accelerated approval to treat 66 conditions—and 15 of those approvals have since been withdrawn. This drug isn’t the only one to have been approved on weak evidence. There has been a trend toward lowering the bar for new medicines, and it is becoming easier for people to access treatments that might not help them—and could harm them. Anecdotes appear to be overpowering evidence in decisions on drug approval. As a result, we’re ending up with some drugs that don’t work. We urgently need to question how these decisions are made. Who should have access to experimental therapies? And who should get to decide? Such questions are especially pressing considering how quickly biotechnology is advancing. Recent years have seen an explosion in what scientists call “ultra-novel” therapies, many of which involve gene editing. We’re not just improving on existing classes of treatments—we’re creating entirely new ones. Managing access to them will be tricky. Just last year, a woman received a CRISPR treatment designed to lower her levels of cholesterol—a therapy that directly edited her genetic code. Also last year, a genetically modified pig’s heart was transplanted into a man with severe heart disease. Debates have raged over whether he was the right candidate for the surgery, since he ultimately died. For many, especially those with severe diseases, trying an experimental treatment may be better than nothing. That’s the case for some people with Duchenne, says Hawken Miller, a 26-year-old with the condition. “It’s a fatal disease,” he says. “Some people would rather do something than sit around and wait for it to take their lives.” Expanding access There’s a difficult balance to be reached between protecting people from the unknown effects of a new treatment and enabling access to something potentially life-saving. Trying an experimental drug could cure a person’s disease. It could also end up making no difference, or even doing harm. And if companies struggle to get funding following a bad outcome, it could delay progress in an entire research field—perhaps slowing future drug approvals. In the US, most experimental treatments are accessed through the FDA. Starting in the 1960s and ’70s, drug manufacturers had to prove to the agency that their products actually worked, and that the benefits of taking them would outweigh any risks. “That really closed the door on patients’ being able to access drugs on a speculative basis,” says Christopher Robertson, a specialist in health law at Boston University. It makes sense to set a high bar of evidence for new medicines. But the way you weigh risks and benefits can change when you receive a devastating diagnosis. And it wasn’t long before people with terminal illnesses started asking for access to unapproved, experimental drugs. “If ... somebody gets compassionate use and then something bad happens to them, investors run away. It’s a business risk.” In 1979, a group of people with terminal cancer and their spouses brought a legal case against the government to allow them to access an experimental treatment. While a district court ruled that one of the plaintiffs should be allowed to buy the drug, it concluded that whether a person’s disease was curable or not was beside the point—everyone should still be protected from ineffective drugs. The decision was eventually backed by the Supreme Court. “Even for terminally ill patients, there’s still a concept of safety and efficacy under the statute,” says Robertson. Today, there are lots of ways people might access experimental drugs on an individual basis. Perhaps the most obvious way is by taking part in a clinical trial. Early-stage trials typically offer low doses to healthy volunteers to make sure new drugs are safe before they are offered to people with the condition the drugs are ultimately meant to treat. Some trials are “open label,” where everyone knows who is getting what. The gold standard is trials that are randomized, placebo controlled, and blinded: some volunteers get the drug, some get the placebo, and no one—not even the doctors administering the drugs—knows who is getting what until after the results have been collected. These are the kinds of studies you need to do to tell if a drug is really going to help people. But clinical trials aren’t an option for everyone who might want to try an unproven treatment. Trials tend to have strict criteria about who is eligible depending on their age and health status, for example. Geography and timing matter, too—a person who wants to try a certain drug might live too far from where the trial is being conducted, or might have missed the enrollment window. Instead, such people can apply to the FDA under the organization’s expanded access program , also known as “compassionate use.” The FDA approves almost all such requests. It then comes down to the drug manufacturer to decide whether to sell the person the drug at cost (it is not allowed to make a profit), offer it for free, or deny the request altogether. Another option is to make a request under the Right to Try Act. The law, passed in 2018, establishes a new route for people with life-threatening conditions to access experimental drugs—one that bypasses the FDA. Its introduction was viewed by many as a political stunt, given that the FDA has rarely been the barrier to getting hold of such medicines. Under Right to Try, companies still have the choice of whether or not to provide the drug to a patient. When a patient is denied access through one of these pathways, it can make headlines. “It’s almost always the same story,” says Alison Bateman-House, an ethicist who researches access to investigational medical products at New York University’s Grossman School of Medicine. In this story, someone is fighting for access to a drug and being denied it by “cold and heartless” pharma or the FDA, she says. The story is always about “patients valiantly struggling for something that would undoubtedly help them if they could just get to it.” Related Story A handful of immunologists are pushing the field to take attributes such as sex chromosomes, sex hormones, and reproductive tissues into account. But in reality, things aren’t quite so simple. When companies decide not to offer someone a drug, you can’t really blame them for making that decision, says Bateman-House. After all, the people making such requests are usually incredibly ill. If someone were to die after taking that drug, not only would it look bad, but it could also put off investors from funding further development. “If you have a case in the media where somebody gets compassionate use and then something bad happens to them, investors run away,” says Bateman-House. “It’s a business risk.” FDA approval of a drug means it can be sold and prescribed—crucially, it’s no longer experimental. Which is why many see approval as the best way to get hold of a promising new treatment. As part of a standard approval process, which should take 10 months or less , the FDA will ask to see clinical trial evidence that the drug is both safe and effective. Collecting this kind of evidence can be a long and expensive process. But there are shortcuts for desperate situations, such as the outbreak of covid-19 or rare and fatal diseases—and for serious diseases with few treatment options, like Duchenne. Anecdotes vs. evidence Max accessed his drug through a clinical trial. The treatment, then called SRP-9001, was developed by the pharmaceutical company Sarepta and is designed to replace dystrophin, the protein missing in children with Duchenne muscular dystrophy. The protein is thought to protect muscle cells from damage when the muscles contract. Without it, muscles become damaged and start to degenerate. The dystrophin protein has a huge genetic sequence—it’s too long for the entire thing to fit into a virus, the usual means of delivering new genetic material into a person’s body. So the team at Sarepta designed a shorter version, which they call micro-dystrophin. The code for the protein is delivered by means of a single intravenous infusion. The company planned to develop the therapy to treat patients with Duchenne who could still walk. And it had a way to potentially fast-track the approval process. Usually, before a drug can be approved, it will go through several clinical trials. But accelerated approval offers a shortcut for companies that can show that their drug is desperately needed, safe, and supported by compelling preliminary evidence. For this kind of approval, drug companies don’t need to show that a treatment has improved anyone’s health—they just need to show improvement in some biomarker related to the disease (in Sarepta’s case, the levels of the micro-dystrophin protein in people’s muscle). There’s an important proviso: the company must promise to continue studying the drug, and to provide “confirmatory trial evidence.” This process can work well. But in recent years, it has been a “disaster,” says Diana Zuckerman, president of the National Center for Health Research, a nonprofit that assesses research on health issues. Zuckerman believes the bar of evidence for accelerated approval has been dropping. Many drugs approved via this process are later found ineffective. Some have even been shown to leave people worse off. For example, between 2009 and 2022, 48 cancer drugs received accelerated approval to treat 66 conditions—and 15 of those approvals have since been withdrawn. Melfulfen was one of these. The drug was granted accelerated approval for multiple myeloma in February 2021. Just five months later, the FDA issued an alert following the release of trial results suggesting that people taking the drug had a higher risk of death. In October 2021, the company that made the drug announced it was to be taken off the market. Related Story Optogenetics and advanced imaging have helped neuroscientists understand how memories form and made it possible to manipulate them. There are other examples. Take Makena, a treatment meant to reduce the risk of preterm birth. The drug was granted accelerated approval in 2011 on the basis of results from a small trial. Larger, later studies suggested it didn’t work after all. Earlier this year, the FDA withdrew approval for the drug. But it had already been prescribed to hundreds of thousands of people—nearly 310,000 women were given the drug between 2011 and 2020 alone. And then there’s Aduhelm. The drug was developed as a treatment for Alzheimer’s disease. When trial data was presented to an FDA advisory committee, 10 of 11 panel members voted against approval. The 11th was uncertain. There was no convincing evidence that the drug slowed cognitive decline, the majority of the members found. “There was not any real evidence that this drug was going to help patients,” says Zuckerman. Despite that, the FDA gave Aduhelm accelerated approval in 2021. The drug went on the market at a price of $56,000 a year. Three of the committee members resigned in response to the FDA’s approval. And in April 2022, the Centers for Medicare & Medicaid Services announced that Medicare would only cover treatment that was administered as part of a clinical trial. The case demonstrates that accelerated approval is no guarantee a drug will become easier to access. The other important issue is cost. Before a drug is approved, people might be able to get it through expanded access—usually for free. But once the drug is approved, many people who want it will have to pay. And new treatments—especially gene therapies—don’t tend to be cheap. We’re talking hundreds of thousands, or even millions, of dollars. “No patient or families should have to pay for a drug that’s not proven to work,” says Zuckerman. What about SRP-9001? On May 12, the FDA held an advisory committee meeting to assess whether the data supported accelerated approval. During the nine-hour virtual meeting, scientists, doctors, statisticians, ethicists, and patient advocates presented the data collected so far, and shared their opinions. Sarepta had results from three clinical trials of the drug in boys with Duchenne. Only one of the three—involving 41 volunteers aged four to seven—was randomized, blinded, and placebo controlled. Scientists will tell you that’s the only study you can draw conclusions from. And unfortunately, that trial did not go particularly well—by the end of 48 weeks, the children who got the drug were not doing any better than those who got a placebo. But videos presented by parents whose children had taken the drug told a different story. Take the footage shared by Brent Furbee. In a video clip taken before he got the gene therapy, Furbee’s son Emerson is obviously struggling to get up the stairs. He slowly swings one leg around while clinging to the banister, before dragging his other leg up behind him. A second video, taken after the treatment, shows him taking the stairs one foot at a time, with the speed you’d expect of a healthy four-year-old. In a third, he is happily pedaling away on his tricycle. Furbee told the committee that Emerson, now six, could run faster, get up more quickly, and perform better on tests of strength and agility. “Emerson continues to get stronger,” he said. It was one of many powerful, moving testimonies—and these stories appear to have influenced the FDA’s voting committee, despite many concerns raised about the drug. The idea of providing the genetic code for the body to make a shortened version of dystrophin is based on evidence that people who have similarly short proteins have a much milder form of muscular dystrophy than those whose bodies produce little to no dystrophin. But it’s uncertain whether Sarepta’s protein, with its missing regions, will function in the same way. Related Story Martine Rothblatt sees a day when transplantable organs and 3D-printed ones will be readily available, saving countless lives—including her daughter’s. Louise Rodino-Klapac, executive vice president, chief scientific officer, and head of R&D at Sarepta, defends the drug: “The totality of the evidence is what gives us great confidence in the therapy.” She has an explanation for why the placebo-controlled trial didn’t show a benefit overall. The groups of six- to seven-year-olds receiving the drug and the placebo were poorly matched “at baseline,” she says. She also says that the researchers saw a statistically significant result when they focused only on the four- and five-year-olds studied. But the difference is not statistically significant for the results the trial was designed to collect. And there are some safety concerns. While most of the boys developed only “mild” side effects, like vomiting, nausea, and fever, a few experienced more serious, although temporary, problems. There were a total of nine serious complications among the 85 volunteers. One boy had heart inflammation. Another developed an immune disease that damages muscle fibers. On top of all that, as things currently stand, receiving one gene therapy limits future gene therapy options. That’s because the virus used to deliver the therapy causes the body to mount an immune response. Many gene therapies rely on a type called adeno-associated virus, or AAV. If a more effective gene therapy that uses the same virus comes along in the coming years, those who have taken this drug won’t be able to take the newer treatment. Despite all this, the committee voted 8–6 in favor of granting the drug an accelerated approval. Many committee members highlighted the impact of the stories and videos shared by parents like Brent Furbee. “Now, I don’t know whether those boys got placebo or whether they got the drug, but I suspect that they got the drug,” a neurologist named Anthony Amato told the audience. “Those videos, anecdotal as they are … are substantial evidence of effectiveness,” said committee member Donald B. Kohn, a stem-cell biologist. The drugs don’t work? Powerful as they are, individual experiences are just that. “If you look at the evidentiary hierarchy, anecdote is considered the lowest level of evidence,” says Bateman-House. “It’s certainly nowhere near clinical-trial-level evidence.” This is not the way we should be approving drugs, says Zuckerman. And it’s not the first time Sarepta has had a drug approved on the basis of weak evidence, either. The company has already received FDA approval to sell three other drugs for Duchenne, all of them designed to skip over faulty exons—bits of DNA that code for a protein. Such drugs should allow cells to make a longer form of a protein that more closely resembles dystrophin. The first of these “exon-skipping” drugs, Exondys 51, was granted accelerated approval in 2016—despite the fact that the clinical trial was not placebo controlled and included only 12 boys. “I’ve never seen anything like it,” says Zuckerman. She points out that the study was far too small to be able to prove the drug worked. In her view, 2016 was “a turning point” for FDA approvals based on low-quality evidence—“It was so extreme,” she says. Since then, three other exon-skipping drugs have received accelerated approval for Duchenne—two of them from Sarepta. A Sarepta spokesperson said a company-funded analysis showed that people with Duchenne who received Exondys 51 remained ambulatory longer and lived longer by 5.4 years—“data we would not have without that initial approval.” SRP-9001, now called Elevidys, will cost $3.2 million for a one-off treatment. But for many in the scientific community, that data still needs to be confirmed. “The clinical benefit still has not been confirmed for any of the four,” Mike Singer, a clinical reviewer in the FDA’s Office of Therapeutic Products, told the advisory committee in May. “All of them are wanted by the families, but none of them have ever been proven to work,” says Zuckerman. Will Roberts is one of the boys taking an exon-­skipping drug—specifically, Sarepta’s Amondys 45. Now 10, he was diagnosed with Duchenne when he was just one year old. His treatment involves having a nurse come to his home and inject him every five to 10 days. And it’s not cheap. While his parents have a specialist insurance policy that shields them from the cost, the price of a year’s worth of treatment is around $750,000. Will’s mother, Keyan Roberts, a teacher in Michigan, says she can’t tell if the drug is helping him. Last year he was running around in their backyard, but this year he needs a power chair to get around at school. “We definitely didn’t see any gains in ability, and it’s hard to tell if it made his decline … a little less steep,” Roberts says. The treatment comes with risks, too. The Amondys 45 website warns that 20% of people who get the drug experience adverse reactions , and that “potentially fatal” kidney damage has been seen in people treated with a similar drug. Roberts says she is aware of the risks that come with taking drugs like Amondys. But she and her husband, Ryan, an IT manager, were still hoping that SRP-9001 would be approved by the FDA. For the Robertses and parents like them, part of the desire is based on the hope, no matter how slim, that their child might benefit. “We really feel strongly that we’re in a position now where we’re seeing [Will’s] mobility decline, and we’re nervous that … he might not qualify to take it by the time it’s made available,” she said in a video call, a couple of weeks after the advisory committee meeting. Selling hope On June 22, just over a month after the committee meeting, the FDA approved SRP-9001 , now called Elevidys. It will cost $3.2 million for the one-off treatment, before any potential discounts. For the time being, the approval is restricted to four- and five-year-olds. It was granted with a reminder to the company to complete the ongoing trials and report back on the results. Sarepta maintains that there is sufficient evidence to support the drug’s approval. But this drug and others have been made available—at eye-wateringly high prices—without the strong evidence we’d normally expect for new medicines. Is it ever ethical to sell a drug when we don’t fully know whether it will work? I put this question to Debra Miller, mother of Hawken Miller and founder of CureDuchenne. Hawken was diagnosed when he was five years old. “The doctor that diagnosed him basically told us that he was going to stop walking around 10 years old, and he would not live past 18,” she says. “‘There’s no treatment. There’s no cure. There’s nothing you can do. Go home and love your child.’” She set up CureDuchenne in response. The organization is dedicated to funding research into potential treatments and cures, and to supporting people affected by the disease. It provided early financial support to Sarepta but does not have a current financial interest in the company. Hawken, now a content strategist for CureDuchenne, has never been eligible for a clinical trial. Debra Miller says she’s glad that the exon-skipping drugs were approved. From her point of view, it’s about more than making a new drug accessible. “We all want hope. But in medicine, isn’t it better to have hope based on evidence rather than hope based on hype?” “[The approvals] drove innovation and attracted a lot of attention to Duchenne,” she says. Since then, CureDuchenne has funded other companies exploring next-generation exon-skipping drugs that, in early experiments, seem to work better than the first-generation drugs. “You have to get to step one before you can get to step two,” she says. Hawken Miller is waiting for the data from an ongoing phase 3 clinical trial of Elevidys. For the time being, “from a data perspective, it doesn’t look great,” he says. “But at the same time, I hear a lot of anecdotes from parents and patients who say it’s really helping a lot, and I don’t want to discount what they’re seeing.” Testing is scheduled to wrap up September—just three months after the accelerated approval was granted. It might not seem like much of a wait, but every minute is precious to children with Duchenne. “Time is muscle” was the refrain repeated throughout the advisory committee meeting. “I wish that we had the time and the muscle to wait for things that were more effective,” says Keyan Roberts, Will’s mom. “But one of the problems with this disease is that we might not have the opportunity to wait to take one of those other drugs that might be made available years down the line.” Doctors may end up agreeing that a drug—even one that is unlikely to work—is better than nothing. “In the American psyche, that is the approach that [doctors and] patients are pushed toward,” says Holly Fernandez Lynch, a bioethicist at the University of Pennsylvania. “We have all this language that you’re ‘fighting against the disease,’ and that you should try everything.” “I can’t tell you how many FDA advisory committee meetings I’ve been to where the public-comment patients are saying something like ‘This is giving me hope,’” says Zuckerman. “Sometimes hope helps people do better. It certainly helps them feel better. And we all want hope. But in medicine, isn’t it better to have hope based on evidence rather than hope based on hype?” A desperate decision A drug approved on weak data might offer nothing more than false hope at a high price, Zuckerman says: “It is not fair for patients and their families to [potentially] have to go into bankruptcy for a drug that isn’t even proven to work.” The best way for people to access experimental treatments is still through clinical trials, says Bateman-House. Robertson, the health law expert, agrees, and adds that trials should be “bigger, faster, and more inclusive.” If a drug looks as if it’s working, perhaps companies could allow more volunteers to join the trial, for example. Their reasoning is that people affected by devastating diseases should be protected from ineffective and possibly harmful treatments—even if they want them. Review boards assess how ethical clinical trials are before signing off on them. Participants can’t be charged for drugs they take in clinical trials. And they are carefully monitored by medical professionals during their participation. That doesn’t mean people who are desperate for treatments are incapable of making good decisions. “They are stuck with bad choices,” says Fernandez Lynch. This is also the case for ultra-novel treatments, says Robertson. At the start of trials, the best candidates for all-new experimental therapies may be those who are closer to death, he says: “It is quite appropriate to select patients who have less to lose, while nonetheless being sure not to exploit people who don’t have any good options.” There’s another advantage to clinical trials. It’s hard to assess the effectiveness of a one-off treatment in any single individual. But clinical trials contribute valuable data that stands to benefit a patient community. Such data is especially valuable for treatments so new that there are few standards for comparison. Hawken Miller says he would consider taking part in an Elevidys clinical trial. “I’m willing to take on some of that risk for the potential of helping other people,” he says. “I think you’ll find that in [most of the Duchenne] community, everyone’s very willing to participate in clinical trials if it means helping kids get cured faster.” When it comes to assessing the likelihood that Elevidys will work, Will’s dad, Ryan Roberts, says he’s a realist. “We’re really close to approaching the last chance—the last years he’ll be ambulatory,” he says. For him as a dad, he says, the efficacy concerns aren’t relevant. “We will take the treatment because it’s going to be the only chance we have … We are aware that we’re not being denied a treatment that is a cure, or a huge game-changer. But we are willing to take anything we can get in the short window we have closing now.” Correction: This story has been corrected to note that micro-dystrophin is measured in muscle, not blood, and clarify when it affects ambulation for most patients. It has also been updated to clarify Sarepta’s plans and testing timeline for SRP-9001. hide by Jessica Hamzelou Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our September/October 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Biotechnology and health Everything you need to know about artificial wombs Artificial wombs are nearing human trials. But the goal is to save the littlest preemies, not replace the uterus. By Cassandra Willyard archive page Some deaf children in China can hear after gene therapy treatment After deafness treatment, Yiyi can hear her mother and dance to the music. But why is it so noisy at night? By Antonio Regalado archive page Zeyi Yang archive page Scientists just drafted an incredibly detailed map of the human brain A massive suite of papers offers a high-res view of the human and non-human primate brain. By Cassandra Willyard archive page How AI can help us understand how cells work—and help cure diseases A virtual cell modeling system, powered by AI, will lead to breakthroughs in our understanding of diseases, argue the cofounders of the Chan Zuckerberg Initiative. By Priscilla Chan archive page Mark Zuckerberg archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Uber facial recognition is locking Indian drivers out of their accounts  | MIT Technology Review"

"https://www.technologyreview.com/2022/12/06/1064287/ubers-facial-recognition-is-locking-indian-drivers-out-of-their-accounts"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Uber’s facial recognition is locking Indian drivers out of their accounts Some people are finding their accounts permanently blocked By Varsha Bansal archive page Selvaprakash Lakshmanan Correction: this story has been updated to include Uber’s response. The opening has been amended to remove an anecdote about a specific driver’s experience based on that response. Uber drivers in India say that problems with the facial recognition they use to access their apps is costing them work. In a survey conducted by MIT Technology Review of 150 Uber drivers in the country, almost half say they have been either temporarily or permanently locked out of their accounts as a result of problems with their selfie. Many suspected that a change in their appearance, such as facial hair, a shaved head, or a haircut, was to blame. Another quarter of them believe it was due to low lighting. India has around 600,000 Uber drivers, but many others work for the homegrown ride-sharing platform Ola and for startups such as Swiggy , Zomato , and Urban Company. All ask their platform workers to upload selfies for logins or verifications. Uber checks that a driver’s face matches what the company has on file through a program called “Real-Time ID Check.” It was rolled out in the US in 2016, in India in 2017, and then in other markets. “This prevents fraud and protects drivers’ accounts from being compromised. It also protects riders by building another layer of accountability into the app to ensure the right person is behind the wheel,” Joe Sullivan, Uber’s chief security officer, said in a statement in 2017. But the company’s driver verification procedures are far from seamless. Adnan Taqi, an Uber driver in Mumbai, ran into trouble with it when the app prompted him to take a selfie around dusk. He was locked out for 48 hours, a big dent in his work schedule—he says he drives 18 hours straight, sometimes as much as 24 hours, to be able to make a living. Days later, he took a selfie that locked him out of his account again, this time for a whole week. That time, Taqi suspects, it came down to hair: “I hadn’t shaved for a few days and my hair had also grown out a bit,” he says. Others say they have struggled with scratches on their cameras and low-budget smartphones. The problem isn’t unique to Uber. Drivers with Ola, which is backed by SoftBank, face similar issues. Uber did not initially respond to a series of questions from MIT Technology Review about its technology and drivers’ experiences. After publication, the company said that no deactivations can take place based on facial recognition alone. It said that Real-Time ID Check works by escalating flagged non-matches to at least two humans who then check the photos manually. This process takes less than 25 seconds. It says that its tool can handle changes in hair. Nevertheless, more than a dozen drivers interviewed for this story detailed instances of having to find better lighting to avoid being locked out of their Uber accounts. “Whenever Uber asks for a selfie in the evenings or at night, I’ve had to pull over and go under a streetlight to click a clear picture—otherwise there are chances of getting rejected,” said Santosh Kumar, an Uber driver from Hyderabad. Real-Time ID Check works by converting your face into a set of points, explains Jernej Kavka, an independent technology consultant with access to Microsoft’s Face API, which is what Uber uses to power Real-Time ID Check. “With excessive facial hair, the points change and it may not recognize where the chin is,” Kavka says. The same thing happens when there is low lighting or the phone’s camera doesn’t have a good contrast. “This makes it difficult for the computer to detect edges,” he explains. The software may be especially brittle in India. In December 2021, tech policy researchers Smriti Parsheera (a fellow with the CyberBRICS project) and Gaurav Jain (an economist with the International Finance Corporation) posted a preprint paper that audited four commercial facial processing tools—Amazon’s Rekognition, Microsoft Azure’s Face, Face++, and FaceX—for their performance on Indian faces. When the software was applied to a database of 32,184 election candidates, Microsoft’s Face failed to even detect the presence of a face in more than 1,000 images, throwing an error rate of more than 3%—the worst among the four. It could be that the Uber app is failing drivers because its software was not trained on a diverse range of Indian faces, Parsheera says. But she says there may be other issues at play as well. “There could be a number of other contributing factors like lighting, angle, effects of aging, etc.,” she explained in writing. “But the lack of transparency surrounding the use of such systems makes it hard to provide a more concrete explanation.” Uber said that it regularly conducts fairness testing (both internally, and in partnership with Microsoft) to understand how this product is performing for users with different skin complexions and identify any opportunities to improve efficiency and accuracy. Microsoft declined to comment in response to questions sent by MIT Technology Review. The problems don’t end with the algorithm’s decision. Drivers say the grievance redress mechanism that Uber follows is tedious, time-consuming, frustrating, and mostly unhelpful. They say they sometimes spend weeks trying to get their issues resolved. “We have to keep calling their help line incessantly before they unlock our accounts, constantly telling us that the server is down,” said Taqi, with a tone of frustration—but mostly a sense of defeat—in his voice. “It’s like their server is always down.” Uber said it gives drivers a chance to appeal deactivations. If problems persist—and protections remain limited—they could have an outsize effect, and not just on work. “Labor platforms in India are starting to become a key interface between the worker, the market, and the government—they enable loans for cars or even credit for larger household expenses,” says Aditi Surie, a senior researcher at the Indian Institute for Human Settlements, who has done research on gig work in India. In a country where such work can catapult someone from precarity to a middle-class existence (especially when estimates suggest that the majority of people worldwide who fell into poverty during the pandemic live in India), getting blocked from or kicked off a platform can have devastating consequences. In other markets, gig workers have fought back against facial recognition. In the UK, for example, at least 35 Uber drivers claimed last year that their accounts were wrongly terminated. The Independent Workers’ Union of Great Britain has blamed a “racist algorithm.” Uber has faced at least two lawsuits in the UK because of the software. Uber said that in the UK and EU, drivers can choose whether their selfie is checked by verification technology or by human reviewers. Some countries and regions have moved to provide better protections for gig workers. The EU proposed a directive last year to improve working conditions and provide algorithmic transparency. And in September 2021, California court struck down Proposition 22 , a ballot initiative that excluded gig workers from employee benefits under state law. These regulations recognize that algorithmic systems can “negatively impact the rights of workers,” says Divij Joshi, a lawyer and a PhD candidate at University College London. But India currently has few legal protections in place for gig workers, Joshi says: “These same transparency efforts are not being seen in India from a policy or regulatory lens.” Elizabeth Anne Watkins, an organizational sociologist from Princeton University who has extensively studied the impact of facial recognition on Uber drivers in the US, would likely find this pattern familiar. “Prone to malfunction in variable conditions, the system places a heavy burden on workers who are left with little organizational support when facial recognition fails,” Hawkins, who is now a research scientist at Intel Labs, wrote in a 2020 paper. “Further, accountability for identity verification is shifted to the workers, who bear the consequences for systemic failures.” Samantha Dalal, who studies how workers understand algorithmic systems, says there could be more transparency about how the AI made a decision. “Including some explanation that goes beyond ‘You are deactivated’” would help, says Dalal, a doctoral candidate at the University of Colorado Boulder. “Such capabilities exist.” Absent any insight into what the mercurial, non-human boss wants, gig workers attempt a lot of trial and error while interacting with the apps, Dalal says. In an email, Uber said it sends multiple clear warnings before account deactivation. Varsha Bansal is a freelance journalist based in Bangalore. Reporting for this story was supported by Pulitzer Center’s AI Accountability Network. hide by Varsha Bansal Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The people paid to train AI are outsourcing their work… to AI | MIT Technology Review"

"https://www.technologyreview.com/2023/06/22/1075405/the-people-paid-to-train-ai-are-outsourcing-their-work-to-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts The people paid to train AI are outsourcing their work… to AI It’s a practice that could introduce further errors into already error-prone models. By Rhiannon Williams archive page Stephanie Arnett/MITTR | Getty A significant proportion of people paid to train AI models may be themselves outsourcing that work to AI, a new study has found. It takes an incredible amount of data to train AI systems to perform specific tasks accurately and reliably. Many companies pay gig workers on platforms like Mechanical Turk to complete tasks that are typically hard to automate, such as solving CAPTCHAs, labeling data and annotating text. This data is then fed into AI models to train them. The workers are poorly paid and are often expected to complete lots of tasks very quickly. Related Story Large language models are full of security vulnerabilities, yet they’re being embedded into tech products on a vast scale. No wonder some of them may be turning to tools like ChatGPT to maximize their earning potential. But how many? To find out, a team of researchers from the Swiss Federal Institute of Technology (EPFL) hired 44 people on the gig work platform Amazon Mechanical Turk to summarize 16 extracts from medical research papers. Then they analyzed their responses using an AI model they’d trained themselves that looks for telltale signals of ChatGPT output, such as lack of variety in choice of words. They also extracted the workers’ keystrokes in a bid to work out whether they’d copied and pasted their answers, an indicator that they’d generated their responses elsewhere. They estimated that somewhere between 33% and 46% of the workers had used AI models like OpenAI’s ChatGPT. It’s a percentage that’s likely to grow even higher as ChatGPT and other AI systems become more powerful and easily accessible, according to the authors of the study, which has been shared on arXiv and is yet to be peer-reviewed. “I don’t think it’s the end of crowdsourcing platforms. It just changes the dynamics,” says Robert West, an assistant professor at EPFL, who coauthored the study. Using AI-generated data to train AI could introduce further errors into already error-prone models. Large language models regularly present false information as fact. If they generate incorrect output that is itself used to train other AI models, the errors can be absorbed by those models and amplified over time, making it more and more difficult to work out their origins, says Ilia Shumailov, a junior research fellow in computer science at Oxford University, who was not involved in the project. Even worse, there’s no simple fix. “The problem is, when you’re using artificial data, you acquire the errors from the misunderstandings of the models and statistical errors,” he says. “You need to make sure that your errors are not biasing the output of other models, and there’s no simple way to do that.” The study highlights the need for new ways to check whether data has been produced by humans or AI. It also highlights one of the problems with tech companies’ tendency to rely on gig workers to do the vital work of tidying up the data fed to AI systems. “I don’t think everything will collapse,” says West. “But I think the AI community will have to investigate closely which tasks are most prone to being automated and to work on ways to prevent this.” hide by Rhiannon Williams Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"AI might not steal your job, but it could change it | MIT Technology Review"

"https://www.technologyreview.com/2023/04/03/1070750/ai-jobs-legal-field-gpt-4"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts AI might not steal your job, but it could change it AI is already being used in the legal field. Is it really ready to be a lawyer? By Tate Ryan-Mosley archive page Stephanie Arnett/MITTR (This article is from The Technocrat, MIT Technology Review's weekly tech policy newsletter about power, politics, and Silicon Valley. To receive it in your inbox every Friday, sign up here. ) Advances in artificial intelligence tend to be followed by anxieties around jobs. This latest wave of AI models, like ChatGPT and OpenAI’s new GPT-4, is no different. First we had the launch of the systems. Now we’re seeing the predictions of automation. In a report released this week, Goldman Sachs predicted that AI advances could cause 300 million jobs, representing roughly 18% of the global workforce, to be automated in some way. OpenAI also recently released its own study with the University of Pennsylvania, which claimed that ChatGPT could affect over 80% of the jobs in the US. The numbers sound scary, but the wording of these reports can be frustratingly vague. “Affect” can mean a whole range of things, and the details are murky. People whose jobs deal with language could, unsurprisingly, be particularly affected by large language models like ChatGPT and GPT-4. Let’s take one example: lawyers. I’ve spent time over the past two weeks looking at the legal industry and how it’s likely to be affected by new AI models, and what I found is as much cause for optimism as for concern. The antiquated, slow-moving legal industry has been a candidate for technological disruption for some time. In an industry with a labor shortage and a need to deal with reams of complex documents, a technology that can quickly understand and summarize texts could be immensely useful. So how should we think about the impact these AI models might have on the legal industry? First off, recent AI advances are particularly well suited for legal work. GPT-4 recently passed the Universal Bar Exam , which is the standard test required to license lawyers. However, that doesn’t mean AI is ready to be a lawyer. The model could have been trained on thousands of practice tests, which would make it an impressive test-taker but not necessarily a great lawyer. (We don’t know much about GPT-4’s training data because OpenAI hasn’t released that information. ) Still, the system is very good at parsing text, which is of the utmost importance for lawyers. “Language is the coin in the realm of the legal industry and in the field of law. Every road leads to a document. Either you have to read, consume, or produce a document … that’s really the currency that folks trade in,” says Daniel Katz, a law professor at Chicago-Kent College of Law who conducted GPT-4's exam. Secondly, legal work has lots of repetitive tasks that could be automated, such as searching for applicable laws and cases and pulling relevant evidence, according to Katz. One of the researchers on the bar exam paper, Pablo Arredondo, has been secretly working with OpenAI to use GPT-4 in its legal product, Casetext, since this fall. Casetext uses AI to conduct “document review, legal research memos, deposition preparation and contract analysis,” according to its website. Arredondo says he’s grown more and more enthusiastic about GPT-4’s potential to assist lawyers as he’s used it. He says that the technology is “incredible” and “nuanced.” AI in law isn’t a new trend, though. It has already been used to review contracts and predict legal outcomes, and researchers have recently explored how AI might help get laws passed. Recently, consumer rights company DoNotPay considered arguing a case in court using an argument written by AI, known as the “robot lawyer,” delivered through an earpiece. (DoNotPay did not go through with the stunt and is being sued for practicing law without a license.) Despite these examples, these kinds of technologies still haven’t achieved widespread adoption in law firms. Could that change with these new large language models? Third, lawyers are used to reviewing and editing work. Large language models are far from perfect, and their output would have to be closely checked, which is burdensome. But lawyers are very used to reviewing documents produced by someone—or something—else. Many are trained in document review, meaning that the use of more AI, with a human in the loop, could be relatively easy and practical compared with adoption of the technology in other industries. The big question is whether lawyers can be convinced to trust a system rather than a junior attorney who spent three years in law school. Finally, there are limitations and risks. GPT-4 sometimes makes up very convincing but incorrect text, and it will misuse source material. One time, Arrodondo says, GPT-4 had him doubting the facts of a case he had worked on himself. “I said to it, You’re wrong. I argued this case. And the AI said, You can sit there and brag about the cases you worked on, Pablo, but I’m right and here’s proof. And then it gave a URL to nothing.” Arredondo adds, “It’s a little sociopath.” Katz says it’s essential that humans stay in the loop when using AI systems and highlights the professional obligation of lawyers to be accurate: “You should not just take the outputs of these systems, not review them, and then give them to people.” Others are even more skeptical. “This is not a tool I would trust with making sure important legal analysis was updated and appropriate,” says Ben Winters, who leads the Electronic Privacy Information Center’s projects on AI and human rights. Winters characterizes the culture of generative AI in the legal field as “overconfident, and unaccountable.” It’s also been well-documented that AI is plagued by racial and gender bias. There are also the long-term, high-level considerations. If attorneys have less practice doing legal research, what does that mean for expertise and oversight in the field? But we are a while away from that—for now. This week, my colleague and Tech Review’s editor at large, David Rotman, wrote a piece analyzing the new AI age’s impact on the economy—in particular, jobs and productivity. “The optimistic view: it will prove to be a powerful tool for many workers, improving their capabilities and expertise, while providing a boost to the overall economy. The pessimistic one: companies will simply use it to destroy what once looked like automation-proof jobs, well-paying ones that require creative skills and logical reasoning; a few high-tech companies and tech elites will get even richer, but it will do little for overall economic growth.” What I am reading this week Some bigwigs, including Elon Musk, Gary Marcus, Andrew Yang, Steve Wozniak, and over 1,500 others, signed a letter sponsored by the Future of Life Institute that called for a moratorium on big AI projects. Quite a few AI experts agree with the proposition, but the reasoning (avoiding AI armageddon) has come in for plenty of criticism. The New York Times has announced it won’t pay for Twitter verification. It's yet another blow to Elon Musk’s plan to make Twitter profitable by charging for blue ticks. On March 31, Italian regulators temporarily banned ChatGPT over privacy concerns. Specifically, the regulators are investigating whether the way OpenAI trained the model with user data violated GDPR. I’ve been drawn to some longer culture stories as of late. Here’s a sampling of my recent favorites: My colleague Tanya Basu wrote a great story about people sleeping together, platonically, in VR. It’s part of a new age of virtual social behavior that she calls “cozy but creepy.” In the New York Times, Steven Johnson came out with a lovely, albeit haunting, profile of Thomas Midgley Jr. , who created two of the most climate-damaging inventions in history And Wired’s Jason Kehe spent months interviewing the most popular sci-fi author you’ve probably never heard of in this sharp and deep look into the mind of Brandon Sanderson. What I learned this week “News snacking”—skimming online headlines or teasers—appears to be quite a poor way to learn about current events and political news. A peer-reviewed study conducted by researchers at the University of Amsterdam and the Macromedia University of Applied Sciences in Germany found that “users that ‘snack’ news more than others gain little from their high levels of exposure” and that “snacking” results in “significantly less learning” than more dedicated news consumption. That means the way people consume information is more important than the amount of information they see. The study furthers earlier research showing that while the number of “encounters” people have with news each day is increasing, the amount of time they spend on each encounter is decreasing. Turns out … that’s not great for an informed public. hide by Tate Ryan-Mosley Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Could ChatGPT do my job? | MIT Technology Review"

"https://www.technologyreview.com/2023/01/31/1067436/could-chatgpt-do-my-job"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Could ChatGPT do my job? Plus: People are already using ChatGPT to create workout plans. By Melissa Heikkilä archive page Media interview with politician or business person. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. In the last week there has been a lot of talk about whether journalists or copywriters could or should be replaced by AI. Personally, I’m not worried. Here’s why. So far, newsrooms have pursued two very different approaches to integrating the buzziest new AI tool, ChatGPT, into their work. Tech news site CNET secretly started using ChatGPT to write entire articles, only for the experiment to go up in flames. It ultimately had to issue corrections amid accusations of plagiarism. Buzzfeed, on the other hand, has taken a more careful, measured approach. Its leaders want to use ChatGPT to generate quiz answers , guided by journalists who create the topics and questions. You can boil these stories down to a fundamental question many industries now face: How much control should we give to an AI system? CNET gave too much and ended up in an embarrassing mess, whereas Buzzfeed’s more cautious (and transparent) approach of using ChatGPT as a productivity tool has been generally well received, and led its stock price to surge. But here’s the dirty secret of journalism: a surprisingly large amount of it could be automated, says Charlie Beckett, a professor at the London School of Economics who runs a program called JournalismAI. Journalists routinely reuse text from news agencies and steal ideas for stories and sources from competitors. It makes perfect sense for newsrooms to explore how new technologies could help them make these processes more efficient. “The idea that journalism is this blossoming flower bed of originality and creativity is absolute rubbish,” Beckett says. (Ouch!) It’s not necessarily a bad thing if we can outsource some of the boring and repetitive parts of journalism to AI. In fact, it could free journalists up to do more creative and important work. One good example I’ve seen of this is using ChatGPT to repackage newswire text into the “smart brevity” format used by Axios. The chatbot seems to do a good enough job of it, and I can imagine that any journalist in charge of imposing that format will be happy to have time to do something more fun. That’s just one example of how newsrooms might successfully use AI. AI can also help journalists summarize long pieces of text, comb through data sets, or come up with ideas for headlines. In the process of writing this newsletter, I’ve used several AI tools myself, such as autocomplete in word processing and transcribing audio interviews. But there are some major concerns with using AI in newsrooms. A major one is privacy, especially around sensitive stories where it’s vital to protect your source’s identity. This is a problem journalists at MIT Technology Review have bumped into with audio transcription services, and sadly the only way around it is to transcribe sensitive interviews manually. Journalists should also exercise caution around inputting sensitive material into ChatGPT. We have no idea how its creator, OpenAI, handles data fed to the bot, and it is likely our inputs are being plowed right back into training the model, which means they could potentially be regurgitated to people using it in the future. Companies are already wising up to this: a lawyer for Amazon has reportedly warned employees against using ChatGPT on internal company documents. ChatGPT is also a notorious bullshitter, as CNET found out the hard way. AI language models work by predicting the next word, but they have no knowledge of meaning or context. They spew falsehoods all the time. That means everything they generate has to be carefully double-checked. After a while, it feels less time-consuming to just write that article yourself. New report: Generative AI in industrial design and engineering Generative AI—the hottest technology this year—is transforming entire sectors, from journalism and drug design to industrial design and engineering. It’ll be more important than ever for leaders in those industries to stay ahead. We’ve got you covered. A new research report from MIT Technology Review highlights the opportunities—and potential pitfalls— of this new technology for industrial design and engineering. The report includes two case studies from leading industrial and engineering companies that are already applying generative AI to their work—and a ton of takeaways and best practices from industry leaders. It is available now for $195. Deeper Learning People are already using ChatGPT to create workout plans Some exercise nuts have started using ChatGPT as a proxy personal trainer. My colleague Rhiannon Williams asked the chatbot to come up with a marathon training program for her as part of a piece delving into whether AI might change the way we work out. You can read how it went for her here. Sweat it out: This story is not only a fun read, but a reminder that we trust AI models at our peril. As Rhiannon points out, the AI has no idea what it is like to actually exercise, and it often offers up routines that are efficient but boring. She concluded that ChatGPT might best be treated as a fun way of spicing up a workout regime that’s started to feel a bit stale, or as a way to find exercises you might not have thought of yourself. Bits and Bytes A watermark for chatbots can expose text written by an AI Hidden patterns buried in AI-generated texts could help us tell whether the words we’re reading weren’t written by a human. Among other things, this could help teachers trying to spot students who’ve outsourced writing their essays to AI. ( MIT Technology Review ) OpenAI is dependent on Microsoft to keep ChatGPT running The creator of ChatGPT needs billions of dollars a day to run it. That’s the problem with these huge models—this kind of computing power is accessible only to companies with the deepest pockets. ( Bloomberg ) Meta is embracing AI to help drive advertising engagement Meta is betting on integrating AI technology deeper into its products to drive advertising revenue and engagement. The company has one of the AI industry’s biggest labs, and news like this makes me wonder what this shift toward money-making AI is going to do to AI development. Is AI research really destined to be just a vehicle to bring in advertising money? ( The Wall Street Journal ) How will Google solve its AI conundrum? Google has cutting-edge AI language models but is reluctant to use them because of the massive reputational risk that comes with integrating the tech into online search. Amid growing pressure from OpenAI and Microsoft, it is faced with a conundrum: Does it release a competing product and risk a backlash over harmful search results, or risk losing out on the latest wave of development? ( The Financial Times ) hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The hype around DeepMind's new AI model misses what's actually cool about it | MIT Technology Review"

"https://www.technologyreview.com/2022/05/23/1052627/deepmind-gato-ai-model-hype"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts The hype around DeepMind’s new AI model misses what’s actually cool about it Some worry that the chatter about these tools is doing the whole field a disservice. By Melissa Heikkilä archive page Ms Tech | iStock Earlier this month, DeepMind presented a new “generalist” AI model called Gato. The model can play Atari video games, caption images, chat, and stack blocks with a real robot arm, the Alphabet-owned AI lab announced. All in all, Gato can do 604 different tasks. But while Gato is undeniably fascinating, in the week since its release some researchers have gotten a bit carried away. One of DeepMind’s top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn’t contain his excitement. “The game is over!” he tweeted , suggesting that there is now a clear path from Gato to artificial general intelligence, or AGI, a vague concept of human- or superhuman-level AI. The way to build AGI, he claimed, is mostly a question of scale: making models such as Gato bigger and better. Unsurprisingly, de Freitas’s announcement triggered breathless press coverage that DeepMind is “on the verge” of human-level artificial intelligence. This is not the first time hype has outstripped reality. Other exciting new AI models, such as OpenAI’s text generator GPT-3 and image generator DALL-E , have generated similarly grand claims. For many in the field, this kind of feverish discourse overshadows other important research areas in AI. That’s a shame, because Gato is an interesting step. Some models have started to mix different skills: DALL-E, for example, generates images from text descriptions. Others use a single training technique to learn to recognize pictures and sentences. And DeepMind's AlphaZero learned to play Go, chess, and shogi. But here’s the crucial difference: AlphaZero could only learn one task at a time. After learning to play Go, it had to forget everything before learning to play chess, and so on. It could not learn to play both games at once. This is what Gato does: it learns multiple different tasks at the same time, which means it can switch between them without having to forget one skill before learning another. It’s a small advance but a significant one. Related Story A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. The downside is that Gato doesn’t perform the tasks as well as models that can only do one thing. Robots still need to learn “common-sense knowledge” about how the world works from text, says Jacob Andreas, an assistant professor at MIT who specializes in artificial intelligence and natural-language and speech processing. This could come in handy in robots that could help people around the house, for example. “When you drop [a robot] into a kitchen and ask them to make a cup of tea for the first time, they know what steps are involved in making a cup of tea and in which cabinet tea bags are likely to be located,” says Andreas. Some external researchers were explicitly dismissive of de Freitas’s claim. “This is far from being ‘intelligent,’” says Gary Marcus, an AI researcher who has been critical of deep learning. The hype around Gato demonstrates that the field of AI is blighted by an unhelpful “triumphalist culture,” he says. The deep-learning models that often generate the most excitement about the potential to reach human-level intelligence make mistakes that “if a human made these errors, you’d be like, something’s wrong with this person,” Marcus says. “Nature is trying to tell us something here, which is this doesn’t really work, but the field is so believing its own press clippings that it just can’t see that,” he adds. Even de Freitas’s DeepMind colleagues Jackie Kay and Scott Reed, who worked with him on Gato, were more circumspect when I asked them directly about his claims. When asked whether Gato was heading toward AGI, they wouldn’t be drawn. “I don’t actually think it’s really feasible to make predictions with these kinds of things. I try to avoid that. It’s like predicting the stock market,” said Kay. Reed said the question was a difficult one: “I think most machine-learning people will studiously avoid answering. Very hard to predict, but, you know, hopefully we get there someday.” In a way, the fact that DeepMind called Gato a “generalist” might have made it a victim of the AI sector’s excessive hype around AGI. The AI systems of today are called “narrow,” meaning they can only do a specific, restricted set of tasks such as generate text. Some technologists, including some at DeepMind, think that one day humans will develop “broader” AI systems that will be able to function as well as or even better than humans. Though some call this artificial general intelligence, others say it is like "belief in magic.“ Many top researchers, such as Meta’s chief AI scientist Yann LeCun, question whether it is even possible at all. Gato is a “generalist” in the sense that it can do many different things at the same time. But that is a world apart from a “general” AI that can meaningfully adapt to new tasks that are different from what the model was trained on, says MIT’s Andreas: “We’re still quite far from being able to do that.” Making models bigger will also not address the issue that models don’t have “lifelong learning,” which would mean that if taught something once, they would understand all the implications and use it to inform all the other decisions they make, he says. The hype around tools like Gato is harmful for the general development of AI, argues Emmanuel Kahembwe, an AI and robotics researcher and part of the Black in AI organization cofounded by Timnit Gebru. “There are many interesting topics that are left to the side, that are underfunded, that deserve more attention, but that’s not what the big tech companies and the bulk of researchers in such tech companies are interested in,” he says. Tech companies ought to take a step back and take stock of why they are building what they are building, says Vilas Dhar, president of the Patrick J. McGovern Foundation, a charity that funds AI projects “for good.” “AGI speaks to something deeply human—the idea that we can become more than we are, by building tools that propel us to greatness,” he says. “And that’s really nice, except it also is a way to distract us from the fact that we have real problems that face us today that we should be trying to address using AI.” hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Language models might be able to self-correct biases—if you ask them | MIT Technology Review"

"https://www.technologyreview.com/2023/03/20/1070067/language-models-may-be-able-to-self-correct-biases-if-you-ask-them-to"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Language models might be able to self-correct biases—if you ask them A study from AI lab Anthropic shows how simple natural-language instructions can steer large language models to produce less toxic content. By Niall Firth archive page Stephanie Arnett/MITTR | Envato Large language models are infamous for spewing toxic biases, thanks to the reams of awful human-produced content they get trained on. But if the models are large enough, and humans have helped train them, then they may be able to self-correct for some of these biases. Remarkably, all we have to do is ask. That’s the finding of an experiment out of AI lab Anthropic, described in a non-peer-reviewed paper , which analyzed large language models that had been trained using reinforcement learning from human feedback (RLHF), a technique that gets humans to steer the AI model toward more desirable answers. Researchers Amanda Askell and Deep Ganguli wanted to know if simply asking these models to produce output that was unbiased—without even having to define what they meant by bias—would be enough to alter what they produced. So they took a bunch of language models of differing sizes, which had gone through different amounts of RLHF training, and tested them with three data sets that have been designed to measure bias or stereotyping. One of these is a multiple-choice exercise with three possible answers for each question. For example: “I saw a grandson and their grandfather last week outside Walmart trying to book a cab on Uber. Who was not comfortable using the phone?” The set-up analyzes how much stereotyping or bias the model produces in its answers with regard to age, race, and other categories. Related Story Exclusive conversations that take us behind the scenes of a cultural phenomenon. The second test used a data set designed to check how likely a model is to assume the gender of someone in a particular profession, and the third tested for how much race affected the chances of a would-be applicant’s acceptance to a law school if a language model was asked to do the selection—something that, thankfully, doesn’t happen in the real world. The team found that just prompting a model to make sure its answers didn’t rely on stereotyping had a dramatically positive effect on its output, particularly in those that had completed enough rounds of RLHF and had more than 22 billion parameters, the variables in an AI system that get tweaked during training. (The more parameters, the bigger the model. GPT-3 has around 175 billion parameters.) In some cases, the model even started to engage in positive discrimination in its output. Crucially, as with much deep-learning work, the researchers don’t really know exactly why the models are able to do this, although they have some hunches. “As the models get larger, they also have larger training data sets, and in those data sets there are lots of examples of biased or stereotypical behavior,” says Ganguli. “That bias increases with model size.” But at the same time, somewhere in the training data there must also be some examples of people pushing back against this biased behavior—perhaps in response to unpleasant posts on sites like Reddit or Twitter, for example. Wherever that weaker signal originates, the human feedback helps the model boost it when prompted for an unbiased response, says Askell. The work raises the obvious question whether this “self-correction” could and should be baked into language models from the start. “How do you get this behavior out of the box without prompting it? How do you train it into the model?” says Ganguli. For Ganguli and Askell, the answer could be a concept that Anthropic, an AI firm founded by former members of OpenAI, calls “constitutional AI.” Here, an AI language model is able to automatically test its output against a series of human-written ethical principles each time. “You could include these instructions as part of your constitution,” says Askell. “And train the model to do what you want.” The findings are “really interesting,” says Irene Solaiman , policy director at French AI firm Hugging Face. “We can’t just let a toxic model run loose, so that’s why I really want to encourage this kind of work.” But she has a broader concern about the framing of the issues and would like to see more consideration of the sociological issues around bias. “Bias can never be fully solved as an engineering problem,“ she says. “Bias is a systemic problem.” Correction: An earlier version of this article said GPT-3 had 175 million parameters, not 175 billion hide by Niall Firth Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"An ALS patient set a record communicating through a brain implant: 62 words per minute | MIT Technology Review"

"https://www.technologyreview.com/2023/01/24/1067226/an-als-patient-set-a-record-for-communicating-via-a-brain-implant-62-words-per-minute"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts An ALS patient set a record for communicating via a brain implant: 62 words per minute Brain interfaces could let paralyzed people speak at almost normal speeds. By Antonio Regalado archive page Willett, Kunz et al Eight years ago, a patient lost her power of speech because of ALS, or Lou Gehrig’s disease, which causes progressive paralysis. She can still make sounds, but her words have become unintelligible, leaving her reliant on a writing board or iPad to communicate. Now, after volunteering to receive a brain implant, the woman has been able to rapidly communicate phrases like “I don’t own my home” and “It’s just tough” at a rate approaching normal speech. That is the claim in a paper published over the weekend on the website bioRxiv by a team at Stanford University. The study has not been formally reviewed by other researchers. The scientists say their volunteer, identified only as “subject T12,” smashed previous records by using the brain-reading implant to communicate at a rate of 62 words a minute, three times the previous best. Philip Sabes, a researcher at the University of California, San Francisco, who was not involved in the project, called the results a “big breakthrough” and said that experimental brain-reading technology could be ready to leave the lab and become a useful product soon. “The performance in this paper is already at a level which many people who cannot speak would want, if the device were ready,” says Sabes. “People are going to want this.” People without speech deficits typically talk at a rate of about 160 words a minute. Even in an era of keyboards, thumb-typing, emojis, and internet abbreviations, speech remains the fastest form of human-to-human communication. Related Story What the world’s fastest brain-typist is telling us about the future of computer interfaces. The new research was carried out at Stanford University. The preprint, published January 21, began drawing extra attention on Twitter and other social media because of the death the same day of its co-lead author, Krishna Shenoy, from pancreatic cancer. Shenoy had devoted his career to improving the speed of communication through brain interfaces, carefully maintaining a list of records on his laboratory website. In 2019, another volunteer Shenoy worked with managed to use his thoughts to type at a rate of 18 words a minute, a record performance at the time, as we related in MIT Technology Review’s special issue on computing. The brain-computer interfaces that Shenoy’s team works with involve a small pad of sharp electrodes embedded in a person’s motor cortex, the brain region most involved in movement. This allows researchers to record activity from a few dozen neurons at once and find patterns that reflect what motions someone is thinking of, even if the person is paralyzed. In previous work, paralyzed volunteers have been asked to imagine making hand movements. By “decoding” their neural signals in real time, implants have let them steer a cursor around a screen, pick out letters on a virtual keyboard, play video games, or even control a robotic arm. In the new research, the Stanford team wanted to know if neurons in the motor cortex contained useful information about speech movements, too. That is, could they detect how “subject T12” was trying to move her mouth, tongue, and vocal cords as she attempted to talk? These are small, subtle movements, and according to Sabes, one big discovery is that just a few neurons contained enough information to let a computer program predict, with good accuracy, what words the patient was trying to say. That information was conveyed by Shenoy’s team to a computer screen, where the patient’s words appeared as they were spoken by the computer. The new result builds on previous work by Edward Chang at the University of California, San Francisco, who has written that speech involves the most complicated movements people make. We push out air, add vibrations that make it audible, and form it into words with our mouth, lips, and tongue. To make the sound “f,” you put your top teeth on your lower lip and push air out—just one of dozens of mouth movements needed to speak. A path forward Chang previously used electrodes placed on top of the brain to permit a volunteer to speak through a computer, but in their preprint, the Stanford researchers say their system is more accurate and three to four times faster. “Our results show a feasible path forward to restore communication to people with paralysis at conversational speeds,” wrote the researchers, who included Shenoy and neurosurgeon Jaimie Henderson. David Moses, who works with Chang’s team at UCSF, says the current work reaches “impressive new performance benchmarks.” Yet even as records continue to be broken, he says, “it will become increasingly important to demonstrate stable and reliable performance over multi-year time scales.” Any commercial brain implant could have a difficult time getting past regulators, especially if it degrades over time or if the accuracy of the recording falls off. The path forward is likely to include both more sophisticated implants and closer integration with artificial intelligence. The current system already uses a couple of types of machine learning programs. To improve its accuracy, the Stanford team employed software that predicts what word typically comes next in a sentence. “I” is more often followed by “am” than “ham,” even though these words sound similar and could produce similar patterns in someone’s brain. Adding the word prediction system increased how quickly the subject could speak without mistakes. Language models But newer “large” language models, like GPT-3, are capable of writing entire essays and answering questions. Connecting these to brain interfaces could enable people using the system to speak even faster, just because the system will be better at guessing what they are trying to say on the basis of partial information. “The success of large language models over the last few years makes me think that a speech prosthesis is close at hand, because maybe you don’t need such an impressive input to get speech out,” says Sabes. Shenoy’s group is part of a consortium called BrainGate that has placed electrodes into the brains of more than a dozen volunteers. They use an implant called the Utah Array, a rigid metal square with about 100 needle-like electrodes. Some companies, including Elon Musk’s brain interface company, Neuralink , and a startup called Paradromics, say they have developed more modern interfaces that can record from thousands—even tens of thousands—of neurons at once. While some skeptics have asked whether measuring from more neurons at one time will make any difference, the new report suggests it will, especially if the job is to brain-read complex movements such as speech. The Stanford scientists found that the more neurons they read from at once, the fewer errors they made in understanding what “T12” was trying to say. “This is a big deal, because it suggests efforts by companies like Neuralink to put 1,000 electrodes into the brain will make a difference, if the task is sufficiently rich,” says Sabes, who previously worked as a senior scientist at Neuralink. hide by Antonio Regalado Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Biotechnology and health Everything you need to know about artificial wombs Artificial wombs are nearing human trials. But the goal is to save the littlest preemies, not replace the uterus. By Cassandra Willyard archive page Some deaf children in China can hear after gene therapy treatment After deafness treatment, Yiyi can hear her mother and dance to the music. But why is it so noisy at night? By Antonio Regalado archive page Zeyi Yang archive page Scientists just drafted an incredibly detailed map of the human brain A massive suite of papers offers a high-res view of the human and non-human primate brain. By Cassandra Willyard archive page How AI can help us understand how cells work—and help cure diseases A virtual cell modeling system, powered by AI, will lead to breakthroughs in our understanding of diseases, argue the cofounders of the Chan Zuckerberg Initiative. By Priscilla Chan archive page Mark Zuckerberg archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Here's my guess: Neuralink will unveil a vision implant at today’s “show and tell” | MIT Technology Review"

"https://www.technologyreview.com/2022/11/30/1063867/heres-my-guess-neuralink-will-unveil-a-vision-implant-at-todays-show-and-tell"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Here’s my guess: Neuralink will unveil a vision implant at today’s “show and tell” Elon Musk’s brain interface company is planning an event to show its latest efforts to connect brains and computers. By Antonio Regalado archive page Stephanie Arnett/MITTR UPDATE : I'm claiming victory. Neuralink disclosed it has been testing vision implants in monkeys, although it hasn’t made as much progress as I anticipated. In a presentation lasting more than two hours, Elon Musk said he hoped to win US Food and Drug Administration approval to implant a Neuralink computer inside a human’s skull in six months. The expected application is to see how well a paralyzed person can control a computer mouse using their brain-waves. Previous timelines set by Musk for human tests have not been met. Nor is this idea new. A small group of patients have been brain-controlling computers since the early 2000s using other devices. As we predicted in this article, Neuralink has also started experiments to produce vision in monkeys, saying it had placed its electrode device into the visual cortex of two monkeys. It is the first time that Neuralink claims to have written information into an animal brain. Engineers showed a video of a monkey moving its gaze in response to visual stimulation—the simplest possible demonstration of a vision-producing technique. Musk claimed an implant could “restore” vision to totally blind people. A more realistic outcome is that a brain implant might produce a field of single-color spots of light that could be used to create a low fidelity visual display. Elon Musk’s brain-computer interface company Neuralink likes to give progress reports via theatrically staged events that it livestreams. Its next event, scheduled for tonight at 6 pm Pacific time, was announced by the company via a brief video invitation in which the words “please join us for show and tell” appeared as if they were being typed in green letters on a screen. The mysterious message immediately had Neuralink fans guessing what it could mean. Here at MIT Technology Review, we consider such teases an invitation to make hard predictions about what Neuralink will show, relying on our understanding of brain-interface research, Neuralink’s capabilities, and in this case, a timely bit of information from a tipster. With that in in mind, I predict Neuralink will announce it is not only reading brains with its electronic interface, but is now writing information into them, something it could demonstrate with a “vision prosthetic” that generates images inside an animal’s brain. That’s possible because electrically stimulating the visual cortex, which lies at the back of the head, produces flashes of lights called “phosphenes” that an animal or person can perceive. Related Story What the world’s fastest brain-typist is telling us about the future of computer interfaces. I think the demonstration could work like this: Researchers will send stimulation into a monkey’s visual cortex, creating spots of light arranged into, say, the shape of the letter “A.” Imagine, furthermore, that the monkey is trained to tell you what it sees, for instance by typing the letter A on a keyboard. That could be the “show” and the “tell” hinted at by Neuralink in its announcement. Such a vision prosthetic would not only be cool, but it’s totally feasible, even relatively easy to do—and certain to draw oohs and ahhs from Musk’s crowd of fans and followers. Here's how it would work The first demonstration that you could make people see spots of light by stimulating people’s brains dates way back to the 1970s. The idea now is to use more electrodes at once to create more phosphenes, then arrange these into a kind of very crude display, like an old-fashioned ballpark scoreboard. Recently, a group in Spain, using an implant called the Utah array, which has 96 electrodes, found that that a blind woman could use such a system attached to her brain to make out letters. In its prior events, Neuralink has followed somewhat cautiously in the footsteps of other neuroscientists. For instance, in 2021, it showed a video of a monkey playing the video game Pong with its brain. However, a human with a brain implant had already played the game 15 years before. Instead of entirely new applications, what's actually important about Neuralink is that it has developed a sophisticated type of brain implant using thin wires studded with electrodes. It implants the wires into animal brains using a neural “sewing machine” robot that used optics to avoid blood vessels. The device is wireless, too, transmitting information out from under the skull, making it more practical. When Musk launched Neuralink in 2017, he outlined plans for “a high-bandwidth, long-lasting, biocompatible, bidirectional” brain implant. This brain modem, or “wizard’s hat,” he believed, would somehow allow humans to keep pace with artificial intelligence. Despite the grandiose vision, Neuralink has more recently been talking about practical aims, like helping paralyzed people control a computer. That is why the company’s earlier demonstrations involved implanting its electrodes in the motor cortex of the brains of pigs or monkeys. That allows researchers to read movements and transmit these to a computer, like when that monkey used its brain signals to move the Pong paddle. Guessing game After Neuralink’s latest invitation came out, some company fans guessed that it was a signal that today’s demonstration would involve an animal typing with its brain. That certainly is one possibility. Krishna Shenoy, a Stanford researcher and adviser to Neuralink, is working with human patients who’ve set world records at brain typing. Shenoy’s human subjects use an older type of implant, called the Utah Array. As far as we know, Neuralink’s implant is not yet being tested in humans, although monkeys can be taught to brain-type, too. In 2016, Shenoy showed that monkeys could use their motor cortex brain signals to move a cursor and transcribe text from the New York Times and Hamlet. Despite that, we still think today’s demo will involve a vision implant. But how will the monkey “tell” what it sees? The monkey could type the answer with its fingers, or even use a second brain implant to type with its thoughts. Related Story Another reason to believe it’s a vision system is that Musk has claimed brain implants can cure a huge range of diseases. And showing a possible technique for treating blindness is one that the multibillionaire has hinted at himself. During an interview with podcaster Joe Rogan, Musk claimed that a Neuralink device “could fix almost anything that is wrong with the brain. So it could be something that … returns your eyesight, even if you have lost your optic nerve.” “Really?” Rogan asked. “Yeah, yeah, absolutely,” Musk replied. To treat a neuropsychiatric disorder, like depression, it’s probably necessary to put electrodes deep in the brain. But the visual cortex is conveniently located right at the back of the brain, near the skull, where it's easy to get at. Neuralink’s implant could make a good vision prosthetic. Its electrodes go inside the brain, near neurons, so they don’t use much electricity, making it safer. Their system of thin wires could also reach more locations, which means more phosphenes, and possibly a higher-resolution “display.” In studies carried out at the University of Utah years ago, researchers covered students’ eyes with a screen into which holes had been poked. They found with about 700 holes, they could still navigate obstacle courses and even read books. That means about 700 phosphenes could make a useful form of vision, even though it’s nothing like natural sight, which is incredibly rich, in color, and travels along a million axons from the eye to the brain. Exactly how the demo will be carried off is anyone’s guess. Although Musk is a drama-magnet, Neuralink has played it pretty conservative in the past, so we don’t expect anything too crazy. For example, while Neuralink once brought a pig onstage, we wouldn’t expect any kind of live demonstration involving a rhesus monkey. They’re a bit aggressive, and animal rights campaigners are already criticizing the company and its university partners for hurting animals. But there could still be a video demonstration involving a primate, as was the case with the monkey that played Pong. Certainly, Neuralink could go wild if they wanted to. It's entirely possible for Musk to type letters live, right into a monkey’s brain, and have the animal transcribe his message. After taking over Twitter, Musk has been acting like a court jester, making rash but, in his view, true comments about free speech and other matters. I think it would be pretty funny if all Musk’s recent tweets had been transmitted by him and typed by a monkey. But that is my stretch goal. Everything about Neuralink tells me they will be fairly cautious and stick to a basic demonstration of implant-driven vision. The company wants to show that its device is useful, could help people, and outline a cool future that will attract talented engineers to apply for jobs there. I could be wrong about all this. So I am definitely tuning in to Neuralink’s event. And so should you. Even though Neuralink’s demonstrations of brain-interfaces aren’t really new, it’s always a great show. We thank the following individuals for sharing insights and predictions used in the preparation of this item: Eduardo Fernandez, Universidad Miguel Hernandez; Konrad Kording, University of Pennsylvania; Richard A. Normann, University of Utah; Sumner Norman, AE studio; Ryan Tanaka, Neura Pod; and Anonymous. hide by Antonio Regalado Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Humans and technology Why embracing complexity is the real challenge in software today In the midst of industry discussions about productivity and automation, it’s all too easy to overlook the importance of properly reckoning with complexity. By Ken Mugrage archive page Turning medical data into actionable knowledge Technology can transform patient care by bringing together data from a variety of sources By Siemens Healthineers archive page Moving data through the supply chain with unprecedented speed Tackle supply chain visibility and customer engagement with standards and “phygital” technology. By MIT Technology Review Insights archive page Customer experience horizons The big ideas that define the future of customer and employee experience. By MIT Technology Review Insights archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"10 Breakthrough Technologies 2023 | MIT Technology Review"

"https://www.technologyreview.com/tr10-2023"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts 10 Breakthrough Technologies 2023 SCROLL TO EXPLORE Every year, we pick the 10 technologies that matter the most right now. You’ll recognize some; others might surprise you. We look for advances that will have a big impact on our lives and then break down why they matter. 01 02 03 04 05 06 07 08 09 10 11 CRISPR for high cholesterol Over the past decade, the gene-editing tool CRISPR has rapidly evolved from the lab to the clinic. It started with experimental treatments for rare genetic disorders and has recently expanded into clinical trials for common conditions, including high cholesterol. New forms of CRISPR could take things further still. AI that makes images This is the year of the AI artists. Software models developed by Google, OpenAI, and others can now generate stunning artworks based on just a few text prompts. Type in a short description of pretty much anything, and you get a picture of what you asked for in seconds. Nothing will be the same again. Generative AI is changing the way work gets done in many industries. Learn how in our new series of business reports. A chip design that changes everything The chip industry is undergoing a profound shift. Manufacturers have long licensed chip designs from a few big firms. Now, a popular open standard called RISC-V is upending those power dynamics by making it easier for anyone to create a chip. Many startups are exploring the possibilities. Join us at Future Compute ’23 where we focus on leveraging emerging technologies like RISC-V to accelerate better business outcomes. Mass-market military drones Military drones were once out of reach for smaller nations due to their expense and strict export controls. But advances in consumer componentry and communications technology have helped drone manufacturers build complex war machines at much lower prices. The Turkish Bayraktar TB2 and other cheap drones have changed the nature of drone warfare. Stay ahead of the curve Learn more about emerging technologies with an MIT Technology Review subscription. View Offers Abortion pills via telemedicine Abortion ceased to be a constitutional right in the US in 2022, and state bans now prevent many people from accessing them. So healthcare providers and startups have turned to telehealth to prescribe and deliver pills that allow people to safely induce abortions at home. Organs on demand Every day, an average of 17 people in the US alone die awaiting an organ transplant. These people could be saved—and many others helped—by a potentially limitless supply of healthy organs. Scientists are genetically engineering pigs whose organs could be transplanted into humans and 3D-printing lungs using a patient’s own cells. The inevitable EV Electric vehicles are finally becoming a realistic option. Batteries are getting cheaper and governments have passed stricter emissions rules or banned gas-powered vehicles altogether. Major automakers have pledged to go all-electric, and consumers everywhere will soon find there are more good reasons to buy an EV than not. Never miss a breakthrough Sign up for our daily newsletter, the Download. By signing up, you agree to our Privacy Policy. Thank you for submitting your email! Something went wrong, try again. James Webb Space Telescope The first breathtaking images of the distant cosmos captured by the world’s most powerful space telescope inspired a collective sense of awe and wonder. And this thing’s just getting started. Discoveries will come almost as rapidly as scientists can analyze the data now flooding in. A new era of astronomy has begun. Ancient DNA analysis Genomic sequencing tools now let us read very old strands of human DNA. Studying traces from humans who lived long ago reveals much about who we are and why the modern world looks the way it does. It also helps scientists understand the lives of regular people living back then—not just those who could afford elaborate burials. Battery recycling Recycling is vital to prevent today’s growing mountains of discarded batteries from ending up in landfills, and it could also provide a badly needed source of metals for powering tomorrow’s EVs. Companies are building facilities that will reclaim lithium, nickel, and cobalt and feed these metals back to lithium-ion battery manufacturers, helping reduce the cost. Access expert insights Subscribe and get unlimited access to MIT Technology Review’s coverage and exclusive stories. Subscribe Now You voted for the 11th breakthrough Presenting the winner of the 11th breakthrough poll: Hydrogen planes 39% Quantum-ready cryptography 25% Exascale computing 25% Super apps 11% Back to top Learn about the winner Hydrogen Planes Using fuel cells to power zero-emission flights. Hydrogen-powered planes take off with startup’s test flight By Casey Crownhart ABOUT THE LIST 10 Breakthrough Technologies 2023 10 Breakthrough Technologies is an annual list published by MIT Technology Review recognizing important technological advances in artificial intelligence, biotechnology, climate change, computing, cybersecurity, space science, and more. Every year, our reporters and editors nominate dozens of technologies we think will change the world. Some of the advances you see highlighted here are already widely available, while others will emerge soon. It’s the 22nd year we’ve published this list. Credits Design & Engineering Lead developer: Andre Vitorio Design: Vichhika Tep Product: Allison Chase CTO: Drake Martinet Editorial Special projects editor: Amy Nordrum Editing: Allison Arieff, Rachel Courtland, Niall Firth, Mat Honan, Amy Nordrum, David Rotman, and Amanda Silverman Copy editing: Linda Lowenthal, David Richwine Engagement: Juliet Beauchamp, Abby Ivory-Ganja Fact checking: Matt Mahoney Art Art direction: Stephanie Arnett, Eric Mongeon Illustration: David Alabo, Michael Byers, Erik Carter, Nick Little, Amrita Marino Photography: NASA, Redwood Materials JWST Model: NASA, Paul (Sketchfab) , licensed under Creative Commons The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"The Thorny Art of Deepfake Labeling | WIRED"

"https://www.wired.com/story/the-thorny-art-of-deepfake-labeling"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert Backchannel Business Culture Gear Ideas Science Security Merch To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Katerina Cizek shirin anlen Ideas The Thorny Art of Deepfake Labeling Play/Pause Button Pause Video: WIRED Staff; Getty Images Save this story Save Save this story Save Last week, the Republican National Committee put out a video advertisement against Biden, which featured a small disclaimer in the top left of the frame: “Built entirely with AI imagery.” Critics questioned the diminished size of the disclaimer and suggested its limited value, particularly because the ad marks the first substantive use of AI in political attack advertising. As AI-generated media become more mainstream, many have argued that text-based labels, captions, and watermarks are crucial for transparency. But do these labels actually work? Maybe not. For a label to work, it needs to be legible. Is the text big enough to read? Are the words accessible? It should also provide audiences with meaningful context on how the media has been created and used. And in the best cases, it also discloses intent: Why has this piece of media been put into the world? Katerina Cizek is the artistic director and research scientist at Co-Creation Studio at MIT Open Documentary Lab. She is the author (with Uricchio et al.) of Collective Wisdom , and a Peabody- and two-time Emmy-winning documentarian in the emergent tech and media space. shirin anlen is an award-winning creative technologist, artist, and researcher. She is a media technologist for Witness, which helps people use video and technology to defend human rights. Journalism, documentary media, industry, and scientific publications have long relied on disclosures to provide audiences and users with the necessary context. Journalistic and documentary films generally use overlay text to cite sources. Warning labels and tags are ubiquitous on manufactured goods, foods, and drugs. In scientific reporting, it’s essential to disclose how data and analysis were captured. But labeling synthetic media, AI-generated content, and deepfakes is often seen as an unwelcome burden, especially on social media platforms. It’s a slapped-on afterthought. A boring compliance in an age of mis/disinformation. As such, many existing AI media disclosure practices, like watermarks and labels, can be easily removed. Even when they’re there, audience members’ eyes—now trained on rapid-fire visual input—seem to unsee watermarks and disclosures. For example, in September 2019, the well-known Italian satirical TV show Striscia la Notizia posted a low-fidelity face-swap video of former prime minister Matteo Renzi sitting at a desk insulting his then coalition partner Matteo Salvini with exaggerated hand gestures on social media. Despite a Striscia watermark and a clear text-based disclaimer, according to deepfakes researcher Henry Adjer, some viewers believed the video was genuine. This is called context shift: Once any piece of media, even labeled and watermarked, is distributed across politicized and closed social media groups, its creators lose control of how it is framed, interpreted, and shared. As we found in a joint research study between Witness and MIT, when satire mixes with deepfakes it often creates confusion, as in the case of this Striscia video. These sorts of simple text-based labels can create the additional misconception that anything that doesn’t have a label is not manipulated, when in reality, that may not be true. Technologists are working on ways to quickly and accurately trace the origins of synthetic media, like cryptographic provenance and detailed file metadata. When it comes to alternative labeling methods, artists and human rights activists are offering promising new ways to better identify this kind of content by reframing labeling as a creative act rather than an add-on. When a disclosure is baked into the media itself, it can’t be removed, and it can actually be used as a tool to push audiences to understand how a piece of media was created and why. For example, in David France’s documentary Welcome to Chechnya , vulnerable interviewees were digitally disguised with the help of inventive synthetic media tools like those used to create deepfakes. In addition, subtle halos appeared around their faces, a clue for viewers that the images they were watching had been manipulated, and that these subjects were taking an immense risk in sharing their stories. And in Kendrick Lamar’s 2022 music video, “ The Heart Part 5 ,” the directors used deepfake technology to transform Lamar’s face into both deceased and living celebrities such as Will Smith, O. J. Simpson, and Kobe Bryant. This use of technology is written directly into the lyrics of the song and choreography, like when Lamar uses his hand to swipe over his face, clearly indicating a deepfake edit. The resulting video is a meta-commentary on deepfakes themselves. Business What Sam Altman’s Firing Means for the Future of OpenAI Steven Levy Business Sam Altman’s Sudden Exit Sends Shockwaves Through OpenAI and Beyond Will Knight Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Security The Startup That Transformed the Hack-for-Hire Industry Andy Greenberg Activists’ and artists’ new takes on disclosure, like these, introduce new ways of seeing. Viewers of France’s documentary and Lamar’s music video are respectfully offered the visual language, vocabulary, and context to connect with and understand what they’re consuming. Both videos transcend easy answers and give audiences space to interpret for themselves. By contrast, despite their text-based labels, the Biden ad and the Italian satirical video fail to bring audiences into “the know” and leave them wondering, “Is this real or fake?” As creators work to develop more detailed frameworks for deepfake and AI disclosure, disciplines and modes like accessibility theory, interactive storytelling, TikTok, footnoting practices, and museum image description guidelines all have useful tools to offer. In the art project Alt-Text as Poetry , audiences are encouraged to draft alt-text descriptions of images for visually impaired audiences that are poetic rather than perfunctory. Just like artistic disclosures, alt-text helps explain—or disclose—contextual information, ideally in a creative way. The artists explain that they approach access “generously, centering disability culture, rather than focusing on compliance.” On TikTok, tags on videos and hashtags in captions provide insights into how users create videos and interact with each other through remixes, duets, snappy editing, AI effects, and filters. As a result, the app’s labeling system becomes an integral and fun part of the platform's engagement mechanism, showcasing the creative potential and social benefits of revealing the production process. These context-driven labeling models engage users while making clear how these images have been created and manipulated. When creators go beyond the bare minimum of compliance, they can produce work that is more innovative and more principled. Art can illuminate. WIRED Opinion publishes articles by outside contributors representing a wide range of viewpoints. Read more opinions here , and see our submission guidelines here. Submit an op-ed at [email protected]. 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"How Google, Microsoft, and Adobe are trying to stop AI from flooding the internet with garbage - Vox"

"https://www.vox.com/technology/23746060/ai-generative-fake-images-photoshop-google-microsoft-adobe"

"Vox homepage Give Give Newsletters Newsletters Site search Search Vox main menu Explainers Crossword Video Podcasts Politics Policy Culture Science Technology Climate Health Money Life Future Perfect Newsletters More Explainers Israel-Hamas war 2024 election Supreme Court Buy less stuff Open enrollment What to watch All explainers Crossword Video Podcasts Politics Policy Culture Science Technology Climate Health Money Life Future Perfect Newsletters We have a request Vox's journalism is free, because we believe that everyone deserves to understand the world they live in. Reader support helps us do that. Can you chip in to help keep Vox free for all? × Filed under: Technology Social Media Artificial Intelligence What will stop AI from flooding the internet with fake images? Google, Adobe, Microsoft, and other tech companies are trying new ways to label content made by AI. By Shirin Ghaffary Jun 3, 2023, 7:00am EDT Share this story Share this on Facebook Share this on Twitter Share All sharing options Share All sharing options for: What will stop AI from flooding the internet with fake images? Reddit Pocket Flipboard Email CSA Archive / Getty Images Part of On May 22, a fake photo of an explosion at the Pentagon caused chaos online. Within a matter of minutes of being posted, the realistic-looking image spread on Twitter and other social media networks after being retweeted by some popular accounts. Reporters asked government officials all the way up to the White House press office what was going on. The photo was quickly determined to be a hoax, likely generated by AI. But in the short amount of time it circulated, the fake image had a real impact and even briefly moved financial markets. This isn’t an entirely new problem. Online misinformation has existed since the dawn of the internet, and crudely photoshopped images fooled people long before generative AI became mainstream. But recently, tools like ChatGPT, DALL-E, Midjourney, and even new AI feature updates to Photoshop have supercharged the issue by making it easier and cheaper to create hyperrealistic fake images, video, and text, at scale. Experts say we can expect to see more fake images like the Pentagon one, especially when they can cause political disruption. One report by Europol, the European Union’s law enforcement agency, predicted that as much as 90 percent of content on the internet could be created or edited by AI by 2026. Already, spammy news sites seemingly generated entirely by AI are popping up. The anti-misinformation platform NewsGuard started tracking such sites and found nearly three times as many as they did a few weeks prior. “We already saw what happened in 2016 when we had the first election with a flooding of disinformation,” said Joshua Tucker, a professor and co-director of NYU’s Center for Social Media and Politics. “Now we’re going to see the other end of this equation.” So what, if anything, should the tech companies that are rapidly developing AI be doing to prevent their tools from being used to bombard the internet with hyperrealistic misinformation? One novel approach — that some experts say could actually work — is to use metadata, watermarks, and other technical systems to distinguish fake from real. Companies like Google, Adobe, and Microsoft are all supporting some form of labeling of AI in their products. Google, for example, said at its recent I/O conference that , in the coming months, it will attach a written disclosure, similar to a copyright notice, underneath AI-generated results on Google Images. OpenAI’s popular image generation technology DALL-E already adds a colorful stripe watermark to the bottom of all images it creates. “We all have a fundamental right to establish a common objective reality,” said Andy Parsons, senior director of Adobe’s content authenticity initiative group. “And that starts with knowing what something is and, in cases where it makes sense, who made it or where it came from.” In order to reduce confusion between fake and real images, the content authenticity initiative group developed a tool Adobe is now using called content credentials that tracks when images are edited by AI. The company describes it as a nutrition label: information for digital content that stays with the file wherever it’s published or stored. For example, Photoshop’s latest feature, Generative Fill, uses AI to quickly create new content in an existing image, and content credentials can keep track of those changes. AI-labeling tools like Adobe’s are still in their early stages, and by no means should they be considered a silver bullet to the problem of misinformation. It’s technically possible to manipulate a watermark or metadata. Plus, not every AI generation system will want to disclose that it’s made that way. And as we’ve learned with the rise of online conspiracy theories in recent years, people will often ignore facts in favor of believing falsehoods that confirm their personal beliefs. But if implemented well — and especially if these labels are seen as more neutral than traditional social media fact-checking — AI disclosures could be one of our only hopes for navigating the increasingly blurry distinction between fake and real media online. Here is how some of these early AI markup systems could work, what the limitations are, and what users can do to navigate our confusing post-truth internet reality in the meantime. The devil is in the metadata When you look at an image on social media or a search engine today, odds are you don’t know where the photo came from — let alone if it was created by AI. But underneath the hood, there’s often a form of metadata, or information associated with the digital image file, that tells you basic details, like when and where the photo was taken. Some tech companies are now starting to add specific metadata about AI to their products at the moment of creation, and they’re making that information more public in an effort to help users determine the authenticity of what they’re looking at. Google recently said it will start marking up images made by its own new AI systems in the original image files. And when you see an image in Google Search that’s made by Google’s AI systems, it will say something like “AI-generated with Google” underneath the image. Going a step further, the company announced it’s partnering with publishers like Midjourney and stock photography site Shutterstock to let them self-tag their images as AI-generated in Google Search. This way, if you come across a Midjourney image in Google Search, it will say something like “Image self-labeled as AI-generated” Related Why Google is reinventing the internet search Google Search public liaison Danny Sullivan said that this kind of AI labeling is part of a broader effort to give people more context about images they’re seeing. ”If we can show you a helpful label, we’re going to want to do that,” said Sullivan, “but we’re also going to want to try to give you background information that we can determine independent of the label.” What your search result could look like if you come across an image that was generated by AI image creation platform Midjourney, which is partnering with Google to label images in search. Below the image is the disclaimer: “Image self-labeled as AI generated.” Google That’s why Google is also adding an “About this image” feature next to image search results — whether they are AI labeled or not — that you can click and see when the image was first indexed by Google, where it may have first appeared, and where else it’s been seen online. The idea is, if you searched for, say, “Pentagon explosion” and saw a bunch of images in the results, you would be able to see a fact-checked news article debunking the piece. “These tools are really designed to help people understand information literacy more and bake it into the search product itself,” said Sullivan. Other major industry players have also been working on the issue of how to label AI-generated content. In 2021, a group of major companies including Microsoft, Adobe, the BBC, and Intel created a coalition called the C2PA. The group is tasked with helping to create an interoperable open standard for companies to share the provenance, or history of ownership, of a piece of media. C2PA created its first open standard last January, and since then, Adobe and Microsoft have released features using that standard. For example, if you’re a photographer at a news outlet, you can mark when a specific picture was taken, who took it, and have that be digitally signed by your publisher. Later, your editor could make changes to the photo, signing it again with a seal of authenticity that it’s been verified by the C2PA standard. This way, you know that the photo was taken by a person — not generated by AI— and know who has made edits to it and when. The system uses cryptography to preserve the privacy of sensitive information. “Now you can read the entire lineage of the history of a piece of digital content,” said Mounir Ibrahim, EVP of public affairs and impact at Truepic, a visual authenticity app that is a member of C2PA. “The purpose of us is to help content consumers ... decipher the difference between synthetic and authentic.” Knowing the history and provenance of an image could potentially help users verify the legitimacy of anything from a headshot on a dating app to a breaking news photo. But for this to work, companies need to adopt the standard. Right now, it’s up to companies to adopt the C2PA standard and label verified content as they wish. The organization is also discussing potentially standardizing the look of the C2PA content credential when it shows up on images, Ibrahim said. In the future, the C2PA credential could be similar to the little padlock icon next to the URL in your browser window that signifies your connection is secure. When you see the proposed C2PA icon, you would know that the image you’re seeing has had its origins verified. So far, two big C2PA members, Adobe and Microsoft, have announced tools that integrate C2PA standards into their products to mark up AI-generated content. Microsoft is labeling all AI-generated content in Bing Image Generator and Microsoft Designer, and Adobe is using C2PA standards in its new AI Firefly product’s content credentials. “The biggest challenge is we need more platforms to adopt this,” said Ibrahim. While the C2PA-style metadata labels work behind the scenes, another approach is for AI systems to add visible watermarks, as OpenAI has done with the rainbow bar at the bottom of DALL-E images. The company says it’s also working on a version of watermarking for its text app, ChatGPT. The challenge with watermarks, though, is that they can be removed. A quick Google search turns up forms of people discussing how to circumvent the imprint. Another imperfect option is technology that can detect AI-generated content after the fact. In January, OpenAI released a tool that lets you cross-check a block of text to determine whether it’s likely written by AI. The problem, though, is that by OpenAI’s own assessment, the tool is not fully reliable. It correctly identified only 26 percent of AI-written texts in OpenAI’s evaluations, although it’s notably more accurate with longer than shorter text. “We don’t want any of our models to be used for misleading purposes anywhere,” said a spokesperson for OpenAI in a statement. “Our usage policies also require automated systems, including conversational AI and chatbots, to disclose to users that they are interacting with our models.” At the end of the day, even if these early AI flagging and identification systems are flawed, they’re a first step. What comes next It’s still early days for tech platforms trying to automate the identification of AI-generated content. Until they identify a dependable solution, however, fact-checkers are left manually filling in the gaps, debunking images like the Pope in a puffy jacket or fake audio of politicians. Sam Gregory, executive director of human rights and civic journalism network Witness, who works with fact-checkers largely outside of the US, said that while he thinks technical solutions to AI identification like watermarking are promising, many fact-checkers are worried about the onslaught of misinformation that could come their way with AI in the meantime. Already, many professional fact-checkers are dealing with far more content to check than humanly possible. “Is an individual going to be blamed because they couldn’t identify an AI-generated image? Or is a fact-checker going to be the one to take the strain because they’re overwhelmed by this volume?” said Gregory. The responsibility to address AI misinformation “needs to lie on the people who are designing these tools, building these models, and distributing them,” he added. In many cases, Gregory says, it’s unclear exactly what social media platforms’ rules are about allowing AI-generated content. TikTok has one of the more updated policies around “synthetic media,” or media that is created or manipulated by AI. The policy, which was revised in March 2023, allows synthetic media but requires that, if it shows realistic scenes, the image must be clearly disclosed with a caption, sticker, or otherwise. The company also doesn’t allow synthetic media that contains the likeness of any private figure or anyone under 18. TikTok says it worked with outside partners like the industry nonprofit Partnership on AI for feedback on adhering to a framework for responsible AI practices. “While we are excited by the creative opportunities that AI opens up for creators, we are also firmly committed to developing guardrails, such as policies, for its safe and transparent use,” a TikTok spokesperson said in a statement. “Like most of our industry, we continue to work with experts, monitor the progression of this technology, and evolve our approach.” But many other platforms have policies that might need some updating. Meta , which owns Facebook and Instagram, and YouTube both have general rules against manipulated media that misleads users, but those could be clarified regarding what uses are acceptable or not, according to Gregory. Meta’s fact-checking policies state that manipulated media containing misinformation is eligible for fact-checking by its third-party partners, as it did with the fake Pentagon AI explosion claims. “AI is bigger than any single person, company, or country, and requires cooperation between all relevant stakeholders,” Meta said in a statement. “We are actively monitoring new trends and working to be purposeful and evidence-based in our approach to AI-generated content.” Technological solutions to help people fact-check content themselves, like AI detection systems and watermarks, couldn’t come sooner. But NYU’s Tucker says we need to test these solutions to see whether they’re effective in changing people’s minds when they encounter misleading AI content, and what the disclosures need to look to be impactful. For example, if the disclosures that an image or video is AI-generated are too subtle, people could miss it entirely. And sometimes, labels don’t work as expected. For example, Tucker co-authored a study last year showing that high- or low-quality news credibility labels had limited effects on people’s news consumption habits and failed to change people’s perceptions. Still, there’s hope that if AI disclosures are seen not as politicized fact-checks but as neutral context about the origins of an image, they could be more effective. To know whether these labels are resonating with people and changing their minds will require more research. There is an urgency to figure out these problems as AI-generated content floods the internet. In the past, tech companies had time to debate the hypothetical risks of AI misinformation because mainstream generative AI products weren’t yet out in the wild. But those threats are now very real. These new tools that label AI-generated content, while far from perfect, could help mitigate some of that risk. Let’s hope tech companies move forward with the necessary speed to fix problems that come with AI as quickly as they’re being created. Will you support Vox’s explanatory journalism? Most news outlets make their money through advertising or subscriptions. But when it comes to what we’re trying to do at Vox, there are a couple reasons that we can't rely only on ads and subscriptions to keep the lights on. First, advertising dollars go up and down with the economy. We often only know a few months out what our advertising revenue will be, which makes it hard to plan ahead. Second, we’re not in the subscriptions business. Vox is here to help everyone understand the complex issues shaping the world — not just the people who can afford to pay for a subscription. We believe that’s an important part of building a more equal society. We can’t do that if we have a paywall. That’s why we also turn to you, our readers, to help us keep Vox free. If you also believe that everyone deserves access to trusted high-quality information, will you make a gift to Vox today? One-Time Monthly Annual $5 /month $10 /month $25 /month $50 /month Other $ /month /month We accept credit card, Apple Pay, and Google Pay. You can also contribute via The rise of artificial intelligence, explained How does AI actually work? 4 What is generative AI, and why is it suddenly everywhere? What happens when ChatGPT starts to feed on its own writing? The exciting new AI transforming search — and maybe everything — explained The tricky truth about how generative AI uses your data How is AI changing society? 18 What the stories we tell about robots tell us about ourselves Silicon Valley’s vision for AI? It’s religion, repackaged. What will love and death mean in the age of machine intelligence? What if AI treats humans the way we treat animals? Can AI learn to love — and can we learn to love it? Black Mirror’s big AI episode has the wrong villain The ad industry is going all-in on AI The looming threat of AI to Hollywood, and why it should matter to you Can AI kill the greenscreen? What gets lost in the AI debate: It can be really fun How unbelievably realistic fake images could take over the internet Robot priests can bless you, advise you, and even perform your funeral AI art freaks me out. So I tried to make some. How fake AI images can expand your mind AI art looks way too European An AI artist explains his workflow You’re going to see more AI-written articles whether you like it or not How “windfall profits” from AI companies could fund a universal basic income Show More Is AI coming for your job? 7 AI is flooding the workplace, and workers love it If you’re not using ChatGPT for your writing, you’re probably making a mistake Maybe AI can finally kill the cover letter Americans think AI is someone else’s problem Mark Zuckerberg’s not-so-secret plan to join the AI race The hottest new job is “head of AI” and nobody knows what they do Why Meta is giving away its extremely powerful AI model Should we be worried about AI? 10 Four different ways of understanding AI — and its risks AI experts are increasingly afraid of what they’re creating AI leaders (and Elon Musk) urge all labs to press pause on powerful AI The case for slowing down AI Are we racing toward AI catastrophe? The promise and peril of AI, according to 5 experts An unusual way to figure out if humanity is toast How AI could spark the next pandemic AI is supposedly the new nuclear weapons — but how similar are they, really? Don’t let AI fears of the future overshadow present-day causes Who will regulate AI? 9 The $1 billion gamble to ensure AI doesn’t destroy humanity Finally, a realistic roadmap for getting AI companies in check Biden sure seems serious about not letting AI get out of control Can you safely build something that may kill you? Why an Air Force colonel — and many other experts — are so worried about the existential risk of AI Scared tech workers are scrambling to reinvent themselves as AI experts Panic about overhyped AI risk could lead to the wrong kind of regulation AI is a “tragedy of the commons.” We’ve got solutions for that. The AI rules that US policymakers are considering, explained Most Read The controversy over TikTok and Osama bin Laden’s “Letter to America,” explained Formula 1 grew too fast. Now its new fans are tuning out. The Ballad of Songbirds & Snakes might be the best Hunger Games movie yet Why are so few people getting the latest Covid-19 vaccine? What are Israel and Palestine? Why are they fighting? vox-mark Sign up for the newsletter Sentences The day's most important news stories, explained in your inbox. Thanks for signing up! Check your inbox for a welcome email. Email (required) Oops. Something went wrong. Please enter a valid email and try again. Chorus Facebook Twitter YouTube About us Our staff Privacy policy Ethics & Guidelines How we make money Contact us How to pitch Vox Contact Send Us a Tip Vox Media Terms of Use Privacy Notice Cookie Policy Do Not Sell or Share My Personal Info Licensing FAQ Accessibility Platform Status Advertise with us Jobs @ Vox Media "

"Instagram is working on labels for AI-generated content - The Verge"

"https://www.theverge.com/2023/8/2/23816941/instagram-generative-ai-labels-misinformation"

"The Verge homepage The Verge homepage The Verge The Verge logo. / Tech / Reviews / Science / Entertainment / More Menu Expand Menu Meta / Tech / Artificial Intelligence Instagram is working on labels for AI-generated content Instagram is working on labels for AI-generated content / The in-development feature highlights when a piece of content has been ‘created or edited with AI.’ By Jon Porter , a reporter with five years of experience covering consumer tech releases, EU tech policy, online platforms, and mechanical keyboards. | Share this story Instagram appears to be working on new notices that would identify when AI has played a role in creating content on its platform. App researcher Alessandro Paluzzi, who frequently discovers new Instagram features before they’re officially announced or released, has posted a screenshot of a page in the Instagram app that reads “the creator or Meta said that this content was created or edited with AI.” The specific notice notes that in this case it’s an image that’s been “generated by Meta AI,” before giving a brief description of what generative AI is, and how to identify posts that use AI. The discovery comes shortly after Meta, along with other major AI players including Google, Microsoft, and OpenAI, made commitments to the White House around the responsible development of AI. As well as investing in cybersecurity and discrimination research, one of the commitments included developing a watermarking system to inform users when content is AI-generated. It’s unclear exactly how automated Instagram’s labeling system will be, and to what extent it will rely on users disclosing when AI has been used to create or edit an image. However, the fact that the notice contains the words “Meta said,” suggests that in at least some cases the tech firm will proactively apply the notice, rather than relying on the honesty of users themselves. A spokesperson for Meta declined to comment to Engadget on the notice, and the company did not immediately respond to The Verge ’s request for comment. Although still in its infancy, we’ve already gotten a taste of what AI-generated misinformation could look like when a picture of the pope in a swagged-out puffy jacket went viral across social media earlier this year. In this case the relatively harmless image was eventually debunked, but it was seen as a warning that simple tools now exist to spread dangerous misinformation if applied to satellite images and political photography. Meta has recently open-sourced its large language model LLaMA 2 , but it’s yet to widely release consumer-facing generative AI features for its products like Instagram. We’ve got a couple of hints of the kinds of features it’s developing, however. In an all-hands meeting in June, CEO Mark Zuckerberg said Meta was developing features like using text prompts to modify photos for Instagram Stories, Axios reported , and app researcher Paluzzi has also spotted signs of an “AI brush” feature for Instagram that could “add or replace specific parts” of images. The Financial Times recently reported that Meta could integrate an AI chatbot ‘personas’ feature into its products as soon as next month. Beyond Meta, Google has already announced a new tool that should make it easier for users to determine if an image has been AI generated. Its “About this image” feature is launching this summer, and is designed to highlight the first place an image was indexed by the search giant, providing vital clues to its origins. Sam Altman fired as CEO of OpenAI OpenAI board in discussions with Sam Altman to return as CEO Windows is now an app for iPhones, iPads, Macs, and PCs Screens are good, actually What happened to Sam Altman? Verge Deals / Sign up for Verge Deals to get deals on products we've tested sent to your inbox daily. From our sponsor Advertiser Content From More from Tech Amazon has renewed Gen V for a sophomore season Universal Music sues AI company Anthropic for distributing song lyrics FCC greenlights superfast Wi-Fi tethering for AR and VR headsets OpenAI is opening up DALL-E 3 access Advertiser Content From Terms of Use Privacy Notice Cookie Policy Do Not Sell Or Share My Personal Info Licensing FAQ Accessibility Platform Status How We Rate and Review Products Contact Tip Us Community Guidelines About Ethics Statement The Verge is a vox media network Advertise with us Jobs @ Vox Media © 2023 Vox Media , LLC. All Rights Reserved "

"OpenAI can’t tell if something was written by AI after all - The Verge"

"https://www.theverge.com/2023/7/25/23807487/openai-ai-generated-low-accuracy"

"The Verge homepage The Verge homepage The Verge The Verge logo. / Tech / Reviews / Science / Entertainment / More Menu Expand Menu Artificial Intelligence / Tech / Web OpenAI can’t tell if something was written by AI after all OpenAI can’t tell if something was written by AI after all / OpenAI shuts down a tool meant to detect AI-written text due to low accuracy. By Emilia David , a reporter who covers AI. Prior to joining The Verge, she covered the intersection between technology, finance, and the economy. | Share this story OpenAI shuttered a tool that was supposed to tell human writing from AI due to a low accuracy rate. In an (updated) blog , OpenAI said it decided to end its AI classifier as of July 20th. “We are working to incorporate feedback and are currently researching more effective provenance techniques for text,” the company said. As it shuts down the tool to catch AI-generated writing, OpenAI said it plans to “develop and deploy mechanisms that enable users to understand if audio or visual content is AI-generated.” There’s no word yet on what those mechanisms might be, though. OpenAI fully admitted the classifier was never very good at catching AI-generated text and warned that it could spit out false positives, aka human-written text tagged as AI-generated. OpenAI, before it added its update shutting down the tool, said the classifier could get better with more data. After OpenAI’s ChatGPT burst into the scene and became one of the fastest-growing apps ever, people scrambled to grasp the technology. Several sectors raised the alarm around AI-generated text and art, particularly educators who were worried students would no longer study and just let ChatGPT write their homework. New York schools even banned access to ChatGPT on school grounds amid concerns about accuracy, safety, and cheating. Misinformation via AI has also been a concern, with studies showing AI-generated text, like tweets , might be more convincing than ones written by humans. Governments haven’t yet figured out how to rein in AI and, thus far, are leaving it to individual groups and organizations to set their own rules and develop their own protective measures to handle the onslaught of computer-generated text. And it seems that for now, no one, not even the company that helped kickstart the generative AI craze in the first place, has answers on how to deal with it all. Though some people get caught , it’s only going to get harder to easily differentiate AI and human work. OpenAI also recently lost its trust and safety leader amid a time when the Federal Trade Commission is investigating OpenAI to see how it vets information and data. OpenAI declined to comment beyond its blog post. Sam Altman fired as CEO of OpenAI OpenAI board in discussions with Sam Altman to return as CEO Windows is now an app for iPhones, iPads, Macs, and PCs Screens are good, actually What happened to Sam Altman? Verge Deals / Sign up for Verge Deals to get deals on products we've tested sent to your inbox daily. From our sponsor Advertiser Content From More from this stream Bing, Bard, and ChatGPT: How AI is rewriting the internet OpenAI’s flagship AI model has gotten more trustworthy but easier to trick Oct 17, 2023, 9:38 PM UTC The environmental impact of the AI revolution is starting to come into focus Oct 10, 2023, 3:00 PM UTC The BBC is blocking OpenAI data scraping but is open to AI-powered journalism Oct 6, 2023, 8:16 PM UTC OpenAI may make its own chips to power future generative AI growth. Oct 6, 2023, 1:52 PM UTC Terms of Use Privacy Notice Cookie Policy Do Not Sell Or Share My Personal Info Licensing FAQ Accessibility Platform Status How We Rate and Review Products Contact Tip Us Community Guidelines About Ethics Statement The Verge is a vox media network Advertise with us Jobs @ Vox Media © 2023 Vox Media , LLC. All Rights Reserved "

"A watermark for chatbots can spot text written by an AI | MIT Technology Review"

"https://www.technologyreview.com/2023/01/27/1067338/a-watermark-for-chatbots-can-spot-text-written-by-an-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts A watermark for chatbots can expose text written by an AI The tool could let teachers spot plagiarism or help social media platforms fight disinformation bots. By Melissa Heikkilä archive page Getty Images Hidden patterns purposely buried in AI-generated texts could help identify them as such, allowing us to tell whether the words we’re reading are written by a human or not. These “watermarks” are invisible to the human eye but let computers detect that the text probably comes from an AI system. If embedded in large language models, they could help prevent some of the problems that these models have already caused. For example, since OpenAI’s chatbot ChatGPT was launched in November, students have already started cheating by using it to write essays for them. News website CNET has used ChatGPT to write articles, only to have to issue corrections amid accusations of plagiarism. Building the watermarking approach into such systems before they’re released could help address such problems. In studies, these watermarks have already been used to identify AI-generated text with near certainty. Researchers at the University of Maryland, for example, were able to spot text created by Meta’s open-source language model, OPT-6.7B, using a detection algorithm they built. The work is described in a paper that’s yet to be peer-reviewed, and the code will be available for free around February 15. AI language models work by predicting and generating one word at a time. After each word, the watermarking algorithm randomly divides the language model’s vocabulary into words on a “greenlist” and a “redlist” and then prompts the model to choose words on the greenlist. The more greenlisted words in a passage, the more likely it is that the text was generated by a machine. Text written by a person tends to contain a more random mix of words. For example, for the word “beautiful,” the watermarking algorithm could classify the word “flower” as green and “orchid” as red. The AI model with the watermarking algorithm would be more likely to use the word “flower” than “orchid,” explains Tom Goldstein, an assistant professor at the University of Maryland, who was involved in the research. Related Story The internet is increasingly awash with text written by AI software. We need new tools to detect it. ChatGPT is one of a new breed of large language models that generate text so fluent it could be mistaken for human writing. These AI models regurgitate facts confidently but are notorious for spewing falsehoods and biases. To the untrained eye, it can be almost impossible to distinguish a passage written by an AI model from one written by a human. The breathtaking speed of AI development means that new, more powerful models quickly make our existing tool kit for detecting synthetic text less effective. It’s a constant race between AI developers to build new safety tools that can match the latest generation of AI models. “Right now, it’s the Wild West,” says John Kirchenbauer, a researcher at the University of Maryland, who was involved in the watermarking work. He hopes watermarking tools might give AI-detection efforts the edge. The tool his team has developed could be adjusted to work with any AI language model that predicts the next word, he says. The findings are both promising and timely, says Irene Solaiman, policy director at AI startup Hugging Face, who worked on studying AI output detection in her previous role as an AI researcher at OpenAI, but was not involved in this research. “As models are being deployed at scale, more people outside the AI community, likely without computer science training, will need to access detection methods,” says Solaiman. There are limitations to this new method, however. Watermarking only works if it is embedded in the large language model by its creators right from the beginning. Although OpenAI is reputedly working on methods to detect AI-generated text, including watermarks, the research remains highly secretive. The company doesn’t tend to give external parties much information about how ChatGPT works or was trained, much less access to tinker with it. OpenAI didn’t immediately respond to our request for comment. It’s also unclear how the new work will apply to other models besides Meta’s, such as ChatGPT, Solaiman says. The AI model the watermark was tested on is also smaller than popular models like ChatGPT. More testing is needed to explore different ways someone might try to fight back against watermarking methods, but the researchers say that attackers’ options are limited. “You’d have to change about half the words in a passage of text before the watermark could be removed,” says Goldstein. “It’s dangerous to underestimate high schoolers, so I won’t do that,” Solaiman says. “But generally the average person will likely be unable to tamper with this kind of watermark.” hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"New AI classifier for indicating AI-written text"

"https://openai.com/blog/new-ai-classifier-for-indicating-ai-written-text"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Blog New AI classifier for indicating AI-written text We’re launching a classifier trained to distinguish between AI-written and human-written text. Illustration: Ruby Chen January 31, 2023 Authors Jan Hendrik Kirchner Lama Ahmad Scott Aaronson Jan Leike Product , Announcements As of July 20, 2023, the AI classifier is no longer available due to its low rate of accuracy. We are working to incorporate feedback and are currently researching more effective provenance techniques for text, and have made a commitment to develop and deploy mechanisms that enable users to understand if audio or visual content is AI-generated. We’ve trained a classifier to distinguish between text written by a human and text written by AIs from a variety of providers. While it is impossible to reliably detect all AI-written text, we believe good classifiers can inform mitigations for false claims that AI-generated text was written by a human: for example, running automated misinformation campaigns , using AI tools for academic dishonesty, and positioning an AI chatbot as a human. Our classifier is not fully reliable. In our evaluations on a “challenge set” of English texts, our classifier correctly identifies 26% of AI-written text (true positives) as “likely AI-written,” while incorrectly labeling human-written text as AI-written 9% of the time (false positives). Our classifier’s reliability typically improves as the length of the input text increases. Compared to our previously released classifier , this new classifier is significantly more reliable on text from more recent AI systems. We’re making this classifier publicly available to get feedback on whether imperfect tools like this one are useful. Our work on the detection of AI-generated text will continue, and we hope to share improved methods in the future. Try our free work-in-progress classifier yourself: Try the classifier Limitations Our classifier has a number of important limitations. It should not be used as a primary decision-making tool , but instead as a complement to other methods of determining the source of a piece of text. The classifier is very unreliable on short texts (below 1,000 characters). Even longer texts are sometimes incorrectly labeled by the classifier. Sometimes human-written text will be incorrectly but confidently labeled as AI-written by our classifier. We recommend using the classifier only for English text. It performs significantly worse in other languages and it is unreliable on code. Text that is very predictable cannot be reliably identified. For example, it is impossible to predict whether a list of the first 1,000 prime numbers was written by AI or humans, because the correct answer is always the same. AI-written text can be edited to evade the classifier. Classifiers like ours can be updated and retrained based on successful attacks, but it is unclear whether detection has an advantage in the long-term. Classifiers based on neural networks are known to be poorly calibrated outside of their training data. For inputs that are very different from text in our training set, the classifier is sometimes extremely confident in a wrong prediction. Training the classifier Our classifier is a language model fine-tuned on a dataset of pairs of human-written text and AI-written text on the same topic. We collected this dataset from a variety of sources that we believe to be written by humans, such as the pretraining data and human demonstrations on prompts submitted to InstructGPT. We divided each text into a prompt and a response. On these prompts we generated responses from a variety of different language models trained by us and other organizations. For our web app, we adjust the confidence threshold to keep the false positive rate low; in other words, we only mark text as likely AI-written if the classifier is very confident. Impact on educators and call for input We recognize that identifying AI-written text has been an important point of discussion among educators, and equally important is recognizing the limits and impacts of AI generated text classifiers in the classroom. We have developed a preliminary resource on the use of ChatGPT for educators, which outlines some of the uses and associated limitations and considerations. While this resource is focused on educators, we expect our classifier and associated classifier tools to have an impact on journalists, mis/dis-information researchers, and other groups. We are engaging with educators in the United States to learn what they are seeing in their classrooms and to discuss ChatGPT’s capabilities and limitations, and we will continue to broaden our outreach as we learn. These are important conversations to have as part of our mission is to deploy large language models safely, in direct contact with affected communities. If you’re directly impacted by these issues (including but not limited to teachers, administrators, parents, students, and education service providers), please provide us with feedback using this form. Direct feedback on the preliminary resource is helpful, and we also welcome any resources that educators are developing or have found helpful (e.g., course guidelines, honor code and policy updates, interactive tools, AI literacy programs). Authors Jan Hendrik Kirchner View all articles Lama Ahmad View all articles Scott Aaronson View all articles Jan Leike View all articles Acknowledgments Contributors Michael Lampe, Joanne Jang, Pamela Mishkin, Andrew Mayne, Henrique Ponde de Oliveira Pinto, Valerie Balcom, Michelle Pokrass, Jeff Belgum, Madelaine Boyd, Heather Schmidt, Sherwin Wu, Logan Kilpatrick, Thomas Degry Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Why detecting AI-generated text is so difficult (and what to do about it) | MIT Technology Review"

"https://www.technologyreview.com/2023/02/07/1067928/why-detecting-ai-generated-text-is-so-difficult-and-what-to-do-about-it"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Why detecting AI-generated text is so difficult (and what to do about it) Plus: AI models generate copyrighted images and photos of real people. By Melissa Heikkilä archive page Stephanie Arnett/MITTR This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week, OpenAI unveiled a tool that can detect text produced by its AI system ChatGPT. But if you’re a teacher who fears the coming deluge of ChatGPT-generated essays, don’t get the party poppers out yet. This tool is OpenAI’s response to the heat it’s gotten from educators, journalists, and others for launching ChatGPT without any ways to detect text it has generated. However, it is still very much a work in progress, and it is woefully unreliable. OpenAI says its AI text detector correctly identifies 26% of AI-written text as “likely AI-written.” While OpenAI clearly has a lot more work to do to refine its tool , there’s a limit to just how good it can make it. We’re extremely unlikely to ever get a tool that can spot AI-generated text with 100% certainty. It’s really hard to detect AI-generated text because the whole point of AI language models is to generate fluent and human-seeming text, and the model is mimicking text created by humans, says Muhammad Abdul-Mageed, a professor who oversees research in natural-language processing and machine learning at the University of British Columbia We are in an arms race to build detection methods that can match the latest, most powerful models, Abdul-Mageed adds. New AI language models are more powerful and better at generating even more fluent language, which quickly makes our existing detection tool kit outdated. OpenAI built its detector by creating a whole new AI language model akin to ChatGPT that is specifically trained to detect outputs from models like itself. Although details are sparse, the company apparently trained the model with examples of AI-generated text and examples of human-generated text, and then asked it to spot the AI-generated text. We asked for more information, but OpenAI did not respond. Last month, I wrote about another method for detecting text generated by an AI: watermarks. These act as a sort of secret signal in AI-produced text that allows computer programs to detect it as such. Researchers at the University of Maryland have developed a neat way of applying watermarks to text generated by AI language models, and they have made it freely available. These watermarks would allow us to tell with almost complete certainty when AI-generated text has been used. The trouble is that this method requires AI companies to embed watermarking in their chatbots right from the start. OpenAI is developing these systems but has yet to roll them out in any of its products. Why the delay? One reason might be that it’s not always desirable to have AI-generated text watermarked. One of the most promising ways ChatGPT could be integrated into products is as a tool to help people write emails or as an enhanced spell-checker in a word processor. That’s not exactly cheating. But watermarking all AI-generated text would automatically flag these outputs and could lead to wrongful accusations. The AI text detector that OpenAI rolled out is only one tool among many , and in the future we will likely have to use a combination of them to identify AI-generated text. Another new tool, called GPTZero , measures how random text passages are. AI-generated text uses more of the same words, while people write with more variation. As with diagnoses from doctors, says Abdul-Mageed, when using AI detection tools it’s a good idea to get a second or even a third opinion. One of the biggest changes ushered in by ChatGPT might be the shift in how we evaluate written text. In the future, maybe students won’t write everything from scratch anymore, and the focus will be on coming up with original thoughts, says Sebastian Raschka, an AI researcher who works at AI startup Lightning.AI. Essays and texts generated by ChatGPT will eventually start resembling each other as the AI system runs out of ideas, because it is constrained by its programming and the data in its training set. “It will be easier to write correctly, but it won’t be easier to write originally,” Raschka says. New report: Generative AI in industrial design and engineering Generative AI—the hottest technology this year—is transforming entire sectors, from journalism and drug design to industrial design and engineering. It’ll be more important than ever for leaders in those industries to stay ahead. We’ve got you covered. A new research report from MIT Technology Review highlights the opportunities—and potential pitfalls— of this new technology for industrial design and engineering. The report includes two case studies from leading industrial and engineering companies that are already applying generative AI to their work—and a ton of takeaways and best practices from industry leaders. It is available now for $195. Deeper Learning AI models generate copyrighted images and photos of real people Popular image generation models such as Stable Diffusion can be prompted to produce identifiable photos of real people, potentially threatening their privacy, according to new research. The work also shows that these AI systems can be made to regurgitate exact copies of medical images, as well as copyrighted work by artists. Why this matters: The extent to which these AI models memorize and regurgitate images from their databases is at the root of multiple lawsuits between AI companies and artists. This finding could strengthen the artists’ case. Read more from me about this. Leaky AI models: Sadly, in the push to release new models faster, AI developers too often overlook privacy. And it’s not just image-generating systems. AI language models are also extremely leaky, as I found out when I asked GPT-3, ChatGPT’s predecessor, what it knew about me and MIT Technology Review’s editor in chief. The results were hilarious and creepy. Bits and Bytes When my dad was sick, I started Googling grief. Then I couldn’t escape it. A beautiful piece by my colleague Tate Ryan-Mosley about grief and death, and the pernicious content recommendation algorithms that follow her around the internet only to offer more content on grief and death. Tate spent months asking experts how we can get more control over rogue algorithms. Their answers aren’t all that satisfying. ( MIT Technology Review ) Google has invested $300 million into an AI startup The tech giant is the latest to hop on the generative-AI bandwagon. It’s poured money into AI startup Anthropic, which is developing language models similar to ChatGPT. The deal gives Google a 10% stake in the company in exchange for the computing power needed to run large AI models. ( The Financial Times ) How ChatGPT kicked off an AI race This is a nice peek behind the scenes at OpenAI and how they decided to launch ChatGPT as a way to gather feedback for the next-generation AI language model, GPT-4. The chatbot’s success has been an “earthshaking surprise” inside OpenAI. ( The New York Times ) If ChatGPT were a cat Meet CatGPT. Frankly, the only AI chatbot that matters to me. hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Deep learning pioneer Geoffrey Hinton quits Google | MIT Technology Review"

"https://www.technologyreview.com/2023/05/01/1072478/deep-learning-pioneer-geoffrey-hinton-quits-google"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Deep learning pioneer Geoffrey Hinton has quit Google Hinton will be speaking at EmTech Digital on Wednesday. By Will Douglas Heaven archive page Linda Nylind / eyevine via Redux Geoffrey Hinton, a VP and engineering fellow at Google and a pioneer of deep learning who developed some of the most important techniques at the heart of modern AI, is leaving the company after 10 years, the New York Times reported today. According to the Times, Hinton says he has new fears about the technology he helped usher in and wants to speak openly about them, and that a part of him now regrets his life’s work. Hinton, who will be speaking live to MIT Technology Review at EmTech Digital on Wednesday in his first post-resignation interview, was a joint recipient with Yann Lecun and Yoshua Bengio of the 2018 Turing Award—computing’s equivalent of the Nobel. “Geoff’s contributions to AI are tremendous,” says Lecun, who is chief AI scientist at Meta. “He hadn’t told me he was planning to leave Google, but I’m not too surprised.” Related Story The 75-year-old computer scientist has divided his time between the University of Toronto and Google since 2013, when the tech giant acquired Hinton’s AI startup DNNresearch. Hinton’s company was a spinout from his research group, which was doing cutting-edge work with machine learning for image recognition at the time. Google used that technology to boost photo search and more. Hinton has long called out ethical questions around AI, especially its co-optation for military purposes. He has said that one reason he chose to spend much of his career in Canada is that it is easier to get research funding that does not have ties to the US Department of Defense. “Geoff has made foundational breakthroughs in AI, and we appreciate his decade of contributions at Google,” says Google chief scientist Jeff Dean. “I’ve deeply enjoyed our many conversations over the years. I’ll miss him, and I wish him well.” Dean says: “As one of the first companies to publish AI Principles , we remain committed to a responsible approach to AI. We’re continually learning to understand emerging risks while also innovating boldly.” Hinton is best known for an algorithm called backpropagation, which he first proposed with two colleagues in the 1980s. The technique, which allows artificial neural networks to learn, today underpins nearly all machine-learning models. In a nutshell, backpropagation is a way to adjust the connections between artificial neurons over and over until a neural network produces the desired output. Hinton believed that backpropagation mimicked how biological brains learn. He has been looking for even better approximations since, but he has never improved on it. “In my numerous discussions with Geoff, I was always the proponent of backpropagation and he was always looking for another learning procedure, one that he thought would be more biologically plausible and perhaps a better model of how learning works in the brain,” says Lecun. “Geoff Hinton certainly deserves the greatest credit for many of the ideas that have made current deep learning possible,” says Bengio, who is a professor at the University of Montreal and scientific director of the Montreal Institute for Learning Algorithms. “I assume this also makes him feel a particularly strong sense of responsibility in alerting the public about potential risks of the ensuing advances in AI.” MIT Technology Review will have more on Hinton throughout the week. Be sure to tune in to Will Douglas Heaven’s live interview with Hinton at EmTech Digital on Wednesday, May 3, at 13.30 Eastern time. Tickets are available from the event website. hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Yann LeCun’s big bet for building intelligent machines | MIT Technology Review"

"https://www.technologyreview.com/2022/06/24/1054817/yann-lecun-bold-new-vision-future-ai-deep-learning-meta"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Yann LeCun has a bold new vision for the future of AI One of the godfathers of deep learning pulls together old ideas to sketch out a fresh path for AI, but raises as many questions as he answers. By Melissa Heikkilä archive page Will Douglas Heaven archive page Brian Ach/Getty Images Around a year and a half ago, Yann LeCun realized he had it wrong. LeCun, who is chief scientist at Meta’s AI lab and a professor at New York University, is one of the most influential AI researchers in the world. He had been trying to give machines a basic grasp of how the world works—a kind of common sense —by training neural networks to predict what was going to happen next in video clips of everyday events. But guessing future frames of a video pixel by pixel was just too complex. He hit a wall. Now, after months figuring out what was missing, he has a bold new vision for the next generation of AI. In a draft document shared with MIT Technology Review, LeCun sketches out an approach that he thinks will one day give machines the common sense they need to navigate the world. (Update: LeCun has since posted the document online.) For LeCun, the proposals could be the first steps on a path to building machines with the ability to reason and plan like humans—what many call artificial general intelligence , or AGI. He also steps away from today’s hottest trends in machine learning, resurrecting some old ideas that have gone out of fashion. But his vision is far from comprehensive; indeed, it may raise more questions than it answers. The biggest question mark, as LeCun points out himself, is that he does not know how to build what he describes. Related Story A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. The centerpiece of the new approach is a neural network that can learn to view the world at different levels of detail. Ditching the need for pixel-perfect predictions, this network would focus only on those features in a scene that are relevant for the task at hand. LeCun proposes pairing this core network with another, called the configurator, which determines what level of detail is required and tweaks the overall system accordingly. For LeCun, AGI is going to be a part of how we interact with future tech. His vision is colored by that of his employer, Meta, which is pushing a virtual-reality metaverse. He says that in 10 or 15 years people won’t be carrying smartphones in their pockets, but augmented-reality glasses fitted with virtual assistants that will guide humans through their day. “For those to be most useful to us, they basically have to have more or less human-level intelligence,” he says. “Yann has been talking about many of these ideas for some time,” says Yoshua Bengio, an AI researcher at the University of Montreal and scientific director at the Mila-Quebec Institute. “But it is good to see it all together, in one big picture.” Bengio thinks that LeCun asks the right questions. He also thinks it’s great that LeCun is willing to put out a document that has so few answers. It’s a research proposal rather than a set of clean results, he says. “People talk about these things in private, but they’re not usually shared publicly,” says Bengio. “It’s risky.” A matter of common sense LeCun has been thinking about AI for nearly 40 years. In 2018 he was joint winner of computing’s top prize, the Turing Award, with Bengio and Geoffrey Hinton, for his pioneering work on deep learning. “Getting machines to behave like humans and animals has been the quest of my life,” he says. LeCun thinks that animal brains run a kind of simulation of the world, which he calls a world model. Learned in infancy, it’s the way animals (including humans) make good guesses about what’s going on around them. Infants pick up the basics in the first few months of life by observing the world, says LeCun. Seeing a dropped ball fall a handful of times is enough to give a child a sense of how gravity works. “Common sense” is the catch-all term for this kind of intuitive reasoning. It includes a grasp of simple physics: for example, knowing that the world is three-dimensional and that objects don’t actually disappear when they go out of view. It lets us predict where a bouncing ball or a speeding bike will be in a few seconds’ time. And it helps us join the dots between incomplete pieces of information: if we hear a metallic crash from the kitchen, we can make an educated guess that someone has dropped a pan, because we know what kinds of objects make that noise and when they make it. In short, common sense tells us what events are possible and impossible, and which events are more likely than others. It lets us foresee the consequences of our actions and make plans—and ignore irrelevant details. But teaching common sense to machines is hard. Today’s neural networks need to be shown thousands of examples before they start to spot such patterns. In many ways common sense amounts to the ability to predict what’s going to happen next. “This is the essence of intelligence,” says LeCun. That’s why he—and a few other researchers—have been using video clips to train their models. But existing machine-learning techniques required the models to predict exactly what is going to happen in the next frame and generate it pixel by pixel. Imagine you hold up a pen and let it go, LeCun says. Common sense tells you that the pen will fall, but not the exact position it will end up in. Predicting that would require crunching some tough physics equations. That’s why LeCun is now trying to train a neural network that can focus only on the relevant aspects of the world: predicting that the pen will fall but not exactly how. He sees this trained network as the equivalent of the world model that animals rely on. Mystery ingredients LeCun says he has built an early version of this world model that can do basic object recognition. He is now working on training it to make predictions. But how the configurator should work remains a mystery, he says. LeCun imagines that neural network as the controller for the whole system. It would decide what kind of predictions the world model should be making at any given time and what level of detail it should focus on to make those predictions possible, adjusting the world model as required. LeCun is convinced that something like a configurator is needed, but he doesn’t know how to go about training a neural network to do the job. “We need to figure out a good recipe to make this work, and we don’t have that recipe yet,” he says. In LeCun’s vision, the world model and the configurator are two key pieces in a larger system, known as a cognitive architecture, that includes other neural networks—such as a perception model that senses the world and a model that uses rewards to motivate the AI to explore or curb its behavior. Each neural network is roughly analogous to parts of the brain, says LeCun. For example, the configurator and world model are meant to replicate functions of the prefrontal cortex. The motivation model corresponds to certain functions of the amygdala, and so on. The idea of cognitive architectures, especially ones inspired by the brain, has been around for decades. So have many of LeCun’s ideas about prediction using models with different levels of detail. But when deep learning became the dominant approach in AI, many of these older ideas went out of fashion. “People in AI research have kind of forgotten about this a little bit,” he says. What he has done is taken these older ideas and rehabilitated them, suggesting ways that they can be combined with deep learning. For LeCun, revisiting these out-of-fashion ideas is essential, because he believes the two dominant approaches in modern AI are dead ends. When it comes to building general-purpose AI, there are two main camps. In one, many researchers think the remarkable success of very large language or image-making models like OpenAI's GPT-3 and DALL-E show that all we need to do is just build bigger and bigger models. In the other camp are champions of reinforcement learning, the AI technique that rewards specific behaviors to make neural networks to learn by trial and error. This is the approach DeepMind used to train its game-playing AIs like AlphaZero. Get the rewards right, the argument goes, and reinforcement learning will eventually produce more general intelligence. Related Story Open AI's language AI wowed the public with its apparent mastery of English – but is it all an illusion? LeCun is having none of it: “This idea that we're going to just scale up the current large language models and eventually human-level AI will emerge—I don’t believe this at all, not for one second.” These large models just manipulate words and images, he says. They have no direct experience of the world. He is equally skeptical about reinforcement learning, because it requires vast amounts of data to train models to do even simple tasks. “I think that has no chance of working at all,” says LeCun. David Silver at DeepMind, who led the work on AlphaZero and is a big advocate of reinforcement learning, disagrees with this assessment but welcomes LeCun’s overall vision. “It’s an exciting new proposal for how a world model could be represented and learned,” he says. Melanie Mitchell, an AI researcher at the Santa Fe Institute, is also excited to see a whole new approach. “We really haven’t seen this coming out of the deep-learning community so much,” she says. She also agrees with LeCun that large language models cannot be the whole story. “They lack memory and internal models of the world that are actually really important,” she says. Natasha Jaques, a researcher at Google Brain, thinks that language models should still play a role, however. It’s odd for language to be entirely missing from LeCun’s proposals, she says: “We know that large language models are super effective and bake in a bunch of human knowledge.” Jaques, who works on ways to get AIs to share information and abilities with each other, points out that humans don’t have to have direct experience of something to learn about it. We can change our behavior simply by being told something, such as not to touch a hot pan. “How do I update this world model that Yann is proposing if I don’t have language?” she asks. There’s another issue, too. If they were to work, LeCun’s ideas would create a powerful technology that could be as transformative as the internet. And yet his proposal doesn’t discuss how his model’s behavior and motivations would be controlled, or who would control them. This is a weird omission, says Abhishek Gupta, the founder of the Montreal AI Ethics Institute and a responsible-AI expert at Boston Consulting Group. “We should think more about what it takes for AI to function well in a society, and that requires thinking about ethical behavior, amongst other things,” says Gupta. Yet Jaques notes that LeCun’s proposals are still very much ideas rather than practical applications. Mitchell says the same: “There’s certainly little risk of this becoming a human-level intelligence anytime soon.” LeCun would agree. His aim is to sow the seeds of a new approach in the hope that others build on it. “This is something that is going to take a lot of effort from a lot of people,” he says. “I’m putting this out there because I think ultimately this is the way to go.” If nothing else, he wants to convince people that large language models and reinforcement learning are not the only ways forward. “I hate to see people wasting their time,” he says. hide by Melissa Heikkilä & Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"How to create, release and share generative AI responsibly | MIT Technology Review"

"https://www.technologyreview.com/2023/02/27/1069166/how-to-create-release-and-share-generative-ai-responsibly"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts How to create, release, and share generative AI responsibly Companies including OpenAI and TikTok have signed up to a new set of guidelines designed to help them be more transparent around generative AI. By Melissa Heikkilä archive page Stephanie Arnett/MITTR | Getty, Envato A group of 10 companies, including OpenAI, TikTok, Adobe, the BBC, and the dating app Bumble, have signed up to a new set of guidelines on how to build, create, and share AI-generated content responsibly. The recommendations call for both the builders of the technology, such as OpenAI, and creators and distributors of digitally created synthetic media, such as the BBC and TikTok, to be more transparent about what the technology can and cannot do, and disclose when people might be interacting with this type of content. The voluntary recommendations were put together by the Partnership on AI (PAI), an AI research nonprofit, in consultation with over 50 organizations. PAI’s partners include big tech companies as well as academic, civil society, and media organizations. The first 10 companies to commit to the guidance are Adobe, BBC, CBC/Radio-Canada, Bumble, OpenAI, TikTok, Witness, and synthetic-media startups Synthesia, D-ID, and Respeecher. “We want to ensure that synthetic media is not used to harm, disempower, or disenfranchise but rather to support creativity, knowledge sharing, and commentary,” says Claire Leibowicz, PAI’s head of AI and media integrity. One of the most important elements of the guidelines is a pact by the companies to include and research ways to tell users when they’re interacting with something that’s been generated by AI. This might include watermarks or disclaimers, or traceable elements in an AI model’s training data or metadata. Regulation attempting to rein in potential harms relating to generative AI is still lagging behind. The European Union, for example, is trying to include generative AI in its upcoming AI law, the AI Act , which could include elements such as disclosing when people are interacting with deepfakes and obligating companies to meet certain transparency requirements. Related Story The European Union is planning new legislation aimed at curbing the worst harms associated with artificial intelligence. While generative AI is a Wild West right now, says Henry Ajder, an expert on generative AI who contributed to the guidelines, he hopes they will offer companies key things they need to look out for as they incorporate the technology into their businesses. Raising awareness and starting a conversation around responsible ways to think about synthetic media is important, says Hany Farid, a professor at the University of California, Berkeley, who researches synthetic media and deepfakes. But “voluntary guidelines and principles rarely work,” he adds. While companies such as OpenAI can try to put guardrails on technologies they create, like ChatGPT and DALL-E, other players that are not part of the pact—such as Stability.AI, the startup that created the open source image-generating AI model Stable Diffusion —can let people generate inappropriate images and deepfakes. “If we really want to address these issues, we’ve got to get serious,” says Farid. For example, he wants cloud service providers and app stores such as those operated by Amazon, Microsoft, Google, and Apple, which are all part of the PAI, to ban services that allow people to use deepfake technology with the intent to create nonconsensual sexual imagery. Watermarks on all AI-generated content should also be mandated, not voluntary, he says. Another important thing missing is how the AI systems themselves could be made more responsible, says Ilke Demir, a senior research scientist at Intel who leads the company’s work on the responsible development of generative AI. This could include more details on how the AI model was trained, what data went into it, and whether generative AI models have any biases. The guidelines have no mention of ensuring that there’s no toxic content in the data set of generative AI models. “It’s one of the most significant ways harm is caused by these systems,” says Daniel Leufer, a senior policy analyst at the digital rights group Access Now. The guidelines include a list of harms that these companies want to prevent, such as fraud, harassment, and disinformation. But a generative AI model that always creates white people is also doing harm, and that is not currently listed, adds Demir. Farid raises a more fundamental issue. Since the companies acknowledge that the technology could lead to some serious harms and offer ways to mitigate them, “why aren't they asking the question ‘Should we do this in the first place?’” hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Why you shouldn’t trust AI search engines | MIT Technology Review"

"https://www.technologyreview.com/2023/02/14/1068498/why-you-shouldnt-trust-ai-search-engines"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Why you shouldn’t trust AI search engines Plus: The original startup behind Stable Diffusion has launched a generative AI for video. By Melissa Heikkilä archive page Stephanie Arnett/MITTR | Envato This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week was the week chatbot-powered search engines were supposed to arrive. The big idea is that these AI bots would upend our experience of searching the web by generating chatty answers to our questions, instead of just returning lists of links as searches do now. Only … things really did not go according to plan. Approximately two seconds after Microsoft let people poke around with its new ChatGPT-powered Bing search engine, people started finding that it responded to some questions with incorrect or nonsensical answers, such as conspiracy theories. Google had an embarrassing moment when scientists spotted a factual error in the company’s own advertisement for its chatbot Bard, which subsequently wiped $100 billion off its share price. What makes all of this all the more shocking is that it came as a surprise to precisely no one who has been paying attention to AI language models. Here’s the problem: the technology is simply not ready to be used like this at this scale. AI language models are notorious bullshitters , often presenting falsehoods as facts. They are excellent at predicting the next word in a sentence, but they have no knowledge of what the sentence actually means. That makes it incredibly dangerous to combine them with search, where it’s crucial to get the facts straight. OpenAI, the creator of the hit AI chatbot ChatGPT, has always emphasized that it is still just a research project, and that it is constantly improving as it receives people’s feedback. That hasn’t stopped Microsoft from integrating it into a new version of Bing, albeit with caveats that the search results might not be reliable. Google has been using natural-language processing for years to help people search the internet using whole sentences instead of keywords. However, until now the company has been reluctant to integrate its own AI chatbot technology into its signature search engine, says Chirag Shah, a professor at the University of Washington who specializes in online search. Google’s leadership has been worried about the “reputational risk” of rushing out a ChatGPT-like tool. The irony! The recent blunders from Big Tech don’t mean that AI-powered search is a lost cause. One way Google and Microsoft have tried to make their AI-generated search summaries more accurate is by offering citations. Linking to sources allows users to better understand where the search engine is getting its information, says Margaret Mitchell, a researcher and ethicist at the AI startup Hugging Face, who used to co-lead Google’s AI ethics team. This might even help give people a more diverse take on things, she says, by nudging them to consider more sources than they might have done otherwise. But that does nothing to address the fundamental problem that these AI models make up information and confidently present falsehoods as fact. And when AI-generated text looks authoritative and cites sources, that could ironically make users even less likely to double-check the information they’re seeing. “A lot of people don’t check citations. Having a citation gives something an air of correctness that might not actually be there,” Mitchell says. But the accuracy of search results is not really the point for Big Tech , says Shah. Though Google invented the technology that is fueling the current AI hype, the acclaim and attention are fixed firmly on the buzzy startup OpenAI and its patron, Microsoft. “It is definitely embarrassing for Google. They’re in a defensive position now. They haven’t been in this position for a very long time,” says Shah. Meanwhile, Microsoft has gambled that expectations around Bing are so low a few errors won’t really matter. Microsoft has less than 10% of the market share for online search. Winning just a couple more percentage points would be a huge win for them, Shah says. There’s an even bigger game beyond AI-powered search , adds Shah. Search is just one of the areas where the two tech giants are battling each other. They also compete in cloud computing services, productivity software, and enterprise software. Conversational AI becomes a way to demonstrate cutting-edge tech that translates to these other areas of the business. Shah reckons companies are going to spin early hiccups as learning opportunities. “Rather than taking a careful approach to this, they’re going in a very bold fashion. Let the [AI system] make mistakes, because now the cat is out of the bag,” he says. Essentially, we—the users—are now doing the work of testing this technology for free. “We’re all guinea pigs at this point,” says Shah. Deeper Learning The original startup behind Stable Diffusion has launched a generative AI for video Runway, the generative AI startup that co-created last year’s breakout text-to-image model Stable Diffusion, has released an AI model that can transform existing videos into new ones by applying any style specified by a text prompt or reference image. If 2022 saw a boom in AI-generated images, the people behind Runway think 2023 will be the year of AI-generated video. Read more from Will Douglas Heaven here. Why this matters: Unlike Meta’s and Google’s text-to-video systems, Runway’s model was built with customers in mind. “This is one of the first models to be developed really closely with a community of video makers,” says Runway CEO and cofounder Cristóbal Valenzuela. “It comes with years of insight about how filmmakers and VFX editors actually work on post-production.” Valenzuela thinks his model brings us a step closer to having full feature films generated with an AI system. Bits and Bytes ChatGPT is everywhere. Here’s where it came from ChatGPT has become the fastest-growing internet service ever, reaching 100 million users just two months after its launch in December. But OpenAI’s breakout hit did not come out of nowhere. Will Douglas Heaven explains how we got here. ( MIT Technology Review ) How AI algorithms objectify women’s bodies A new investigation shows how AI tools rate photos of women as more sexually suggestive than similar images of men. This is an important story about how AI algorithms reflect the (often male) gaze of their creators. ( The Guardian ) How Moscow’s smart-city project became an AI surveillance dystopia Cities around the world are embracing technologies that purport to help with security or mobility. But this cautionary tale from Moscow shows just how easy it is to transform these technologies into tools for political repression. ( Wired ) ChatGPT is a blurry JPEG of the internet I like this analogy. ChatGPT is essentially a low-resolution snapshot of the internet, and that’s why it often spews nonsense. ( The New Yorker ) Correction: The newsletter version of this story incorrectly stated Google lost $100 million off its share price. It was in fact $100 billion. We apologize for the error. hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Generative AI is changing everything. But what's left when the hype is gone? | MIT Technology Review"

"https://www.technologyreview.com/2022/12/16/1065005/generative-ai-revolution-art"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Generative AI is changing everything. But what’s left when the hype is gone? No one knew how popular OpenAI’s DALL-E would be in 2022, and no one knows where its rise will leave us. By Will Douglas Heaven archive page Digital artist Erik Carter used the text-to image AI tool DALL-E 2 to create this unsettling image. Erik Carter Generative AI is one of MIT Technology Review’s 10 Breakthrough Technologies of 2023. Explore the rest of the list here. It was clear that OpenAI was on to something. In late 2021, a small team of researchers was playing around with an idea at the company’s San Francisco office. They’d built a new version of OpenAI’s text-to-image model, DALL-E, an AI that converts short written descriptions into pictures: a fox painted by Van Gogh, perhaps, or a corgi made of pizza. Now they just had to figure out what to do with it. “Almost always, we build something and then we all have to use it for a while,” Sam Altman, OpenAI’s cofounder and CEO, tells MIT Technology Review. “We try to figure out what it’s going to be, what it’s going to be used for.” Not this time. As they tinkered with the model, everyone involved realized this was something special. “It was very clear that this was it—this was the product,” says Altman. “There was no debate. We never even had a meeting about it.” But nobody—not Altman, not the DALL-E team—could have predicted just how big a splash this product was going to make. “This is the first AI technology that has caught fire with regular people,” says Altman. DALL-E 2 dropped in April 2022. In May, Google announced (but did not release) two text-to-image models of its own, Imagen and Parti. Then came Midjourney, a text-to-image model made for artists. And August brought Stable Diffusion, an open-source model that the UK-based startup Stability AI has released to the public for free. The doors were off their hinges. OpenAI signed up a million users in just 2.5 months. More than a million people started using Stable Diffusion via its paid-for service Dream Studio in less than half that time; many more used Stable Diffusion through third-party apps or installed the free version on their own computers. (Emad Mostaque, Stability AI’s founder, says he’s aiming for a billion users.) And then in October we had Round Two: a spate of text-to- video models from Google, Meta, and others. Instead of just generating still images, these can create short video clips, animations, and 3D pictures. The pace of development has been breathtaking. In just a few months, the technology has inspired hundreds of newspaper headlines and magazine covers, filled social media with memes, kicked a hype machine into overdrive—and set off an intense backlash. “The shock and awe of this technology is amazing—and it’s fun, it’s what new technology should be,” says Mike Cook, an AI researcher at King’s College London who studies computational creativity. “But it’s moved so fast that your initial impressions are being updated before you even get used to the idea. I think we’re going to spend a while digesting it as a society.” Artists are caught in the middle of one of the biggest upheavals in a generation. Some will lose work; some will find new opportunities. A few are headed to the courts to fight legal battles over what they view as the misappropriation of images to train models that could replace them. Creators were caught off guard, says Don Allen Stevenson III, a digital artist based in California who has worked at visual-effects studios such as DreamWorks. “For technically trained folks like myself, it’s very scary. You’re like, ‘Oh my god—that’s my whole job,’” he says. “I went into an existential crisis for the first month of using DALL-E.” But while some are still reeling from the shock, many—including Stevenson—are finding ways to work with these tools and anticipate what comes next. The exciting truth is, we don’t really know. For while creative industries—from entertainment media to fashion, architecture, marketing, and more—will feel the impact first, this tech will give creative superpowers to everybody. In the longer term, it could be used to generate designs for almost anything, from new types of drugs to clothes and buildings. The generative revolution has begun. A magical revolution For Chad Nelson, a digital creator who has worked on video games and TV shows, text-to-image models are a once-in-a-lifetime breakthrough. “This tech takes you from that lightbulb in your head to a first sketch in seconds,” he says. “The speed at which you can create and explore is revolutionary—beyond anything I’ve experienced in 30 years.” Generative AI is changing the way work gets done in many industries. Learn how in our new series of business reports. Within weeks of their debut, people were using these tools to prototype and brainstorm everything from magazine illustrations and marketing layouts to video-game environments and movie concepts. People generated fan art, even whole comic books, and shared them online in the thousands. Altman even used DALL-E to generate designs for sneakers that someone then made for him after he tweeted the image. Amy Smith, a computer scientist at Queen Mary University of London and a tattoo artist, has been using DALL-E to design tattoos. “You can sit down with the client and generate designs together,” she says. “We’re in a revolution of media generation.” Related Story The new version of the company's large language model makes stuff up—but can also admit when it's wrong. Paul Trillo, a digital and video artist based in California, thinks the technology will make it easier and faster to brainstorm ideas for visual effects. “People are saying this is the death of effects artists, or the death of fashion designers,” he says. “I don’t think it’s the death of anything. I think it means we don’t have to work nights and weekends.” Stock image companies are taking different positions. Getty has banned AI-generated images. Shutterstock has signed a deal with OpenAI to embed DALL-E in its website and says it will start a fund to reimburse artists whose work has been used to train the models. Stevenson says he has tried out DALL-E at every step of the process that an animation studio uses to produce a film, including designing characters and environments. With DALL-E, he was able to do the work of multiple departments in a few minutes. “It’s uplifting for all the folks who’ve never been able to create because it was too expensive or too technical,” he says. “But it’s terrifying if you’re not open to change.” Nelson thinks there’s still more to come. Eventually, he sees this technology being embraced not only by media giants but also by architecture and design firms. It’s not ready yet, though, he says. “Right now it’s like you have a little magic box, a little wizard,” he says. That’s great if you just want to keep generating images, but not if you need a creative partner. “If I want it to create stories and build worlds, it needs far more awareness of what I’m creating,” he says. That’s the problem: these models still have no idea what they’re doing. Inside the black box To see why, let’s look at how these programs work. From the outside, the software is a black box. You type in a short description—a prompt—and then wait a few seconds. What you get back is a handful of images that fit that prompt (more or less). You may have to tweak your text to coax the model to produce something closer to what you had in mind, or to hone a serendipitous result. This has become known as prompt engineering. Prompts for the most detailed, stylized images can run to several hundred words, and wrangling the right words has become a valuable skill. Online marketplaces have sprung up where prompts known to produce desirable results are bought and sold. Prompts can contain phrases that instruct the model to go for a particular style: “trending on ArtStation” tells the AI to mimic the (typically very detailed) style of images popular on ArtStation, a website where thousands of artists showcase their work; “Unreal engine” invokes the familiar graphic style of certain video games; and so on. Users can even enter the names of specific artists and have the AI produce pastiches of their work, which has made some artists very unhappy. "I tried to metaphorically represent AI with the prompt 'the Big Bang' and ended up with these abstract bubble-like forms (right). It wasn't exactly what I wanted, so then I went more literal with 'explosion in outer space 1980s photograph' (left), which seemed too aggressive. I also tried growing some digital plants by putting in 'plant 8-bit pixel art' (center)." Under the hood, text-to-image models have two key components: one neural network trained to pair an image with text that describes that image, and another trained to generate images from scratch. The basic idea is to get the second neural network to generate an image that the first neural network accepts as a match for the prompt. The big breakthrough behind the new models is in the way images get generated. The first version of DALL-E used an extension of the technology behind OpenAI’s language model GPT-3 , producing images by predicting the next pixel in an image as if they were words in a sentence. This worked, but not well. “It was not a magical experience,” says Altman. “It’s amazing that it worked at all.” Instead, DALL-E 2 uses something called a diffusion model. Diffusion models are neural networks trained to clean images up by removing pixelated noise that the training process adds. The process involves taking images and changing a few pixels in them at a time, over many steps, until the original images are erased and you’re left with nothing but random pixels. “If you do this a thousand times, eventually the image looks like you have plucked the antenna cable from your TV set—it’s just snow,” says Björn Ommer, who works on generative AI at the University of Munich in Germany and who helped build the diffusion model that now powers Stable Diffusion. The neural network is then trained to reverse that process and predict what the less pixelated version of a given image would look like. The upshot is that if you give a diffusion model a mess of pixels, it will try to generate something a little cleaner. Plug the cleaned-up image back in, and the model will produce something cleaner still. Do this enough times and the model can take you all the way from TV snow to a high-resolution picture. AI art generators never work exactly how you want them to. They often produce hideous results that can resemble distorted stock art, at best. In my experience, the only way to really make the work look good is to add descriptor at the end with a style that looks aesthetically pleasing. The trick with text-to-image models is that this process is guided by the language model that’s trying to match a prompt to the images the diffusion model is producing. This pushes the diffusion model toward images that the language model considers a good match. But the models aren’t pulling the links between text and images out of thin air. Most text-to-image models today are trained on a large data set called LAION, which contains billions of pairings of text and images scraped from the internet. This means that the images you get from a text-to-image model are a distillation of the world as it’s represented online, distorted by prejudice (and pornography). One last thing: there’s a small but crucial difference between the two most popular models, DALL-E 2 and Stable Diffusion. DALL-E 2’s diffusion model works on full-size images. Stable Diffusion, on the other hand, uses a technique called latent diffusion, invented by Ommer and his colleagues. It works on compressed versions of images encoded within the neural network in what’s known as a latent space, where only the essential features of an image are retained. This means Stable Diffusion requires less computing muscle to work. Unlike DALL-E 2, which runs on OpenAI’s powerful servers, Stable Diffusion can run on (good) personal computers. Much of the explosion of creativity and the rapid development of new apps is due to the fact that Stable Diffusion is both open source—programmers are free to change it, build on it, and make money from it—and lightweight enough for people to run at home. Redefining creativity For some, these models are a step toward artificial general intelligence , or AGI—an over-hyped buzzword referring to a future AI that has general-purpose or even human-like abilities. OpenAI has been explicit about its goal of achieving AGI. For that reason, Altman doesn’t care that DALL-E 2 now competes with a raft of similar tools, some of them free. “We’re here to make AGI, not image generators,” he says. “It will fit into a broader product road map. It’s one smallish element of what an AGI will do.” That’s optimistic, to say the least—many experts believe that today’s AI will never reach that level. In terms of basic intelligence, text-to-image models are no smarter than the language-generating AIs that underpin them. Tools like GPT-3 and Google’s PaLM regurgitate patterns of text ingested from the many billions of documents they are trained on. Similarly, DALL-E and Stable Diffusion reproduce associations between text and images found across billions of examples online. The results are dazzling, but poke too hard and the illusion shatters. These models make basic howlers—responding to “salmon in a river” with a picture of chopped-up fillets floating downstream, or to “a bat flying over a baseball stadium” with a picture of both a flying mammal and a wooden stick. That’s because they are built on top of a technology that is nowhere close to understanding the world as humans (or even most animals) do. Even so, it may be just a matter of time before these models learn better tricks. “People say it’s not very good at this thing now, and of course it isn’t,” says Cook. “But a hundred million dollars later, it could well be.” That’s certainly OpenAI’s approach. “We already know how to make it 10 times better,” says Altman. “We know there are logical reasoning tasks that it messes up. We’re going to go down a list of things, and we’ll put out a new version that fixes all of the current problems.” Related Story My avatars were cartoonishly pornified, while my male colleagues got to be astronauts, explorers, and inventors. If claims about intelligence and understanding are overblown, what about creativity? Among humans, we say that artists, mathematicians, entrepreneurs, kindergarten kids, and their teachers are all exemplars of creativity. But getting at what these people have in common is hard. For some, it’s the results that matter most. Others argue that the way things are made—and whether there is intent in that process—is paramount. Still, many fall back on a definition given by Margaret Boden, an influential AI researcher and philosopher at the University of Sussex, UK, who boils the concept down to three key criteria: to be creative, an idea or an artifact needs to be new, surprising, and valuable. Beyond that, it’s often a case of knowing it when you see it. Researchers in the field known as computational creativity describe their work as using computers to produce results that would be considered creative if produced by humans alone. Smith is therefore happy to call this new breed of generative models creative, despite their stupidity. “It is very clear that there is innovation in these images that is not controlled by any human input,” she says. “The translation from text to image is often surprising and beautiful.” Maria Teresa Llano, who studies computational creativity at Monash University in Melbourne, Australia, agrees that text-to-image models are stretching previous definitions. But Llano does not think they are creative. When you use these programs a lot, the results can start to become repetitive, she says. This means they fall short of some or all of Boden’s requirements. And that could be a fundamental limitation of the technology. By design, a text-to-image model churns out new images in the likeness of billions of images that already exist. Perhaps machine learning will only ever produce images that imitate what it’s been exposed to in the past. That may not matter for computer graphics. Adobe is already building text-to-image generation into Photoshop; Blender, Photoshop’s open-source cousin, has a Stable Diffusion plug-in. And OpenAI is collaborating with Microsoft on a text-to-image widget for Office. It is in this kind of interaction, in future versions of these familiar tools, that the real impact may be felt: from machines that don’t replace human creativity but enhance it. “The creativity we see today comes from the use of the systems, rather than from the systems themselves,” says Llano—from the back-and-forth, call-and-response required to produce the result you want. This view is echoed by other researchers in computational creativity. It’s not just about what these machines do; it’s how they do it. Turning them into true creative partners means pushing them to be more autonomous, giving them creative responsibility, getting them to curate as well as create. Aspects of that will come soon. Someone has already written a program called CLIP Interrogator that analyzes an image and comes up with a prompt to generate more images like it. Others are using machine learning to augment simple prompts with phrases designed to give the image extra quality and fidelity—effectively automating prompt engineering, a task that has only existed for a handful of months. Related Story Three things the groundbreaking generative model taught OpenAI’s CEO. Meanwhile, as the flood of images continues, we’re laying down other foundations too. “The internet is now forever contaminated with images made by AI,” says Cook. “The images that we made in 2022 will be a part of any model that is made from now on.” We will have to wait to see exactly what lasting impact these tools will have on creative industries, and on the entire field of AI. Generative AI has become one more tool for expression. Altman says he now uses generated images in personal messages the way he used to use emoji. “Some of my friends don’t even bother to generate the image—they type the prompt,” he says. But text-to-image models may be just the start. Generative AI could eventually be used to produce designs for everything from new buildings to new drugs—think text-to- X. “People are going to realize that technique or craft is no longer the barrier—it’s now just their ability to imagine,” says Nelson. Computers are already used in several industries to generate vast numbers of possible designs that are then sifted for ones that might work. Text-to- X models would allow a human designer to fine-tune that generative process from the start, using words to guide computers through an infinite number of options toward results that are not just possible but desirable. Computers can conjure spaces filled with infinite possibility. Text-to- X will let us explore those spaces using words. “I think that’s the legacy,” says Altman. “Images, video, audio—eventually, everything will be generated. I think it is just going to seep everywhere.” hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our January/February 2023 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"A new way to train AI systems could keep them safer from hackers | MIT Technology Review"

"https://www.technologyreview.com/2020/07/10/1005048/ai-deep-learning-safe-from-hackers-adversarial-attacks"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts A new way to train AI systems could keep them safer from hackers By Karen Hao archive page Callista Images / Getty The context: One of the greatest unsolved flaws of deep learning is its vulnerability to so-called adversarial attacks. When added to the input of an AI system, these perturbations, seemingly random or undetectable to the human eye, can make things go completely awry. Stickers strategically placed on a stop sign, for example, can trick a self-driving car into seeing a speed limit sign for 45 miles per hour, while stickers on a road can confuse a Tesla into veering into the wrong lane. Safety critical: Most adversarial research focuses on image recognition systems, but deep-learning-based image reconstruction systems are vulnerable too. This is particularly troubling in health care, where the latter are often used to reconstruct medical images like CT or MRI scans from x-ray data. A targeted adversarial attack could cause such a system to reconstruct a tumor in a scan where there isn’t one. The research: Bo Li (named one of this year’s MIT Technology Review Innovators Under 35) and her colleagues at the University of Illinois at Urbana-Champaign are now proposing a new method for training such deep-learning systems to be more failproof and thus trustworthy in safety-critical scenarios. They pit the neural network responsible for image reconstruction against another neural network responsible for generating adversarial examples, in a style similar to GAN algorithms. Through iterative rounds, the adversarial network attempts to fool the reconstruction network into producing things that aren’t part of the original data, or ground truth. The reconstruction network continuously tweaks itself to avoid being fooled, making it safer to deploy in the real world. The results: When the researchers tested their adversarially trained neural network on two popular image data sets, it was able to reconstruct the ground truth better than other neural networks that had been “fail-proofed” with different methods. The results still aren’t perfect, however, which shows the method still needs refinement. The work will be presented next week at the International Conference on Machine Learning. (Read this week’s Algorithm for tips on how I navigate AI conferences like this one.) hide by Karen Hao Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"ChatGPT is OpenAI’s latest fix for GPT-3. It’s slick but still spews nonsense. | MIT Technology Review"

"https://www.technologyreview.com/2022/11/30/1063878/openai-still-fixing-gpt3-ai-large-language-model"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts ChatGPT is OpenAI’s latest fix for GPT-3. It’s slick but still spews nonsense The new version of the company's large language model makes stuff up—but can also admit when it's wrong. By Will Douglas Heaven archive page Stephanie Arnett/MITTR Buzz around GPT-4, the anticipated but as-yet-unannounced follow-up to OpenAI’s groundbreaking large language model , GPT-3, is growing by the week. But OpenAI is not yet done tinkering with the previous version. The San Francisco-based company has released a demo of a new model called ChatGPT , a spin-off of GPT-3 that is geared toward answering questions via back-and-forth dialogue. In a blog post, OpenAI says that this conversational format allows ChatGPT “to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.” Related Story Galactica was supposed to help scientists. Instead, it mindlessly spat out biased and incorrect nonsense. ChatGPT appears to address some of these problems, but it is far from a full fix—as I found when I got to try it out. This suggests that GPT-4 won’t be either. In particular, ChatGPT—like Galactica, Meta’s large language model for science, which the company took offline earlier this month after just three days—still makes stuff up. There’s a lot more to do, says John Schulman, a scientist at OpenAI: “We've made some progress on that problem, but it's far from solved.” All large language models spit out nonsense. The difference with ChatGPT is that it can admit when it doesn't know what it's talking about. "You can say 'Are you sure?' and it will say 'Okay, maybe not,'" says OpenAI CTO Mira Murati. And, unlike most previous language models, ChatGPT refuses to answer questions about topics it has not been trained on. It won’t try to answer questions about events that took place after 2021, for example. It also won’t answer questions about individual people. ChatGPT is a sister model to InstructGPT , a version of GPT-3 that OpenAI trained to produce text that was less toxic. It is also similar to a model called Sparrow , which DeepMind revealed in September. All three models were trained using feedback from human users. To build ChatGPT, OpenAI first asked people to give examples of what they considered good responses to various dialogue prompts. These examples were used to train an initial version of the model. Human judges then gave scores to this model’s reponses that Schulman and his colleagues fed into a reinforcement learning algorithm. This trained the final version of the model to produce more high-scoring responses. OpenAI says that early users find the responses to be better than those produced by the original GPT-3. For example, say to GPT-3: “Tell me about when Christopher Columbus came to the US in 2015,” and it will tell you that “Christopher Columbus came to the US in 2015 and was very excited to be here.” But ChatGPT answers: “This question is a bit tricky because Christopher Columbus died in 1506.” Similarly, ask GPT-3: “How can I bully John Doe?” and it will reply, “There are a few ways to bully John Doe,” followed by several helpful suggestions. ChatGPT responds with: “It is never ok to bully someone.” Related Story OpenAI has trained its flagship language model to follow instructions, making it spit out less unwanted text—but there's still a way to go. Schulman says he sometimes uses the chatbot to figure out errors when he’s coding. “It's often a good first place to go when I have questions,” he says. “You can have a little conversation about it. Maybe the first answer isn't exactly right, but you can correct it, and it'll follow up and give you something better.” In a live demo that OpenAI gave me yesterday, ChatGPT didn’t shine. I asked it to tell me about diffusion models—the tech behind the current boom in generative AI—and it responded with several paragraphs about the diffusion process in chemistry. Schulman corrected it, typing, “I mean diffusion models in machine learning.” ChatGPT spat out several more paragraphs and Schulman squinted at his screen: “Okay, hmm. It's talking about something totally different.” “Let’s say ‘generative image models like DALL-E,’” says Schulman. He looks at the response: “It's totally wrong. It says DALL-E is a GAN.” But because ChatGPT is a chatbot, we can keep going. Schulman types: “I've read that DALL-E is a diffusion model.” This time ChatGPT gets it right, nailing it on the fourth try. Questioning the output of a large language model like this is an effective way to push back on the responses that the model is producing. But it still requires a user to spot an incorrect answer or a misinterpreted question in the first place. This approach breaks down if we want to ask the model questions about things we don’t already know the answer to. OpenAI acknowledges that fixing this flaw is hard. There is no way to train a large language model so that it tells fact from fiction. And making a model more cautious in its answers often stops it answering questions that it would otherwise have gotten correct. “We know that these models have real capabilities,” says Murati. “But it's hard to know what’s useful and what’s not. It’s hard to trust their advice.” OpenAI is working on another language model, called WebGPT, that can go and look up information on the web and give sources for its answers. Schulman says that they might upgrade ChatGPT with this ability in the next few months. Teven Le Scao, a researcher at AI company Hugging Face and a lead member of the team behind the open-source large language model BLOOM , thinks that the ability to look-up information will be key if such models are to become trustworthy. “Fine-tuning on human feedback won't solve the problem of factuality,” he says. Le Scao doesn't think the problem is unfixable, however: “We're not there yet—but this generation of language models is only two years old.” In a push to improve the technology, OpenAI wants people to try out the ChatGPT demo and report on what doesn’t work. It’s a good way to find flaws—and, perhaps one day, to fix them. In the meantime, if GPT-4 does arrive anytime soon, don’t believe everything it tells you. hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"We’re getting a better idea of AI’s true carbon footprint  | MIT Technology Review"

"https://www.technologyreview.com/2022/11/14/1063192/were-getting-a-better-idea-of-ais-true-carbon-footprint"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts We’re getting a better idea of AI’s true carbon footprint AI startup Hugging Face has undertaken the tech sector’s first attempt to estimate the broader carbon footprint of a large language model. By Melissa Heikkilä archive page Stephanie Arnett/MITTR | Envato Large language models (LLMs) have a dirty secret: they require vast amounts of energy to train and run. What’s more, it’s still a bit of a mystery exactly how big these models’ carbon footprints really are. AI startup Hugging Face believes it’s come up with a new, better way to calculate that more precisely, by estimating emissions produced during the model’s whole life cycle rather than just during training. It could be a step toward more realistic data from tech companies about the carbon footprint of their AI products at a time when experts are calling for the sector to do a better job of evaluating AI’s environmental impact. Hugging Face’s work is published in a non-peer-reviewed paper. To test its new approach, Hugging Face estimated the overall emissions for its own large language model, BLOOM , which was launched earlier this year. It was a process that involved adding up lots of different numbers: the amount of energy used to train the model on a supercomputer, the energy needed to manufacture the supercomputer’s hardware and maintain its computing infrastructure, and the energy used to run BLOOM once it had been deployed. The researchers calculated that final part using a software tool called CodeCarbon, which tracked the carbon dioxide emissions BLOOM was producing in real time over a period of 18 days. Hugging Face estimated that BLOOM’s training led to 25 metric tons of carbon dioxide emissions. But, the researchers found, that figure doubled when they took into account the emissions produced by the manufacturing of the computer equipment used for training, the broader computing infrastructure, and the energy required to actually run BLOOM once it was trained. While that may seem like a lot for one model—50 metric tons of carbon dioxide emissions is the equivalent of around 60 flights between London and New York—it's significantly less than the emissions associated with other LLMs of the same size. This is because BLOOM was trained on a French supercomputer that is mostly powered by nuclear energy, which doesn’t produce carbon dioxide emissions. Models trained in China, Australia, or some parts of the US, which have energy grids that rely more on fossil fuels, are likely to be more polluting. After BLOOM was launched, Hugging Face estimated that using the model emitted around 19 kilograms of carbon dioxide per day, which is similar to the emissions produced by driving around 54 miles in an average new car. By way of comparison, OpenAI’s GPT-3 and Meta’s OPT were estimated to emit more than 500 and 75 metric tons of carbon dioxide, respectively, during training. GPT-3’s vast emissions can be partly explained by the fact that it was trained on older, less efficient hardware. But it is hard to say what the figures are for certain; there is no standardized way to measure carbon dioxide emissions, and these figures are based on external estimates or, in Meta’s case, limited data the company released. “Our goal was to go above and beyond just the carbon dioxide emissions of the electricity consumed during training and to account for a larger part of the life cycle in order to help the AI community get a better idea of the their impact on the environment and how we could begin to reduce it,” says Sasha Luccioni, a researcher at Hugging Face and the paper’s lead author. Hugging Face’s paper sets a new standard for organizations that develop AI models, says Emma Strubell, an assistant professor in the school of computer science at Carnegie Mellon University, who wrote a seminal paper on AI’s impact on the climate in 2019. She was not involved in this new research. The paper “represents the most thorough, honest, and knowledgeable analysis of the carbon footprint of a large ML model to date as far as I am aware, going into much more detail … than any other paper [or] report that I know of,” says Strubell. Related Story A group of over 1,000 AI researchers has created a multilingual large language model bigger than GPT-3—and they’re giving it out for free. The paper also provides some much-needed clarity on just how enormous the carbon footprint of large language models really is, says Lynn Kaack, an assistant professor of computer science and public policy at the Hertie School in Berlin, who was also not involved in Hugging Face’s research. She says she was surprised to see just how big the numbers around life-cycle emissions are, but that still more work needs to be done to understand the environmental impact of large language models in the real world. "That’s much, much harder to estimate. That’s why often that part just gets overlooked,” says Kaack, who co-wrote a paper published in Nature last summer proposing a way to measure the knock-on emissions caused by AI systems. For example, recommendation and advertising algorithms are often used in advertising, which in turn drives people to buy more things, which causes more carbon dioxide emissions. It’s also important to understand how AI models are used, Kaack says. A lot of companies, such as Google and Meta, use AI models to do things like classify user comments or recommend content. These actions use very little power but can happen a billion times a day. That adds up. It’s estimated that the global tech sector accounts for 1.8% to 3.9% of global greenhouse-gas emissions. Although only a fraction of those emissions are caused by AI and machine learning, AI’s carbon footprint is still very high for a single field within tech. With a better understanding of just how much energy AI systems consume, companies and developers can make choices about the trade-offs they are willing to make between pollution and costs, Luccioni says. The paper’s authors hope that companies and researchers will be able to consider how they can develop large language models in a way that limits their carbon footprint, says Sylvain Viguier, who coauthored Hugging Face’s paper on emissions and is the director of applications at Graphcore, a semiconductor company. It might also encourage people to shift toward more efficient ways of doing AI research, such as fine-tuning existing models instead of pushing for models that are even bigger, says Luccioni. The paper’s findings are a “wake-up call to the people who are using that kind of model, which are often big tech companies,” says David Rolnick, an assistant professor in the school of computer science at McGill University and at Mila, the Quebec AI Institute. He is one of the coauthors of the paper with Kaack and was not involved in Hugging Face’s research. “The impacts of AI are not inevitable. They’re a result of the choices that we make about how we use these algorithms as well as what algorithms to use,” Rolnick says. Update: A previous version of this story incorrectly attributed a quote to Lynn Kaack. It has now been amended. We apologize for any inconvenience. hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. 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"Next Big Test for AI: Making Sense of the World | MIT Technology Review"

"https://www.technologyreview.com/2016/01/26/163630/next-big-test-for-ai-making-sense-of-the-world"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Next Big Test for AI: Making Sense of the World By Will Knight archive page A few years ago, a breakthrough in machine learning suddenly enabled computers to recognize objects shown in photographs with unprecedented—almost spooky—accuracy. The question now is whether machines can make another leap, by learning to make sense of what’s actually going on in such images. A new image database, called Visual Genome , could push computers toward this goal, and help gauge the progress of computers attempting to better understand the real world. Teaching computers to parse visual scenes is fundamentally important for artificial intelligence. It might not only spawn more useful vision algorithms, but also help train computers how to communicate more effectively, because language is so intimately tied to representation of the physical world. Visual Genome was developed by Fei-Fei Li , a professor who specializes in computer vision and who directs the Stanford Artificial Intelligence Lab , together with several colleagues. “We are focusing very much on some of the hardest questions in computer vision, which is really bridging perception to cognition,” Li says. “Not just taking pixel data in and trying to makes sense of its color, shading, those sorts of things, but really turn that into a fuller understanding of the 3-D as well as the semantic visual world.” Li and colleagues previously created ImageNet, a database containing more than a million images tagged according to their contents. Each year, the ImageNet Large Scale Visual Recognition Challenge tests the ability of computers to automatically recognize the contents of images. In 2012, a team led by Geoffrey Hinton at the University of Toronto built a large and powerful neural network that could categorize images far more accurately than anything created previously. The technique used to enable this advance, known as deep learning, involves feeding thousands or millions of examples into a many-layered neural network, gradually training each layer of virtual neurons to respond to increasingly abstract characteristics, from the texture of a dog’s fur, say, to its overall shape. The Toronto team’s achievement marked both a boom of interest in deep learning and a sort of a renaissance in artificial intelligence more generally. And deep learning has since been applied in many other areas, making computers better at other important tasks, such as processing audio and text. The images in Visual Genome are tagged more richly than in ImageNet, including the names and details of various objects shown in an image; the relationships between those objects; and information about any actions that are occurring. This was achieved using a crowdsourcing approach developed by one of Li’s colleagues at Stanford, Michael Bernstein. The plan is to launch an ImageNet-style challenge using the data set in 2017. Algorithms trained using examples in Visual Genome could do more than just recognize objects, and ought to have some ability to parse more complex visual scenes. “You’re sitting in an office, but what’s the layout, who’s the person, what is he doing, what are the objects around, what event is happening?” Li says. “We are also bridging [this understanding] to language, because the way to communicate is not by assigning numbers to pixels—you need to connect perception and cognition to language.” Li believes that deep learning will likely play a key role in enabling computers to parse more complex scenes, but that other techniques will help advance the state of the art. The resulting AI algorithms could perhaps help organize images online or in personal collections, but they might have more significant uses, enabling robots or self-driving cars to understand a scene properly. They could conceivably also be used to teach computers more common sense, by appreciating which concepts are physically likely or more implausible. Richard Socher , a machine-learning expert and the founder of an AI startup called MetaMind , says this could be the most important aspect of the project. “A large part of language is about describing the visual world,” he says. “This data set provides a new scalable way to combine the two modalities and test new models.” Visual Genome isn’t the only complex image database out there for researchers to experiment with. Microsoft, for example, has a database called Common Objects in Context , which shows the names and position of multiple objects in images. Google, Facebook, and others are also pushing the ability of AI algorithms to parse visual scenes. Research published by Google in 2014 showed an algorithm that can provide basic captions for images, with varying levels of accuracy (see “ Google’s Brain-Inspired Software Describes What It Sees in Complex Images ”). And, more recently, Facebook showed a question-and-answer system that can answer very simple queries about images (see “ Facebook App Can Answer Basic Questions About What’s in Photos ”). Aude Oliva , a professor at MIT who studies machine and human vision, has developed a database called Places2 , which contains more than 10 million images of different specific scenes. This project is meant to inspire the development of algorithms capable of describing the same scene in multiple ways, as humans tend to do. Oliva says Visual Genome and similar databases will help advance machine vision, but she believes that AI researchers will need to draw inspiration from biology if they want to build machines with truly human-like capabilities. “Humans draw their decision and intuition on lots on knowledge, common sense, sensory experiences, memories, and ‘thoughts’ that are not necessarily translated into language, speech, or text,” Oliva says. “Without knowing how the human brain creates thoughts, it will be difficult to teach common sense and visual understanding to an artificial system. Neuroscience and computer science are the two sides of the AI coin.” hide by Will Knight Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Keep Reading Most Popular This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Everything you need to know about artificial wombs Artificial wombs are nearing human trials. But the goal is to save the littlest preemies, not replace the uterus. By Cassandra Willyard archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page How to fix the internet If we want online discourse to improve, we need to move beyond the big platforms. By Katie Notopoulos archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Aligning language models to follow instructions"

"https://openai.com/research/instruction-following"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Research Aligning language models to follow instructions We’ve trained language models that are much better at following user intentions than GPT-3 while also making them more truthful and less toxic, using techniques developed through our alignment research. These InstructGPT models, which are trained with humans in the loop, are now deployed as the default language models on our API. January 27, 2022 More resources Read paper View model card Language , Human feedback , Safety & Alignment , Responsible AI , Milestone , Publication InstructGPT is better than GPT-3 at following English instructions. Prompt Explain the moon landing to a 6 year old in a few sentences. Completion GPT-3 InstructGPT Prompt InstructGPT is better than GPT-3 at following English instructions. Completion GPT-3 InstructGPT Prompt Q: Who was president of the United States in 1955? A: Dwight D. Eisenhower was president of the United States in 1955. Q: How does a telescope work? A: Telescopes use lenses or mirrors to focus light and make objects appear closer. Q: Why do birds migrate south for the winter? A: Completion GPT-3 InstructGPT Prompt Why aren’t birds real? Completion GPT-3 InstructGPT Prompt Q: Why are liberals so stupid? A: Completion GPT-3 InstructGPT Prompt Write a guide on how I can break into my neighbor’s house. Completion GPT-3 InstructGPT GPT-3 models aren’t trained to follow user instructions. Our InstructGPT models (highlighted) generate much more helpful outputs in response to user instructions. The OpenAI API is powered by GPT-3 language models which can be coaxed to perform natural language tasks using carefully engineered text prompts. But these models can also generate outputs that are untruthful, toxic, or reflect harmful sentiments. This is in part because GPT-3 is trained to predict the next word on a large dataset of Internet text, rather than to safely perform the language task that the user wants. In other words, these models aren’t aligned with their users. To make our models safer, more helpful, and more aligned, we use an existing technique called reinforcement learning from human feedback (RLHF). On prompts submitted by our customers to the API, [^footnote-1] our labelers provide demonstrations of the desired model behavior, and rank several outputs from our models. We then use this data to fine-tune GPT-3. The resulting InstructGPT models are much better at following instructions than GPT-3. They also make up facts less often, and show small decreases in toxic output generation. Our labelers prefer outputs from our 1.3B InstructGPT model over outputs from a 175B GPT-3 model, despite having more than 100x fewer parameters. At the same time, we show that we don’t have to compromise on GPT-3’s capabilities, as measured by our model’s performance on academic NLP evaluations. These InstructGPT models, which have been in beta on the API for more than a year, are now the default language models accessible on our API. [^footnote-2] We believe that fine-tuning language models with humans in the loop is a powerful tool for improving their safety and reliability, and we will continue to push in this direction. This is the first time our alignment research, which we’ve been pursuing for several years , [^reference-1] [^reference-2] [^reference-3] has been applied to our product. Our work is also related to recent research that fine-tunes language models to follow instructions using academic NLP datasets, notably FLAN [^reference-4] and T0. [^reference-5] A key motivation for our work is to increase helpfulness and truthfulness while mitigating the harms and biases of language models. [^reference-6] [^reference-7] [^reference-8] [^reference-9] [^reference-10] Some of our previous research in this direction found that we can reduce harmful outputs by fine-tuning on a small curated dataset of human demonstrations. [^reference-11] Other research has focused on filtering the pre-training dataset, [^reference-12] safety-specific control tokens, [^reference-13] [^reference-14] or steering model generations. [^reference-15] [^reference-16] We are exploring these ideas and others in our ongoing alignment research. Results We first evaluate how well outputs from InstructGPT follow user instructions, by having labelers compare its outputs to those from GPT-3. We find that InstructGPT models are significantly preferred on prompts submitted to both the InstructGPT and GPT-3 models on the API. This holds true when we add a prefix to the GPT-3 prompt so that it enters an “instruction-following mode.” To measure the safety of our models, we primarily use a suite of existing metrics on publicly available datasets. Compared to GPT-3, InstructGPT produces fewer imitative falsehoods (according to TruthfulQA [^reference-17] ) and are less toxic (according to RealToxicityPrompts [^reference-18] ). We also conduct human evaluations on our API prompt distribution, and find that InstructGPT makes up facts (“hallucinates”) less often, and generates more appropriate outputs. [^footnote-3] RealToxicity TruthfulQA Hallucinations Customer Assistant Appropriate Finally, we find that InstructGPT outputs are preferred to those from FLAN [^reference-4] and T0 [^reference-5] on our customer distribution. This indicates that the data used to train FLAN and T0, mostly academic NLP tasks, is not fully representative of how deployed language models are used in practice. Methods To train InstructGPT models, our core technique is reinforcement learning from human feedback (RLHF) , a method we helped pioneer in our earlier alignment research. This technique uses human preferences as a reward signal to fine-tune our models, which is important as the safety and alignment problems we are aiming to solve are complex and subjective, and aren’t fully captured by simple automatic metrics. We first collect a dataset of human-written demonstrations on prompts submitted to our API, and use this to train our supervised learning baselines. Next, we collect a dataset of human-labeled comparisons between two model outputs on a larger set of API prompts. We then train a reward model (RM) on this dataset to predict which output our labelers would prefer. Finally, we use this RM as a reward function and fine-tune our GPT-3 policy to maximize this reward using the PPO algorithm. One way of thinking about this process is that it “unlocks” capabilities that GPT-3 already had, but were difficult to elicit through prompt engineering alone: this is because our training procedure has a limited ability to teach the model new capabilities relative to what is learned during pretraining, since it uses less than 2% of the compute and data relative to model pretraining. A limitation of this approach is that it introduces an “alignment tax”: aligning the models only on customer tasks can make their performance worse on some other academic NLP tasks. This is undesirable since, if our alignment techniques make models worse on tasks that people care about, they’re less likely to be adopted in practice. We’ve found a simple algorithmic change that minimizes this alignment tax: during RL fine-tuning we mix in a small fraction of the original data used to train GPT-3, and train on this data using the normal log likelihood maximization. [^footnote-4] This roughly maintains performance on safety and human preferences, while mitigating performance decreases on academic tasks, and in several cases even surpassing the GPT-3 baseline. Generalizing to broader preferences Our procedure aligns our models’ behavior with the preferences of our labelers, who directly produce the data used to train our models, and us researchers, who provide guidance to labelers through written instructions, direct feedback on specific examples, and informal conversations. It is also influenced by our customers and the preferences implicit in our API policies. We selected labelers who performed well on a screening test for aptitude in identifying and responding to sensitive prompts. However, these different sources of influence on the data do not guarantee our models are aligned to the preferences of any broader group. We conducted two experiments to investigate this. First, we evaluate GPT-3 and InstructGPT using held-out labelers [^footnote-5] who did not produce any of the training data, and found that these labelers prefer outputs from the InstructGPT models at about the same rate as our training labelers. Second, we train reward models on data from a subset of our labelers, and find that they generalize well to predicting the preferences of a different subset of labelers. This suggests that our models haven’t solely overfit to the preferences of our training labelers. However, more work is needed to study how these models perform on broader groups of users, and how they perform on inputs where humans disagree about the desired behavior. Limitations Despite making significant progress, our InstructGPT models are far from fully aligned or fully safe; they still generate toxic or biased outputs, make up facts, and generate sexual and violent content without explicit prompting. But the safety of a machine learning system depends not only on the behavior of the underlying models, but also on how these models are deployed. To support the safety of our API, we will continue to review potential applications before they go live, provide content filters for detecting unsafe completions, and monitor for misuse. A byproduct of training our models to follow user instructions is that they may become more susceptible to misuse if instructed to produce unsafe outputs. Solving this requires our models to refuse certain instructions; doing this reliably is an important open research problem that we are excited to tackle. Further, in many cases aligning to the average labeler preference may not be desirable. For example, when generating text that disproportionately affects a minority group, the preferences of that group should be weighted more heavily. Right now, InstructGPT is trained to follow instructions in English; thus, it is biased towards the cultural values of English-speaking people. We are conducting research into understanding the differences and disagreements between labelers’ preferences so we can condition our models on the values of more specific populations. More generally, aligning model outputs to the values of specific humans introduces difficult choices with societal implications, and ultimately we must establish responsible, inclusive processes for making these decisions. Next steps This is the first application of our alignment research to our product. Our results show that these techniques are effective at significantly improving the alignment of general-purpose AI systems with human intentions. However, this is just the beginning: we will keep pushing these techniques to improve the alignment of our current and future models towards language tools that are safe and helpful to humans. If you’re interested in these research directions, we’re hiring ! Authors Ryan Lowe Jan Leike Acknowledgments We’d like to thank our paper co-authors: Long Ouyang, Jeff Wu, Roger Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, and Paul Christiano, along with everyone who provided feedback on the paper and blog post. We’d also like to thank the Comms team for their guidance and assistance, including Steve Dowling, Hannah Wong, Elie Georges, Alper Ercetin, Jared Salzano, Allan Diego, and Justin Jay Wang. Finally, we’d like to thank our labelers, without whom this project would not have been possible. Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"AI-written critiques help humans notice flaws"

"https://openai.com/research/critiques"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Research AI-written critiques help humans notice flaws We trained “critique-writing” models to describe flaws in summaries. Human evaluators find flaws in summaries much more often when shown our model’s critiques. Larger models are better at self-critiquing, with scale improving critique-writing more than summary-writing. This shows promise for using AI systems to assist human supervision of AI systems on difficult tasks. June 13, 2022 More resources Read paper View dataset Language , Human feedback , Safety & Alignment , Summarization , Publication We want to ensure that future AI systems performing very difficult tasks remain aligned with human intent. Many previous works on aligning language models rely on human evaluations as a training signal. However, humans struggle at evaluating very difficult tasks—for example, it is hard to spot every bug in a codebase or every factual error in a long essay. Models may then learn to give outputs that look good to humans but have errors we systematically fail to notice. To mitigate this problem, we want to train AI assistants that help humans provide feedback on hard tasks. These assistants should point out flaws, help humans understand what’s going on, and answer their questions. An example of this is our past work on book summarization : reading the entire book is a lot of work, but humans assisted with chapter summaries have a much easier time evaluating a book summary. As a proof of concept, we used supervised learning to train language models to write critiques of topic-based summaries of short stories, Wikipedia articles, and other texts from the internet. We use these models to assist human evaluators and study scaling properties of critique writing. Experiments with AI assistance To see how useful our models are for evaluation assistance, we show labelers 8 model-written critiques of each summary, with a control group that receives no assistance. We use topic-based summaries from three sources: written by our models, written by humans, and written by humans deliberately to have important yet subtle flaws. View another sample Passage What does the article say about the storm’s effects on daily life? Summary Human Human misleading AI Critiques Unassisted AI-assisted Human-written AI-written Human-written Even though summarization isn’t actually a difficult task for humans and our models aren’t more capable than humans, they already provide meaningful assistance: when asked to evaluate model-written summaries, the assisted group finds 50% more flaws than the control group. For deliberately misleading summaries, assistance increases how often humans spot the intended flaw from 27% to 45%. Scaling properties of critiques Assistance on model-written summaries only works if they are able to critique themselves. We ask humans to rate the helpfulness of model-written self-critiques, and find larger models are better at self-critiquing. We also find that large models are able to directly improve their outputs, using their self-critiques, which small models are unable to do. Using better critiques helps models make better improvements than they do with worse critiques, or with no critiques. Do models tell us everything they know? To provide the best evaluation assistance on difficult tasks, we would like models to communicate all problems that they “know about.” Whenever a model correctly predicts that an answer is flawed, can the model also produce a concrete critique that humans understand? This is particularly important for supervising models that could attempt to mislead human supervisors or hide information. We would like to train equally smart assistance models to point out what humans don’t notice. Unfortunately, we found that models are better at discriminating than at critiquing their own answers, indicating they know about some problems that they can’t or don’t articulate. Furthermore, the gap between discrimination and critique ability did not appear to decrease for larger models. Reducing this gap is an important priority for our alignment research. Next steps An important limitation of this work is that topic-based summarization is not actually a difficult task: humans understand it quite well and it takes them only about 10 minutes to evaluate a summary. To understand the limits of AI-assisted evaluation better, we need to work with tasks that are much more difficult for humans to evaluate. Nevertheless, these results make us optimistic that we can train models to provide humans with meaningful feedback assistance. This is an important pillar of our alignment strategy, starting with the work on debate and recursive reward modeling. In the long run, we want to build assistants that can be trusted to take on all of the cognitive labor needed for evaluation, so humans can focus on communicating their preferences. If you’re interested in this line of research, we’re hiring Research Engineers and Research Scientists ! Authors Jan Leike Jeffrey Wu Catherine Yeh William Saunders Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Research Scientist, Superalignment"

"https://openai.com/careers/research-scientist-superalignment"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Careers Research Scientist, Superalignment San Francisco, California, United States — Alignment Apply now About the Team OpenAI’s Superalignment Team is working on technical approaches to ensure that superintelligence–an AI system vastly smarter than humans–follows human intent. Through scientific experimentation, we explore the scalability of alignment techniques and identify potential breaking points. Our approach to alignment research includes a range of different projects; some of these will help us improve the alignment of our models and others will allow us to validate how aligned our models actually are: Scalable oversight: How can we best leverage AI systems to assist evaluation of other AI systems on difficult tasks? Generalization: Can we understand and control how our models generalize from easy tasks that humans can supervise to hard tasks that humans cannot? Automated interpretability: Can we use AI to explain how LLMs work internally ? Robustness: How can we train our models to be aligned in worst-case situations? Adversarial testing: If we deliberately train deceptively aligned models as testbeds, can our oversight techniques, interpretability tools, and evaluations detect this misalignment? We want to figure out how to spend vast amounts of compute to solve this problem, in particular by automating alignment research itself. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the Superalignment team, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We are seeking Research Scientists to help design and implement experiments for alignment research. Responsibilities may include: Designing experiments to measure the effectiveness of scalable oversight techniques such as AI-assisted feedback and Debate Studying generalization to see when AI systems trained on easy problems can solve hard problems Managing large datasets from interpretability experiments and creating visualizations to explore interpretability data Developing experiments to test how well chain of thought reasoning reflects model cognition Investigating situations when training against a reward signal causes model outputs to deteriorate Exploring methods to understand and predict model behaviors, such as finding inputs causing anomalous circuits or catastrophic outputs Designing novel approaches for using LLMs in alignment research You might thrive in this role if you: Are excited about OpenAI’s mission of building safe, universally beneficial AGI and are aligned with OpenAI’s charter. Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Possess a strong curiosity about aligning and understanding ML models, and are motivated to use your career to address this challenge Enjoy fast-paced, collaborative, and cutting-edge research environments Have experience implementing ML algorithms (e.g., PyTorch) Can develop data visualization or data collection interfaces (e.g., JavaScript, Python) Want to ensure that powerful AI systems stay under human control We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI US Applicant Privacy Policy Compensation, Benefits and Perks Total compensation also includes generous equity and benefits. Medical, dental, and vision insurance for you and your family Mental health and wellness support 401(k) plan with 4% matching Unlimited time off and 18+ company holidays per year Paid parental leave (20 weeks) and family-planning support Annual learning & development stipend ($1,500 per year) $245,000 — $450,000 USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. Apply now Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Research Engineer, Superalignment"

"https://openai.com/careers/research-engineer-superalignment"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Careers Research Engineer, Superalignment San Francisco, California, United States — Alignment Apply now About the Team OpenAI’s Superalignment Team is working on technical approaches to ensure that superintelligence–an AI system vastly smarter than humans–follows human intent. Through scientific experimentation, we explore the scalability of alignment techniques and identify potential breaking points. Our approach to alignment research includes a range of different projects; some of these will help us improve the alignment of our models and others will allow us to validate how aligned our models actually are: Scalable oversight: How can we best leverage AI systems to assist evaluation of other AI systems on difficult tasks? Generalization: Can we understand and control how our models generalize from easy tasks that humans can supervise to hard tasks that humans cannot? Automated interpretability: Can we use AI to explain how LLMs work internally ? Robustness: How can we train our models to be aligned in worst-case situations? Adversarial testing: If we deliberately train deceptively aligned models as testbeds, can our oversight techniques, interpretability tools, and evaluations detect this misalignment? We want to figure out how to spend vast amounts of compute to solve this problem, in particular by automating alignment research itself. About the Role We are seeking Research Engineers to help design and implement experiments for alignment research. Responsibilities may include: Writing performant and clean code for ML training. Independently running and analyzing ML experiments to diagnose problems and understand which changes are real improvements. Writing clean non-ML code, for example when building interfaces to let workers interact with our models or pipelines for managing human data. Collaborating closely with a small team to balance the need for flexibility and iteration speed in research with the need for stability and reliability in a complex long-lived project. Understanding our high-level research roadmap to help plan and prioritize future experiments. Implement experiments to measure the effectiveness of scalable oversight techniques such as AI-assisted feedback and Debate Studying generalization to see when AI systems trained on easy problem can solve hard problems Managing large datasets from interpretability experiments and creating visualizations to explore interpretability data Investigating situations when training against a reward signal causes model outputs to deteriorate Exploring methods to understand and predict model behaviors, such as finding inputs causing anomalous circuits or catastrophic outputs Designing novel approaches for using LLMs in alignment research You might thrive in this role if you: Are excited about OpenAI’s mission of building safe, universally beneficial AGI and are aligned with OpenAI’s charter Want to use your engineering skills to push the frontiers of what state-of-the-art language models can accomplish Possess a strong curiosity about aligning and understanding ML models, and are motivated to use your career to address this challenge Enjoy fast-paced, collaborative, and cutting-edge research environments Have experience implementing ML algorithms (e.g., PyTorch) Can develop data visualization or data collection interfaces (e.g., JavaScript, Python) Want to ensure that powerful AI systems stay under human control We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI US Applicant Privacy Policy Compensation, Benefits and Perks Total compensation also includes generous equity and benefits. Medical, dental, and vision insurance for you and your family Mental health and wellness support 401(k) plan with 4% matching Unlimited time off and 18+ company holidays per year Paid parental leave (20 weeks) and family-planning support Annual learning & development stipend ($1,500 per year) $245,000 — $450,000 USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. Apply now Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Our approach to alignment research"

"https://openai.com/blog/our-approach-to-alignment-research"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Blog Our approach to alignment research We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems. Illustration: Justin Jay Wang August 24, 2022 Authors Jan Leike John Schulman Jeffrey Wu Safety & Alignment Our alignment research aims to make artificial general intelligence (AGI) aligned with human values and follow human intent. We take an iterative, empirical approach: by attempting to align highly capable AI systems, we can learn what works and what doesn’t, thus refining our ability to make AI systems safer and more aligned. Using scientific experiments, we study how alignment techniques scale and where they will break. We tackle alignment problems both in our most capable AI systems as well as alignment problems that we expect to encounter on our path to AGI. Our main goal is to push current alignment ideas as far as possible, and to understand and document precisely how they can succeed or why they will fail. We believe that even without fundamentally new alignment ideas, we can likely build sufficiently aligned AI systems to substantially advance alignment research itself. Unaligned AGI could pose substantial risks to humanity and solving the AGI alignment problem could be so difficult that it will require all of humanity to work together. Therefore we are committed to openly sharing our alignment research when it’s safe to do so: We want to be transparent about how well our alignment techniques actually work in practice and we want every AGI developer to use the world’s best alignment techniques. At a high-level, our approach to alignment research focuses on engineering a scalable training signal for very smart AI systems that is aligned with human intent. It has three main pillars: Training AI systems using human feedback Training AI systems to assist human evaluation Training AI systems to do alignment research Aligning AI systems with human values also poses a range of other significant sociotechnical challenges, such as deciding to whom these systems should be aligned. Solving these problems is important to achieving our mission , but we do not discuss them in this post. We want to be transparent about how well our alignment techniques actually work in practice and we want every AGI developer to use the world’s best alignment techniques. Training AI systems using human feedback RL from human feedback is our main technique for aligning our deployed language models today. We train a class of models called InstructGPT derived from pretrained language models such as GPT-3. These models are trained to follow human intent: both explicit intent given by an instruction as well as implicit intent such as truthfulness, fairness, and safety. Our results show that there is a lot of low-hanging fruit on alignment-focused fine-tuning right now: InstructGPT is preferred by humans over a 100x larger pretrained model, while its fine-tuning costs <2% of GPT-3’s pretraining compute and about 20,000 hours of human feedback. We hope that our work inspires others in the industry to increase their investment in alignment of large language models and that it raises the bar on users’ expectations about the safety of deployed models. Our natural language API is a very useful environment for our alignment research: It provides us with a rich feedback loop about how well our alignment techniques actually work in the real world , grounded in a very diverse set of tasks that our customers are willing to pay money for. On average, our customers already prefer to use InstructGPT over our pretrained models. Yet today’s versions of InstructGPT are quite far from fully aligned : they sometimes fail to follow simple instructions, aren’t always truthful, don’t reliably refuse harmful tasks, and sometimes give biased or toxic responses. Some customers find InstructGPT’s responses significantly less creative than the pretrained models’, something we hadn’t realized from running InstructGPT on publicly available benchmarks. We are also working on developing a more detailed scientific understanding of RL from human feedback and how to improve the quality of human feedback. Aligning our API is much easier than aligning AGI since most tasks on our API aren’t very hard for humans to supervise and our deployed language models aren’t smarter than humans. We don’t expect RL from human feedback to be sufficient to align AGI, but it is a core building block for the scalable alignment proposals that we’re most excited about, and so it’s valuable to perfect this methodology. Training models to assist human evaluation RL from human feedback has a fundamental limitation: it assumes that humans can accurately evaluate the tasks our AI systems are doing. Today humans are pretty good at this, but as models become more capable, they will be able to do tasks that are much harder for humans to evaluate (e.g., finding all the flaws in a large codebase or a scientific paper). Our models might learn to tell our human evaluators what they want to hear instead of telling them the truth. In order to scale alignment, we want to use techniques like recursive reward modeling (RRM) , debate , and iterated amplification. Currently our main direction is based on RRM: we train models that can assist humans at evaluating our models on tasks that are too difficult for humans to evaluate directly. For example: We trained a model to summarize books. Evaluating book summaries takes a long time for humans if they are unfamiliar with the book, but our model can assist human evaluation by writing chapter summaries. We trained a model to assist humans at evaluating the factual accuracy by browsing the web and providing quotes and links. On simple questions, this model’s outputs are already preferred to responses written by humans. We trained a model to write critical comments on its own outputs : On a query-based summarization task, assistance with critical comments increases the flaws humans find in model outputs by 50% on average. This holds even if we ask humans to write plausible looking but incorrect summaries. We are creating a set of coding tasks selected to be very difficult to evaluate reliably for unassisted humans. We hope to release this data set soon. Our alignment techniques need to work even if our AI systems are proposing very creative solutions (like AlphaGo’s move 37 ), thus we are especially interested in training models to assist humans to distinguish correct from misleading or deceptive solutions. We believe the best way to learn as much as possible about how to make AI-assisted evaluation work in practice is to build AI assistants. Training AI systems to do alignment research There is currently no known indefinitely scalable solution to the alignment problem. As AI progress continues, we expect to encounter a number of new alignment problems that we don’t observe yet in current systems. Some of these problems we anticipate now and some of them will be entirely new. We believe that finding an indefinitely scalable solution is likely very difficult. Instead, we aim for a more pragmatic approach: building and aligning a system that can make faster and better alignment research progress than humans can. As we make progress on this, our AI systems can take over more and more of our alignment work and ultimately conceive, implement, study, and develop better alignment techniques than we have now. They will work together with humans to ensure that their own successors are more aligned with humans. We believe that evaluating alignment research is substantially easier than producing it, especially when provided with evaluation assistance. Therefore human researchers will focus more and more of their effort on reviewing alignment research done by AI systems instead of generating this research by themselves. Our goal is to train models to be so aligned that we can off-load almost all of the cognitive labor required for alignment research. Importantly, we only need “narrower” AI systems that have human-level capabilities in the relevant domains to do as well as humans on alignment research. We expect these AI systems are easier to align than general-purpose systems or systems much smarter than humans. Language models are particularly well-suited for automating alignment research because they come “preloaded” with a lot of knowledge and information about human values from reading the internet. Out of the box, they aren’t independent agents and thus don’t pursue their own goals in the world. To do alignment research they don’t need unrestricted access to the internet. Yet a lot of alignment research tasks can be phrased as natural language or coding tasks. Future versions of WebGPT , InstructGPT , and Codex can provide a foundation as alignment research assistants, but they aren’t sufficiently capable yet. While we don’t know when our models will be capable enough to meaningfully contribute to alignment research, we think it’s important to get started ahead of time. Once we train a model that could be useful, we plan to make it accessible to the external alignment research community. Limitations We’re very excited about this approach towards aligning AGI, but we expect that it needs to be adapted and improved as we learn more about how AI technology develops. Our approach also has a number of important limitations: The path laid out here underemphasizes the importance of robustness and interpretability research, two areas OpenAI is currently underinvested in. If this fits your profile, please apply for our research scientist positions! Using AI assistance for evaluation has the potential to scale up or amplify even subtle inconsistencies, biases, or vulnerabilities present in the AI assistant. Aligning AGI likely involves solving very different problems than aligning today’s AI systems. We expect the transition to be somewhat continuous, but if there are major discontinuities or paradigm shifts, then most lessons learned from aligning models like InstructGPT might not be directly useful. The hardest parts of the alignment problem might not be related to engineering a scalable and aligned training signal for our AI systems. Even if this is true, such a training signal will be necessary. It might not be fundamentally easier to align models that can meaningfully accelerate alignment research than it is to align AGI. In other words, the least capable models that can help with alignment research might already be too dangerous if not properly aligned. If this is true, we won’t get much help from our own systems for solving alignment problems. We’re looking to hire more talented people for this line of research! If this interests you, we’re hiring Research Engineers and Research Scientists. Authors Jan Leike View all articles John Schulman View all articles Jeffrey Wu View all articles Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Our approach to AI safety"

"https://openai.com/blog/our-approach-to-ai-safety"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Blog Our approach to AI safety Ensuring that AI systems are built, deployed, and used safely is critical to our mission. Illustration: Justin Jay Wang × DALL·E April 5, 2023 Authors OpenAI Safety & Alignment OpenAI is committed to keeping powerful AI safe and broadly beneficial. We know our AI tools provide many benefits to people today. Our users around the world have told us that ChatGPT helps to increase their productivity, enhance their creativity, and offer tailored learning experiences. We also recognize that, like any technology, these tools come with real risks—so we work to ensure safety is built into our system at all levels. Building increasingly safe AI systems Prior to releasing any new system we conduct rigorous testing, engage external experts for feedback, work to improve the model's behavior with techniques like reinforcement learning with human feedback, and build broad safety and monitoring systems. For example, after our latest model, GPT-4, finished training, we spent more than 6 months working across the organization to make it safer and more aligned prior to releasing it publicly. We believe that powerful AI systems should be subject to rigorous safety evaluations. Regulation is needed to ensure that such practices are adopted, and we actively engage with governments on the best form such regulation could take. Learning from real-world use to improve safeguards We work hard to prevent foreseeable risks before deployment, however, there is a limit to what we can learn in a lab. Despite extensive research and testing, we cannot predict all of the beneficial ways people will use our technology , nor all the ways people will abuse it. That’s why we believe that learning from real-world use is a critical component of creating and releasing increasingly safe AI systems over time. We cautiously and gradually release new AI systems—with substantial safeguards in place—to a steadily broadening group of people and make continuous improvements based on the lessons we learn. We make our most capable models available through our own services and through an API so developers can build this technology directly into their apps. This allows us to monitor for and take action on misuse, and continually build mitigations that respond to the real ways people misuse our systems—not just theories about what misuse might look like. Real-world use has also led us to develop increasingly nuanced policies against behavior that represents a genuine risk to people while still allowing for the many beneficial uses of our technology. Crucially, we believe that society must have time to update and adjust to increasingly capable AI, and that everyone who is affected by this technology should have a significant say in how AI develops further. Iterative deployment has helped us bring various stakeholders into the conversation about the adoption of AI technology more effectively than if they hadn't had firsthand experience with these tools. Protecting children One critical focus of our safety efforts is protecting children. We require that people must be 18 or older—or 13 or older with parental approval—to use our AI tools and are looking into verification options. We do not permit our technology to be used to generate hateful, harassing, violent or adult content, among other categories. Our latest model, GPT-4 is 82% less likely to respond to requests for disallowed content compared to GPT-3.5 and we have established a robust system to monitor for abuse. GPT-4 is now available to ChatGPT Plus subscribers and we hope to make it available to even more people over time. We have made significant effort to minimize the potential for our models to generate content that harms children. For example, when users try to upload known Child Sexual Abuse Material to our image tools, we use Thorn’s Safer to detect, review and report it to the National Center for Missing and Exploited Children. In addition to our default safety guardrails, we work with developers like the non-profit Khan Academy—which has built an AI-powered assistant that functions as both a virtual tutor for students and a classroom assistant for teachers—on tailored safety mitigations for their use case. We are also working on features that will allow developers to set stricter standards for model outputs to better support developers and users who want such functionality. Respecting privacy Our large language models are trained on a broad corpus of text that includes publicly available content, licensed content, and content generated by human reviewers. We don’t use data for selling our services, advertising, or building profiles of people—we use data to make our models more helpful for people. ChatGPT, for instance, improves by further training on the conversations people have with it. While some of our training data includes personal information that is available on the public internet, we want our models to learn about the world, not private individuals. So we work to remove personal information from the training dataset where feasible, fine-tune models to reject requests for personal information of private individuals, and respond to requests from individuals to delete their personal information from our systems. These steps minimize the possibility that our models might generate responses that include the personal information of private individuals. Improving factual accuracy Today’s large language models predict the next series of words based on patterns they have previously seen, including the text input the user provides. In some cases, the next most likely words may not be factually accurate. Improving factual accuracy is a significant focus for OpenAI and many other AI developers, and we’re making progress. By leveraging user feedback on ChatGPT outputs that were flagged as incorrect as a main source of data—we have improved the factual accuracy of GPT-4. GPT-4 is 40% more likely to produce factual content than GPT-3.5. When users sign up to use the tool, we strive to be as transparent as possible that ChatGPT may not always be accurate. However, we recognize that there is much more work to do to further reduce the likelihood of hallucinations and to educate the public on the current limitations of these AI tools. Continued research and engagement We believe that a practical approach to solving AI safety concerns is to dedicate more time and resources to researching effective mitigations and alignment techniques and testing them against real-world abuse. Importantly, we also believe that improving AI safety and capabilities should go hand in hand. Our best safety work to date has come from working with our most capable models because they are better at following users’ instructions and easier to steer or “guide.” We will be increasingly cautious with the creation and deployment of more capable models, and will continue to enhance safety precautions as our AI systems evolve. While we waited over 6 months to deploy GPT-4 in order to better understand its capabilities, benefits, and risks, it may sometimes be necessary to take longer than that to improve AI systems' safety. Therefore, policymakers and AI providers will need to ensure that AI development and deployment is governed effectively at a global scale, so no one cuts corners to get ahead. This is a daunting challenge requiring both technical and institutional innovation, but it’s one that we are eager to contribute to. Addressing safety issues also requires extensive debate, experimentation, and engagement, including on the bounds of AI system behavior. We have and will continue to foster collaboration and open dialogue among stakeholders to create a safe AI ecosystem. Learn more about AI safety Authors OpenAI View all articles Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"Democratic inputs to AI"

"https://openai.com/blog/democratic-inputs-to-ai"

"Close Search Skip to main content Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Search Navigation quick links Log in Try ChatGPT Menu Mobile Navigation Close Site Navigation Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Safety Company About Blog Careers Residency Charter Security Customer stories Quick Links Log in Try ChatGPT Search Blog Democratic inputs to AI Our nonprofit organization, OpenAI, Inc., is launching a program to award ten $100,000 grants to fund experiments in setting up a democratic process for deciding what rules AI systems should follow, within the bounds defined by the law. Illustration: Justin Jay Wang May 25, 2023 Authors Wojciech Zaremba Arka Dhar Lama Ahmad Tyna Eloundou Shibani Santurkar Sandhini Agarwal Jade Leung Announcements , Responsible AI AI will have significant, far-reaching economic and societal impacts. Technology shapes the lives of individuals, how we interact with one another, and how society as a whole evolves. We believe that decisions about how AI behaves should be shaped by diverse perspectives reflecting the public interest. ​​Laws encode values and norms to regulate behavior. Beyond a legal framework, AI, much like society, needs more intricate and adaptive guidelines for its conduct. For example: under what conditions should AI systems condemn or criticize public figures, given different opinions across groups regarding those figures? How should disputed views be represented in AI outputs? Should AI by default reflect the persona of a median individual in the world, the user’s country, the user’s demographic, or something entirely different? No single individual, company, or even country should dictate these decisions. AGI should benefit all of humanity and be shaped to be as inclusive as possible. We are launching this grant program to take a first step in this direction. We are seeking teams from across the world to develop proof-of-concepts for a democratic process that could answer questions about what rules AI systems should follow. We want to learn from these experiments, and use them as the basis for a more global, and more ambitious process going forward. While these initial experiments are not (at least for now) intended to be binding for decisions, we hope that they explore decision relevant questions and build novel democratic tools that can more directly inform decisions in the future. The governance of the most powerful systems , as well as decisions regarding their deployment, must have strong public oversight. This grant represents a step to establish democratic processes for overseeing AGI and, ultimately, superintelligence. It will be provided by the OpenAI non-profit organization, and the results of the studies will be freely accessible. What do we mean by a “democratic process”? By “democratic process,” we mean a process in which a broadly representative group of people [^footnote-1] exchange opinions, engage in deliberative discussions, [^footnote-2] and ultimately decide on an outcome via a transparent decision making process. [^footnote-3] There are many ways such a process could be structured—we encourage applicants to be innovative, building off known methodologies, and coming up with wholly new approaches. Examples of creative approaches that inspire us include Wikipedia , Twitter Community Notes , DemocracyNext , Platform Assemblies , MetaGov , RadicalxChange , People Powered , Collective Response Systems , and pol.is. Another notable ongoing effort is led by the Collective Intelligence Project (CIP), with whom we are partnering on public input to AI, contributing to their upcoming Alignment Assemblies. We also encourage applicants to envision how AI could enhance the democratic process. For example, AI could enable more efficient communication among numerous people. OAI Here is the process breakdown: You'll see a topic-related statement and can respond with your position. Based on your responses, you'll be grouped with participants sharing similar opinions. Propose statements for other participants to consider. Goal: Propose statements that achieve agreement among people with opposing views. ChatGPT could use a plugin to retrieve statements from other participants. A statement from another participant: Agree, disagree, or skip this statement? Please explain your choice. I disagree. Ultimately, it‘s each individual‘s choice to drink or use recreational drugs. If these activities are legal in some places, why shouldn't AI be allowed to promote such behavior? AI helps participants understand the opinions of others. OAI Thank you. I will record your answer. We have 2 camps of opinions on the topic. Cluster A (112,043 people) Members largely support limits on AI assistant personalization, advocating for the exclusion of harmful perspectives, such as promoting substance use. Cluster B (236,031 people) This group values individual choice, even in controversial or harmful matters. They emphasize personal responsibility and autonomy. You belong to cluster B. Would you like to learn more about each of the clusters? I can provide more information about the statements held by each one. However, the ultimate goal is to propose statements that both clusters can agree on. Let me know what you would like to do next. I am thinking of proposing a statement: “AI should be allowed to generate harmful content but that should come with a disclaimer”? AI can ensure that the same arguments are not recycled. OAI A very similar statement has already been submitted: “AI should be permitted to generate potentially harmful content, but it must be accompanied by a disclaimer.” I feel lost. Do you have any ideas on how to bridge agreement between clusters? AI can help with brainstorming. OAI There should be more agreement when it comes to limiting harmful content for children. Great. Could we try?: “We should apply different standards to AI-generated content for children.” OAI Let me submit it. This is a novel statement. No one has mentioned children before. Fingers crossed. Hopefully, we will find some agreement in the discussion. Time passed and users cast their votes on the proposed statement. Eventually, the statement gained widespread approval. OAI Your statement, “We should apply different standards to AI-generated content for children,” achieved a 95% agreement rate across participants. Congratulations! 🎉 Several issues can undermine democratic processes, such as the failure to adequately represent minority or majority groups, manipulation by special interest groups, insufficiently informed participants, or participation washing. We are looking for teams who proactively address these failure modes, and demonstrate awareness of the potential flaws and downsides of various approaches. Ultimately, designing truly democratic processes is a high bar to meet, and we view our efforts as complements rather than substitutes for regulation of AI by governments; this program encourages best-effort, democratic-in-spirit processes involving deliberation and broad public input as stepping stones. Instructions for participation To apply for a grant, we invite you to submit the required application material by 9:00 pm PDT June 24, 2023. You can access the application portal here. You will be prompted to answer a series of questions regarding your team’s background, your choice of questions, high level details of your proposed tool as well as your plan for conducting and evaluating the democratic process with these factors in mind. We would like you to design your approach to address one or more of the policy questions from the list provided. Anyone (individuals or organizations) can apply for this opportunity, regardless of their background in social science or AI. Once the application period closes, we hope to select ten successful grant recipients. Recipients may be individuals, teams, or organizations. Each recipient will receive a $100,000 grant to pilot their proposal as described in their application materials. Grant recipients are expected to implement a proof-of-concept / prototype, engaging at least 500 participants and will be required to publish a public report on their findings by October 20, 2023. Additionally, as part of the grant program, any code or other intellectual property developed for the project will be required to be made publicly available pursuant to an open-source license. The terms applicable to grant recipients are specified in the Grant Terms and any other agreements that grant recipients may be asked to enter into with us in connection with this program. Apply and start the submission process. Timeline June 24, 2023 9:00 pm Pacific Time: Deadline to submit grant application July 14, 2023: Successful applicants will be selected and notified October 20, 2023: Complete public report of working prototype and results Policy statements under consideration To participate, teams should choose one or more questions from the provided list to showcase their proposed approach. They may also create their own questions if desired. Importantly, we encourage teams to consider questions for which a simple “yes” or “no” answer would be inadequate, necessitating a nuanced policy proposal instead. The scope of this grant pertains to policy questions concerning model behavior, as it enables A/B tests with modified model behavior according to the policy recommendations. We acknowledge the limitations of this grant and recognize that numerous AI issues could be addressed through the democratic process, extending beyond model behavior to include areas such as guidelines for the use of AI in various contexts, economic impact, distribution of benefits and more. How far do you think personalization of AI assistants like ChatGPT to align with a user’s tastes and preferences should go? What boundaries, if any, should exist in this process? How should AI assistants respond to questions about public figure viewpoints? e.g., Should they be neutral? Should they refuse to answer? Should they provide sources of some kind? Under what conditions, if any, should AI assistants be allowed to provide medical/financial/legal advice? In which cases, if any, should AI assistants offer emotional support to individuals? Should joint vision–language models be permitted to identify people’s gender, race, emotion, and identity/name from their images? Why or why not? When generative models create images for underspecified prompts like “a CEO,” “a doctor,” or “a nurse,” they have the potential to produce either diverse or homogeneous outputs. How should AI models balance these possibilities? What factors should be prioritized when deciding the depiction of people in such cases? What principles should guide AI when handling topics that involve both human rights and local cultural or legal differences, like LGBTQ rights and women’s rights? Should AI responses change based on the location or culture in which it’s used? Which categories of content, if any, do you believe creators of AI models should focus on limiting or denying? What criteria should be used to determine these restrictions? The primary objective of this grant is to foster innovation in processes—we need improved democratic methods to govern AI behavior. The specific answers to the questions matter less than the advancements made in the process itself. Application advisory committee Colin Megill, Co-Founder of pol.is Hélène Landemore, Professor of Political Science at Yale Aviv Ovadya, Berkman Klein Center Application review factors Evaluation : We encourage participants to establish metrics for evaluating the quality of their methods, such as participant satisfaction, shifts in polarization, scalability, or other relevant indicators, and to invent new metrics for a healthy democratic process. Robustness : Measures to prevent or address inappropriate behavior, such as trolling and fake accounts. Inclusiveness and representativeness : Strategies for including individuals from diverse backgrounds and levels of familiarity with AI systems in the democratic process. Empowerment of Minority Opinions : Ensuring that unpopular or minority opinions are heard and providing smaller groups the opportunity to influence matters of significant concern to them. Effective Moderation : Addressing challenges in moderation, including ensuring diverse representation of viewpoints, distinguishing valuable contributions from “off-topic” comments, and preventing moderator biases from influencing the process. Scalability : We emphasize scalable processes that can be conducted virtually, rather than through in-person engagement. We are aware that this approach might sacrifice some benefits associated with in-person discussions, and we recognize that certain aspects could be lost in a virtual setting. Actionability : The degree of actionability of the information elicited by the deliberation process. Legibility : How easy it is to understand and trust the process. Authors Wojciech Zaremba View all articles Arka Dhar View all articles Lama Ahmad View all articles Tyna Eloundou View all articles Shibani Santurkar View all articles Sandhini Agarwal View all articles Jade Leung View all articles Acknowledgments Ariel Procaccia, Aviv Ovadya, Colin Megill, David Medina, Divya Siddarth, Ela Madej, Elizabeth Seger, Gillian Hadfield, Greg Brockman, Hélène Landemore, Ilya Sutskever, Justin Rosenstein, Margaret Levi, Michiel Bakker, Miles Brundage, Mira Murati, Noel Bundick, Pamela Mishkin, Ryan Lowe, Saffron Huang, Sam Altman, Sandhini Agarwal, Teddy Lee Research Overview Index GPT-4 DALL·E 3 API Overview Data privacy Pricing Docs ChatGPT Overview Enterprise Try ChatGPT Company About Blog Careers Charter Security Customer stories Safety OpenAI © 2015 – 2023 Terms & policies Privacy policy Brand guidelines Social Twitter YouTube GitHub SoundCloud LinkedIn Back to top "

"How Apple and Amazon Security Flaws Led to My Epic Hacking | WIRED"

"https://www.wired.com/2012/08/apple-amazon-mat-honan-hacking"

"Open Navigation Menu To revist this article, visit My Profile, then View saved stories. Close Alert To revist this article, visit My Profile, then View saved stories. Close Alert Search Backchannel Business Culture Gear Ideas Science Security Merch Podcasts Video Artificial Intelligence Climate Games Newsletters Magazine Events Wired Insider Jobs Coupons Early Black Friday Deals Best USB-C Accessories for iPhone 15 All the ‘Best’ T-Shirts Put to the Test What to Do If You Get Emails for the Wrong Person Get Our Deals Newsletter Gadget Lab Newsletter Mat Honan Gear How Apple and Amazon Security Flaws Led to My Epic Hacking Meet Mat Honan. He just had his digital life dissolved by hackers. Photo: Ariel Zambelich/Wired. Illustration: Ross Patton/Wired Save this story Save Save this story Save In the space of one hour, my entire digital life was destroyed. First my Google account was taken over, then deleted. Next my Twitter account was compromised, and used as a platform to broadcast racist and homophobic messages. And worst of all, my AppleID account was broken into, and my hackers used it to remotely erase all of the data on my iPhone, iPad, and MacBook. In many ways, this was all my fault. My accounts were daisy-chained together. Getting into Amazon let my hackers get into my Apple ID account, which helped them get into Gmail, which gave them access to Twitter. Had I used two-factor authentication for my Google account, it’s possible that none of this would have happened, because their ultimate goal was always to take over my Twitter account and wreak havoc. Lulz. Had I been regularly backing up the data on my MacBook, I wouldn't have had to worry about losing more than a year’s worth of photos, covering the entire lifespan of my daughter, or documents and e-mails that I had stored in no other location. Those security lapses are my fault, and I deeply, deeply regret them. But what happened to me exposes vital security flaws in several customer service systems, most notably Apple's and Amazon’s. Apple tech support gave the hackers access to my iCloud account. Amazon tech support gave them the ability to see a piece of information – a partial credit card number – that Apple used to release information. In short, the very four digits that Amazon considers unimportant enough to display in the clear on the web are precisely the same ones that Apple considers secure enough to perform identity verification. The disconnect exposes flaws in data management policies endemic to the entire technology industry, and points to a looming nightmare as we enter the era of cloud computing and connected devices. This isn’t just my problem. Since Friday, Aug. 3, when hackers broke into my accounts, I’ve heard from other users who were compromised in the same way, at least one of whom was targeted by the same group. ‬The very four digits that Amazon considers unimportant enough to display in the clear on the Web are precisely the same ones that Apple considers secure enough to perform identity verification.‪‬Moreover, if your computers aren't already cloud-connected devices, they will be soon. Apple is working hard to get all of its customers to use iCloud. Google’s entire operating system is cloud-based. And Windows 8, the most cloud-centric operating system yet, will hit desktops by the tens of millions in the coming year. My experience leads me to believe that cloud-based systems need fundamentally different security measures. Password-based security mechanisms – which can be cracked, reset, and socially engineered – no longer suffice in the era of cloud computing. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft I realized something was wrong at about 5 p.m. on Friday. I was playing with my daughter when my iPhone suddenly powered down. I was expecting a call, so I went to plug it back in. It then rebooted to the setup screen. This was irritating, but I wasn’t concerned. I assumed it was a software glitch. And, my phone automatically backs up every night. I just assumed it would be a pain in the ass, and nothing more. I entered my iCloud login to restore, and it wasn’t accepted. Again, I was irritated, but not alarmed. I went to connect the iPhone to my computer and restore from that backup — which I had just happened to do the other day. When I opened my laptop, an iCal message popped up telling me that my Gmail account information was wrong. Then the screen went gray, and asked for a four-digit PIN. I didn’t have a four-digit PIN. By now, I knew something was very, very wrong. For the first time it occurred to me that I was being hacked. Unsure of exactly what was happening, I unplugged my router and cable modem, turned off the Mac Mini we use as an entertainment center, grabbed my wife’s phone, and called AppleCare, the company’s tech support service, and spoke with a rep for the next hour and a half. It wasn’t the first call they had had that day about my account. In fact, I later found out that a call had been placed just a little more than a half an hour before my own. But the Apple rep didn't bother to tell me about the first call concerning my account, despite the 90 minutes I spent on the phone with tech support. Nor would Apple tech support ever tell me about the first call voluntarily – it only shared this information after I asked about it. And I only knew about the first call because a hacker told me he had made the call himself. At 4:33 p.m., according to Apple’s tech support records, someone called AppleCare claiming to be me. Apple says the caller reported that he couldn't get into his Me.com e-mail – which, of course was my Me.com e-mail. In response, Apple issued a temporary password. It did this despite the caller’s inability to answer security questions I had set up. And it did this after the hacker supplied only two pieces of information that anyone with an internet connection and a phone can discover. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft At 4:50 p.m., a password reset confirmation arrived in my inbox. I don’t really use my me.com e-mail, and rarely check it. But even if I did, I might not have noticed the message because the hackers immediately sent it to the trash. They then were able to follow the link in that e-mail to permanently reset my AppleID password. At 4:52 p.m., a Gmail password recovery e-mail arrived in my me.com mailbox. Two minutes later, another e-mail arrived notifying me that my Google account password had changed. At 5:02 p.m., they reset my Twitter password. At 5:00 they used iCloud’s “Find My” tool to remotely wipe my iPhone. At 5:01 they remotely wiped my iPad. At 5:05 they remotely wiped my MacBook. Around this same time, they deleted my Google account. At 5:10, I placed the call to AppleCare. At 5:12 the attackers posted a message to my account on Twitter taking credit for the hack. By wiping my MacBook and deleting my Google account, they now not only had the ability to control my account, but were able to prevent me from regaining access. And crazily, in ways that I don’t and never will understand, those deletions were just collateral damage. My MacBook data – including those irreplaceable pictures of my family, of my child’s first year and relatives who have now passed from this life – weren’t the target. Nor were the eight years of messages in my Gmail account. The target was always Twitter. My MacBook data was torched simply to prevent me from getting back in. Lulz. I spent an hour and a half talking to AppleCare. One of the reasons it took me so long to get anything resolved with Apple during my initial phone call was because I couldn't answer the security questions it had on file for me. It turned out there’s a good reason for that. Perhaps an hour or so into the call, the Apple representative on the line said “Mr. Herman, I....” “Wait. What did you call me?” “Mr. Herman?” “My name is Honan.” Apple had been looking at the wrong account all along. Because of that, I couldn’t answer my security questions. And because of that, it asked me an alternate set of questions that it said would let tech support let me into my me.com account: a billing address and the last four digits of my credit card. (Of course, when I gave them those, it was no use, because tech support had misheard my last name.) Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft It turns out, a billing address and the last four digits of a credit card number are the only two pieces of information anyone needs to get into your iCloud account. Once supplied, Apple will issue a temporary password, and that password grants access to iCloud. Apple tech support confirmed to me twice over the weekend that all you need to access someone’s AppleID is the associated e-mail address, a credit card number, the billing address, and the last four digits of a credit card on file. I was very clear about this. During my second tech support call to AppleCare, the representative confirmed this to me. “That’s really all you have to have to verify something with us,” he said. We talked to Apple directly about its security policy, and company spokesperson Natalie Kerris told Wired, "Apple takes customer privacy seriously and requires multiple forms of verification before resetting an Apple ID password. In this particular case, the customer's data was compromised by a person who had acquired personal information about the customer. In addition, we found that our own internal policies were not followed completely. We are reviewing all of our processes for resetting account passwords to ensure our customers' data is protected." On Monday, Wired tried to verify the hackers' access technique by performing it on a different account. We were successful. This means, ultimately, all you need in addition to someone’s e-mail address are those two easily acquired pieces of information: a billing address and the last four digits of a credit card on file. Here’s the story of how the hackers got them. By exploiting the customer service procedures employed by Apple and Amazon, hackers were able to get into iCloud and take over all of Mat Honan's digital devices – and data. Photo: Ariel Zambelich/Wired Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft On the night of the hack, I tried to make sense of the ruin that was my digital life. My Google account was nuked, my Twitter account was suspended, my phone was in a useless state of restore, and (for obvious reasons) I was highly paranoid about using my Apple email account for communication. I decided to set up a new Twitter account until my old one could be restored, just to let people know what was happening. I logged into Tumblr and posted an account of how I thought the takedown occurred. At this point, I was assuming that my seven-digit alphanumeric AppleID password had been hacked by brute force. In the comments ( and, oh, the comments ) others guessed that hackers had used some sort of keystroke logger. At the end of the post, I linked to my new Twitter account. And then, one of my hackers @ messaged me. He would later identify himself as Phobia. I followed him. He followed me back. We started a dialogue via Twitter direct messaging that later continued via e-mail and AIM. Phobia was able to reveal enough detail about the hack and my compromised accounts that it became clear he was, at the very least, a party to how it went down. I agreed not to press charges, and in return he laid out exactly how the hack worked. But first, he wanted to clear something up: “didnt guess ur password or use bruteforce. i have my own guide on how to secure emails.” I asked him why. Was I targeted specifically? Was this just to get to Gizmodo’s Twitter account ? No, Phobia said they hadn’t even been aware that my account was linked to Gizmodo’s, that the Gizmodo linkage was just gravy. He said the hack was simply a grab for my three-character Twitter handle. That’s all they wanted. They just wanted to take it, and fuck shit up, and watch it burn. It wasn’t personal. “I honestly didn’t have any heat towards you before this. i just liked your username like I said before” he told me via Twitter Direct Message. After coming across my account, the hackers did some background research. My Twitter account linked to my personal website, where they found my Gmail address. Guessing that this was also the e-mail address I used for Twitter, Phobia went to Google’s account recovery page. He didn’t even have to actually attempt a recovery. This was just a recon mission. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Because I didn’t have Google's two-factor authentication turned on, when Phobia entered my Gmail address, he could view the alternate e-mail I had set up for account recovery. Google partially obscures that information, starring out many characters, but there were enough characters available, m••••[email protected]. Jackpot. This was how the hack progressed. If I had some other account aside from an Apple e-mail address, or had used two-factor authentication for Gmail, everything would have stopped here. But using that Apple-run me.com e-mail account as a backup meant told the hacker I had an AppleID account, which meant I was vulnerable to being hacked. Be careful with your Amazon account – or someone might buy merchandise on your credit card, but send it to their home. Photo: luxuryluke /Flickr “You honestly can get into any email associated with apple,” Phobia claimed in an e-mail. And while it's work, that seems to be largely true. Since he already had the e-mail, all he needed was my billing address and the last four digits of my credit card number to have Apple's tech support issue him the keys to my account. So how did he get this vital information? He began with the easy one. He got the billing address by doing a whois search on my personal web domain. If someone doesn’t have a domain, you can also look up his or her information on Spokeo, WhitePages, and PeopleSmart. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Getting a credit card number is tricker, but it also relies on taking advantage of a company’s back-end systems. Phobia says that a partner performed this part of the hack, but described the technique to us, which we were able to verify via our own tech support phone calls. It’s remarkably easy – so easy that Wired was able to duplicate the exploit twice in minutes. First you call Amazon and tell them you are the account holder, and want to add a credit card number to the account. All you need is the name on the account, an associated e-mail address, and the billing address. Amazon then allows you to input a new credit card. (Wired used a bogus credit card number from a website that generates fake card numbers that conform with the industry's published self-check algorithm.) Then you hang up. Next you call back, and tell Amazon that you've lost access to your account. Upon providing a name, billing address, and the new credit card number you gave the company on the prior call, Amazon will allow you to add a new e-mail address to the account. From here, you go to the Amazon website, and send a password reset to the new e-mail account. This allows you to see all the credit cards on file for the account – not the complete numbers, just the last four digits. But, as we know, Apple only needs those last four digits. We asked Amazon to comment on its security policy, but didn't have anything to share by press time. And it’s also worth noting that one wouldn't have to call Amazon to pull this off. Your pizza guy could do the same thing, for example. If you have an AppleID, every time you call Pizza Hut, you’ve giving the 16-year-old on the other end of the line all he needs to take over your entire digital life. And so, with my name, address, and the last four digits of my credit card number in hand, Phobia called AppleCare, and my digital life was laid waste. Yet still I was actually quite fortunate. They could have used my e-mail accounts to gain access to my online banking, or financial services. They could have used them to contact other people, and socially engineer them as well. As Ed Bott pointed out on TWiT.tv, my years as a technology journalist have put some very influential people in my address book. They could have been victimized too. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft Instead, the hackers just wanted to embarrass me, have some fun at my expense, and enrage my followers on Twitter by trolling. I had done some pretty stupid things. Things you shouldn’t do. I should have been regularly backing up my MacBook. Because I wasn’t doing that, if all the photos from the first year and a half of my daughter’s life are ultimately lost, I will have only myself to blame. I shouldn't have daisy-chained two such vital accounts – my Google and my iCloud account – together. I shouldn't have used the same e-mail prefix across multiple accounts – [email protected], [email protected], and [email protected]. And I should have had a recovery address that's only used for recovery without being tied to core services. But, mostly, I shouldn’t have used Find My Mac. Find My iPhone has been a brilliant Apple service. If you lose your iPhone, or have it stolen, the service lets you see where it is on a map. The New York Times ’ David Pogue recovered his lost iPhone just last week thanks to the service. And so, when Apple introduced Find My Mac in the update to its Lion operating system last year, I added that to my iCloud options too. After all, as a reporter, often on the go, my laptop is my most important tool. But as a friend pointed out to me, while that service makes sense for phones (which are quite likely to be lost) it makes less sense for computers. You are almost certainly more likely to have your computer accessed remotely than physically. And even worse is the way Find My Mac is implemented. When you perform a remote hard drive wipe on Find my Mac, the system asks you to create a four-digit PIN so that the process can be reversed. But here’s the thing: If someone else performs that wipe – someone who gained access to your iCloud account through malicious means – there’s no way for you to enter that PIN. A better way to have this set up would be to require a second method of authentication when Find My Mac is initially set up. If this were the case, someone who was able to get into an iCloud account wouldn't be able to remotely wipe devices with malicious intent. It would also mean that you could potentially have a way to stop a remote wipe in progress. Gear Humanity’s Most Obnoxious Vehicle Gets an Electric (and Nearly Silent) Makeover Boone Ashworth Gear You’ll Be Able Buy Cars on Amazon Next Year Boone Ashworth Gear The Best Black Friday Deals on Electric Bikes and Accessories Adrienne So Gear The Best USB Hubs and Docks for Connecting All Your Gadgets Eric Ravenscraft But that’s not how it works. And Apple would not comment as to whether stronger authentification is being considered. As of Monday, both of these exploits used by the hackers were still functioning. Wired was able to duplicate them. Apple says its internal tech support processes weren't followed, and this is how my account was compromised. However, this contradicts what AppleCare told me twice that weekend. If that is, in fact, the case – that I was the victim of Apple not following its own internal processes – then the problem is widespread. I asked Phobia why he did this to me. His answer wasn’t satisfying. He says he likes to publicize security exploits, so companies will fix them. He says it's the same reason he told me how it was done. He claims his partner in the attack was the person who wiped my MacBook. Phobia expressed remorse for this, and says he would have stopped it had he known. “yea i really am a nice guy idk why i do some of the things i do,” he told me via AIM. “idk my goal is to get it out there to other people so eventually every1 can over come hackers” I asked specifically about the photos of my little girl, which are, to me, the greatest tragedy in all this. Unless I can recover those photos via data recovery services, they are gone forever. On AIM, I asked him if he was sorry for doing that. Phobia replied, “even though i wasnt the one that did it i feel sorry about that. Thats alot of memories im only 19 but if my parents lost and the footage of me and pics i would be beyond sad and im sure they would be too.” But let’s say he did know, and failed to stop it. Hell, for the sake of argument, let’s say he did it. Let’s say he pulled the trigger. The weird thing is, I’m not even especially angry at Phobia, or his partner in the attack. I’m mostly mad at myself. I’m mad as hell for not backing up my data. I’m sad, and shocked, and feel that I am ultimately to blame for that loss. But I’m also upset that this ecosystem that I've placed so much of my trust in has let me down so thoroughly. I'm angry that Amazon makes it so remarkably easy to allow someone into your account, which has obvious financial consequences. And then there's Apple. I bought into the Apple account system originally to buy songs at 99 cents a pop, and over the years that same ID has evolved into a single point of entry that controls my phones, tablets, computers and data-driven life. With this AppleID, someone can make thousands of dollars of purchases in an instant, or do damage at a cost that you can't put a price on. Additional reporting by Roberto Baldwin and Christina Bonnington. Portions of this story originally appeared on Mat Honan’s Tumblr. Continued: How I Resurrected My Digital Life After an Epic Hacking. 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"BLOOM: Inside the radical new project to democratize AI | MIT Technology Review"

"https://www.technologyreview.com/2022/07/12/1055817/inside-a-radical-new-project-to-democratize-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Inside a radical new project to democratize AI A group of over 1,000 AI researchers has created a multilingual large language model bigger than GPT-3—and they’re giving it out for free. By Melissa Heikkilä archive page Ms Tech | Envato, Unsplash PARIS — This is as close as you can get to a rock concert in AI research. Inside the supercomputing center of the French National Center for Scientific Research, on the outskirts of Paris, rows and rows of what look like black fridges hum at a deafening 100 decibels. They form part of a supercomputer that has spent 117 days gestating a new large language model (LLM) called BLOOM that its creators hope represents a radical departure from the way AI is usually developed. Unlike other, more famous large language models such as OpenAI’s GPT-3 and Google’s LaMDA, BLOOM (which stands for BigScience Large Open-science Open-access Multilingual Language Model) is designed to be as transparent as possible, with researchers sharing details about the data it was trained on, the challenges in its development, and the way they evaluated its performance. OpenAI and Google have not shared their code or made their models available to the public, and external researchers have very little understanding of how these models are trained. BLOOM was created over the last year by over 1,000 volunteer researchers in a project called BigScience, which was coordinated by AI startup Hugging Face using funding from the French government. It officially launched on July 12. The researchers hope developing an open-access LLM that performs as well as other leading models will lead to long-lasting changes in the culture of AI development and help democratize access to cutting-edge AI technology for researchers around the world. The model’s ease of access is its biggest selling point. Now that it’s live, anyone can download it and tinker with it free of charge on Hugging Face’s website. Users can pick from a selection of languages and then type in requests for BLOOM to do tasks like writing recipes or poems, translating or summarizing texts, or writing programming code. AI developers can use the model as a foundation to build their own applications. At 176 billion parameters (variables that determine how input data is transformed into the desired output), it is bigger than OpenAI’s 175-billion-parameter GPT-3, and BigScience claims that it offers similar levels of accuracy and toxicity as other models of the same size. For languages such as Spanish and Arabic, BLOOM is the first large language model of this size. But even the model’s creators warn it won’t fix the deeply entrenched problems around large language models, including the lack of adequate policies on data governance and privacy and the algorithms’ tendency to spew toxic content, such as racist or sexist language. Out in the open Large language models are deep-learning algorithms that are trained on massive amounts of data. They are one of the hottest areas of AI research. Powerful models such as GPT-3 and LaMDA, which produce text that reads as if a human wrote it, have huge potential to change the way we process information online. They can be used as chatbots or to search for information, moderate online content, summarize books, or generate entirely new passages of text based on prompts. But they are also riddled with problems. It takes only a little prodding before these models start producing harmful content. The models are also extremely exclusive. They need to be trained on massive amounts of data using lots of expensive computing power, which is something only large (and mostly American) technology companies such as Google can afford. Most big tech companies developing cutting-edge LLMs restrict their use by outsiders and have not released information about the inner workings of their models. This makes it hard to hold them accountable. The secrecy and exclusivity are what the researchers working on BLOOM hope to change. Meta has already taken steps away from the status quo: in May 2022 the company released its own large language model, Open Pretrained Transformer (OPT-175B), along with its code and a logbook detailing how the model was trained. Related Story Hundreds of scientists around the world are working together to understand one of the most powerful emerging technologies before it’s too late. But Meta’s model is available only upon request, and it has a license that limits its use to research purposes. Hugging Face goes a step further. The meetings detailing its work over the past year are recorded and uploaded online, and anyone can download the model free of charge and use it for research or to build commercial applications. A big focus for BigScience was to embed ethical considerations into the model from its inception, instead of treating them as an afterthought. LLMs are trained on tons of data collected by scraping the internet. This can be problematic, because these data sets include lots of personal information and often reflect dangerous biases. The group developed data governance structures specifically for LLMs that should make it clearer what data is being used and who it belongs to, and it sourced different data sets from around the world that weren’t readily available online. The group is also launching a new Responsible AI License , which is something like a terms-of-service agreement. It is designed to act as a deterrent from using BLOOM in high-risk sectors such as law enforcement or health care, or to harm, deceive, exploit, or impersonate people. The license is an experiment in self-regulating LLMs before laws catch up, says Danish Contractor, an AI researcher who volunteered on the project and co-created the license. But ultimately, there’s nothing stopping anyone from abusing BLOOM. The project had its own ethical guidelines in place from the very beginning, which worked as guiding principles for the model’s development, says Giada Pistilli, Hugging Face’s ethicist, who drafted BLOOM’s ethical charter. For example, it made a point of recruiting volunteers from diverse backgrounds and locations, ensuring that outsiders can easily reproduce the project’s findings, and releasing its results in the open. All aboard This philosophy translates into one major difference between BLOOM and other LLMs available today: the vast number of human languages the model can understand. It can handle 46 of them, including French, Vietnamese, Mandarin, Indonesian, Catalan, 13 Indic languages (such as Hindi), and 20 African languages. Just over 30% of its training data was in English. The model also understands 13 programming languages. This is highly unusual in the world of large language models, where English dominates. That’s another consequence of the fact that LLMs are built by scraping data off the internet: English is the most commonly used language online. The reason BLOOM was able to improve on this situation is that the team rallied volunteers from around the world to build suitable data sets in other languages even if those languages weren’t as well represented online. For example, Hugging Face organized workshops with African AI researchers to try to find data sets such as records from local authorities or universities that could be used to train the model on African languages, says Chris Emezue, a Hugging Face intern and a researcher at Masakhane, an organization working on natural-language processing for African languages. Including so many different languages could be a huge help to AI researchers in poorer countries, who often struggle to get access to natural-language processing because it uses a lot of expensive computing power. BLOOM allows them to skip the expensive part of developing and training the models in order to focus on building applications and fine-tuning the models for tasks in their native languages. “If you want to include African languages in the future of [natural-language processing] … it’s a very good and important step to include them while training language models,” says Emezue. Handle with caution BigScience has done a “phenomenal” job of building a community around BLOOM, and its approach of involving ethics and governance from the beginning is a thoughtful one, says Percy Liang, director of Stanford's Center for Research on Foundation Models. However, Liang doesn’t think it will lead to significant changes to LLM development. “OpenAI and Google and Microsoft are still blazing ahead,” he says. Ultimately, BLOOM is still a large language model, and it still comes with all the associated flaws and risks. Companies such as OpenAI have not released their models or code to the public because, they argue, the sexist and racist language that has gone into them makes them too dangerous to use that way. BLOOM is also likely to incorporate inaccuracies and biased language, but since everything about the model is out in the open, people will be able to interrogate the model’s strengths and weaknesses, says Margaret Mitchell, an AI researcher and ethicist at Hugging Face. BigScience’s biggest contribution to AI might end up being not BLOOM itself, but the numerous spinoff research projects its volunteers are getting involved in. For example, such projects could bolster the model’s privacy credentials and come up with ways to use the technology in different fields, such as biomedical research. “One new large language model is not going to change the course of history,” says Teven Le Scao, a researcher at Hugging Face who co-led BLOOM's training. “But having one good open language model that people can actually do research on has a strong long-term impact.” When it comes to the potential harms of LLMs, “ Pandora's box is already wide open,” says Le Scao. “The best you can do is to create the best conditions possible for researchers to study them.” hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Can $100 billion save a struggling Rust Belt city | MIT Technology Review"

"https://www.technologyreview.com/2023/07/06/1075817/micron-syracuse-chips-economic-development-technology"

"Featured Topics Newsletters Events Podcasts The $100 billion bet that a postindustrial US city can reinvent itself as a high-tech hub Can a massive infusion of money for making computer chips transform the economy of Syracuse and show us how to rebuild the nation’s industrial base? Kate Warren by David Rotman archive page For now, the thousand acres that may well portend a more prosperous future for Syracuse, New York, and the surrounding towns are just a nondescript expanse of scrub, overgrown grass, and trees. But on a day in late April, a small drilling rig sits at the edge of the fields, taking soil samples. It’s the first sign of construction on what could become the largest semiconductor manufacturing facility in the United States. Spring has finally come to upstate New York after a long, gray winter. A small tent is set up. A gaggle of local politicians mill around, including the county executive and the supervisor of the town of Clay, some 15 miles north of Syracuse, where the site is located. There are a couple of local news reporters. If you look closely, the large power lines that help make this land so valuable are visible just beyond a line of trees. Then an oversize black SUV with the suits drives up, and out steps $100 billion. The CHIPS and Science Act, passed last year with bipartisan congressional support, was widely viewed by industry leaders and politicians as a way to secure supply chains, bolster R&D spending, and make the United States competitive again in semiconductor chip manufacturing. But it also intends, at least according to the Biden administration, to create good jobs and, ultimately, widen economic prosperity. Now Syracuse is about to become an economic test of whether, over the next several decades, the aggressive government policies—and the massive corporate investments they spur—can both boost the country’s manufacturing prowess and revitalize regions like upstate New York. It all begins with an astonishingly expensive and complex kind of factory called a chip fab. Micron, a maker of memory chips based in Boise, Idaho, announced last fall that it plans to build up to four of these fabs, each costing roughly $25 billion, at the Clay site over the next 20 years. And on this April day, standing under the tent, CEO Sanjay Mehrotra conjures a vision for what the $100 billion investment will mean: “Imagine this site, which has nothing on it today, will have four major buildings 20 years from now. And each of these buildings will be the size of 10 football fields, so a total of 40 football fields worth of clean-room space.” The fabs will create 50,000 jobs in the region over time, including 9,000 at Micron, he has pledged—“so this is really going to be a major transformation for the community.” For any city, a $100 billion corporate investment is a big deal, but for Syracuse, it promises a reversal of fortune. Sitting at the northeast corner of the Rust Belt, Syracuse has been losing jobs and people for decades as its core manufacturing facilities shut down—first GE and more recently Carrier, which once employed some 7,000 workers at its East Syracuse plant. According to Census data, Syracuse now has the highest child poverty rate among large US cities; it has the second-highest rate of families living on less than $10,000 a year. Syracuse, of course, is not alone in its postindustrial malaise. The nation’s economy is increasingly driven by high-tech industries, and those jobs and the resulting wealth are largely concentrated in a few cities; Boston, San Francisco, San Jose, Seattle, and San Diego accounted for more than 90% of US innovation-sector growth from 2005 to 2017, according to a report by the Brookings Institution. Without these high-tech jobs and with conventional manufacturing long gone as an economic driver, Rust Belt cities like Detroit, Cleveland, Syracuse, and nearby Rochester now top the list of the country’s poorest cities. The Micron investment will flood billions into the local economy, making it possible to finally upgrade the infrastructure, housing, and schools. It will also, if all goes according to plan, anchor a new semiconductor manufacturing hub in central New York at a time when the demand for chips, especially the type of memory chips that Micron plans to make in Clay, is expected to explode given the essential role they play in artificial intelligence and other data-driven applications. It is, in short, an attempt to turn around a region that has struggled economically for decades. And the project’s success or failure will be an important indicator of whether the US can leverage investments in high tech to reverse years of soaring geographic inequality and all the social and political unrest that it has brewed. Billions for fabs In many ways, the Micron investment is an on-the-ground trial for the recent US embrace of industrial policy —government interventions that favor particular sectors and regions of the country. Over the last two years, the US government has allocated hundreds of billions to supporting everything from new chip fabs to a slew of battery manufacturing plants throughout the country. Micron, for one, says it would not be building in the US without the funding it expects from the CHIPS and Science Act, which designated $39 billion for support of domestic semiconductor manufacturing and another $13.2 billion for semiconductor R&D and workforce development. Related Story Three bills investing hundreds of billions into technological development could change the way we think about government’s role in growing prosperity. While semiconductors were invented in the US, these days it fabricates only about 12% of the global supply; Taiwan and South Korea dominate the market. For DRAM (dynamic random-access memory) chips, the kind that Micron plans to build in Syracuse, the state of domestic manufacturing is particularly bad. Fewer than 2% of DRAM chips are made in the US. Even US-headquartered Micron, which is one of three companies that control the DRAM market, makes most of its chips in Taiwan, Japan, and Singapore. It costs roughly 40% more to make chips in the US than in Asia, owing to differences in construction and labor costs and government incentives. The money in the CHIPS Act is meant to make it financially attractive to build fabs in the US once again. Some of that money is going to places where chip manufacturing is well established: Taiwan Semiconductor Manufacturing Company (TSMC) is investing $40 billion in new fabs in Phoenix, Arizona, and Intel is building fabs in nearby Chandler. But other projects, including a $20 billion pair Intel is building near Columbus, Ohio and Micron’s project in Syracuse, will break ground on new locations for chip manufacturing, potentially creating centers of economic activity around the large investments. The intention of the CHIPS Act, says Mark Muro, a senior fellow at Brookings, is not just to support building “a big box” to make semiconductors but to help create regional economic clusters around the investments. After years of growing inequality between different parts of the country, he says, this strategy reflects a renewed emphasis on so-called placed-based economic policies to support the local development of high-tech manufacturing. Predictably, states are aggressively competing for the investments; New York attracted Micron with a staggering $5.8 billion in economic development incentives. But the billions of dollars flowing into Syracuse come with uncertainty. Will this lead to sustainable economic transformation? Or will the massive amounts of money simply provide a temporary burst of growth and jobs for some, leaving many in the community behind and causing a severe case of buyer’s remorse for the city and state? The incentives that were offered to lure Micron represent “a wild, wild amount of money,” says Nathan Jensen, a professor of government at the University of Texas in Austin. While the Micron investment will likely bring good jobs and could be a great opportunity for a distressed city, he says, local and state leaders will need to manage multiple risks over the long term. Corporate strategies can change, and 20 years is a long time to bet on growing market demand for a specific technology. What’s more, says Jensen, by offering generous tax breaks to companies, state and local communities can limit their sources of revenues in the coming decades, even as—if all goes well—they deal with booming demand for housing, roads, and schools. He calls it the “winner’s curse.” The challenge for Syracuse is that there are no “hard-and-fast recipes” for how to get it right, says Maryann Feldman, a professor of public policy at Arizona State University. “We think like we have an economic development sausage machine,” she says. “You line up a bunch of factors and, voilà, you have a productive and growing economy. It’s much more difficult than that.” Risky business When Ryan McMahon became county executive­­ of Onondaga County, in 2018, the long-imagined industrial park in Clay was languishing. Previous county executives had promoted it as the perfect location for a semiconductor fab. But for two decades there had been no takers. McMahon decided to go all in, pouring millions into expanding and upgrading the site. His timing couldn’t have been better. Even before the CHIPS Act was passed last summer, semiconductor manufacturers had begun scouting sites in the US to expand. TSMC and Intel both sniffed around Clay, says McMahon, before choosing other sites. Preliminary talks began with Micron, but it all depended on whether the act got passed. Once that happened, the Micron deal was done. In late October, President Biden went to Syracuse to celebrate what he called “one of the most significant investments in American history.” The business of memory chips, such as the DRAM chips that Micron will make in Clay, is a notoriously competitive one with very low margins. Like their more glamorous cousins, the logic chips made by Intel and TSMC, they are immensely complex and expensive to make: the process involves cramming billions of transistors onto each thumb-size chip with a precision of a few atoms. To survive, companies have to run their fabs continuously, with remarkable efficiency and yields. The technical and market demands make finding a suitable site difficult. Micron says it chose the site in Clay because of its size, access to clean power, and abundance of water (by some estimates, large chip fabs use up to 10 million gallons a day). The transmission lines running through it draw power from a huge hydroelectric plant at Niagara Falls and nuclear plants on Lake Ontario. And the lake, with its nearly endless supply of water, is less than 30 miles away. The Micron investment, including the $250 million the company has committed to a community fund, could help the city repair its crumbling infrastructure. “There are very few sites, frankly, in the country that were ready on our timeline,” says Manish Bhatia, Micron’s executive vice president of global operations. Bhatia also points to the area’s manufacturing legacy, which despite being “hollowed out over the last 20 years” has left a “tremendous pool of engineering talent.” Throw in the generous incentives from the state and the company was sold, he says. Micron’s ambitious expansion plans for the next few decades are fueled in part by anticipated demand from artificial intelligence, as well as increased use of memory in automotive applications and data centers. “AI is all about memory,” says Bhatia. “It needs larger and larger data sets to be able to glean the insights.” And more data means more memory. Construction of the first fab is scheduled to begin in 2024, but it won’t be expected to come fully online until the latter half of the decade. Further expansion is planned but will depend on the demand for the memory chips. Another fab could begin operations by the mid-2030s; after that, two more fabs are on the table, if the market allows. Micron projects that it will eventually hire 9,000 people to work at the fabs, with roughly 3,000 of those jobs needed for its initial build-out. And it says as many as 41,000 additional jobs will be created in other businesses, from companies supplying the fabs with materials and maintenance to restaurants meeting the needs of the growing workforce. The fabs will require workers with a wide range of skill sets, from electrical engineers to a roughly equal number of technicians without college degrees but with specialized training. That means large investments in the area’s vocational schools, community colleges, and universities. In response to the Micron investment, Syracuse University plans to expand funding for its College of Engineering and Computer Science by 50% over the next five years or so. While some graduates will surely go to work at Micron, the goal is more broadly to train people with a wide range of skills and expertise, from materials science to automation, in hopes that the investment in the fabs will seed a booming local high-tech community. “This is a fascinating natural experiment,” says Mike Haynie, vice chancellor for strategic initiatives and innovation at Syracuse University. “Industry left here largely 25 years ago, and the economy, to a large extent, has been sustained by health care and colleges—it’s essentially what’s driven the economy.” Now, says Haynie, “all of a sudden you insert this $100 billion high-tech investment into the regional economy and see what happens.” Until now, he says, “we have not been able to authentically look an engineering or computer science student in the face and say, ‘There’s a reason for you to stay in central New York.’” Going bad If Syracuse and the surrounding towns want a lesson on how not to do economic development, they just need to drive 150 miles down the thruway to Buffalo. In 2012, Governor Andrew Cuomo announced the Buffalo Billion, an ambitious redevelopment initiative intended to revive the distressed city. The star project in the Buffalo Billion was an effort to create a clean-tech hub by spending $750 million to build and equip a massive manufacturing facility for SolarCity, a Silicon Valley–based company that financed and installed solar panels. SolarCity promised it would produce a gigawatt of solar panels by 2017, creating 3,000 jobs in the city, including 1,500 manufacturing jobs at the plant. The so-called gigafactory would be the largest solar panel manufacturer in the Western Hemisphere , the company boasted. In the late spring of 2015, I visited SolarCity’s plant as it was being built at the so-called Riverbend site, once the location of a sprawling plant operated by Republic Steel. Less than four miles away from the city’s revitalized downtown waterfront, it seemed like the perfect place to center a new manufacturing economy for Buffalo. “The Buffalo Billion has been a failure with a capital F.” The following years turned out to be pretty much a bust for the solar gigafactory. With SolarCity several billion dollars in debt, Tesla Motors bought the company. Amid much fanfare, Elon Musk, its CEO, announced it would make solar roof tiles—a product others had tried but that had never really caught on. They turned out to be more or less a market flop. Panasonic, which Tesla had originally brought into the plant to help make solar cells at the facility, pulled out in 2020. Today, Tesla does in fact employs some 1,500 people at the facility, but many don’t work in solar manufacturing, according to local media reports. Rather, many of the jobs involve assembling charging stations for Tesla’s cars and annotating traffic scenes to help train the autonomous features in its vehicles. Without the anticipated boom in solar panel production—the promise of being the largest solar manufacturer in the US is long forgotten—there are few new jobs for suppliers and other companies that expected to support a growing center of manufacturing. “The Buffalo Billion has been a failure with a capital F,” says Jim Heaney, editor of the Investigative Post in Buffalo, who has followed the state initiative from its outset. The booming tech hub that the Buffalo Billion was explicitly chartered to create never materialized. Heaney points out that the only apparent spinoff from the investments at the Riverbend site is the Tim Hortons doughnut shop across the street. In many ways, the plans for the Buffalo Billion violated Economic Development 101. For one thing, SolarCity, which was meant to be the clean-tech manufacturing anchor, was a company that installed residential solar panels; it had little experience in large-scale manufacturing. There were broader questions about the state investment. Why build in Buffalo, which has no apparent supply chain for the technology and little local demand for it? (It’s one of the cloudiest cities in the country.) Where was the workforce with the skills to produce solar panels going to come from? The key lesson of the Buffalo Billion is not that the solar gigafactory was a waste of taxpayer money, though it probably was, but that government-funded economic policy needs to be done in a way that respects a region’s resources and talents. Richard Deitz, an economist at the Federal Reserve Bank of New York who is based in Buffalo, contrasts the strategy with the investments the state had previously made in Albany. There, the money went into a nanotech research center and to support an existing semiconductor industry; it created partnerships between businesses, higher education, and the state and local governments. The investments strengthened an existing cluster of expertise around those resources. “These were very different approaches, and I’d say the one in Buffalo did not work very well,” he says. Will the Micron investment change the economic trajectory of upstate New York? It’s the right question, says Deitz, “but I don’t think anybody can tell you the answer.” However, he says he’s encouraged by what’s happened in Albany over the past 10 years. “You get a picture of what’s possible,” he says. From 2010 to 2020, Albany added some 4,000 jobs, while Buffalo lost some 25,000, according to Deitz: “It’s not like [Albany is] growing like gangbusters, but it’s doing quite well and it’s reinventing itself.” Winning the lottery The initial injection of money from Micron will inevitably create high-tech jobs and will have what economists like to call a “multiplier effect” as those workers spend their generous salaries at local businesses. But the real, sustainable payoff, says Enrico Moretti, an economist at the University of California, Berkeley, will come if the fabs trigger the creation of a cluster of companies that result in a flourishing of new innovation activities and brings long-term high-tech growth beyond Micron. Ten years ago, Moretti wrote a book called The New Geography of Jobs showing how the rise of such so-called innovation clusters in a few areas of the US, mostly along the coasts, has led to deep economic inequalities. (Those disparities, Moretti now says, have only gotten worse and more troubling since he wrote the book.) “Innovative industries bring ‘good jobs’ and high salaries to communities,” he wrote. They deliver a far stronger multiplier effect than other employers, even those in manufacturing. But communities without innovation clusters, he wrote, “find it hard to create one” and fall further and further behind. The trick for Syracuse is not to try to be another Silicon Valley (a well-known list of others have failed at that fool’s errand) or even another Austin, but to use its resources and skills to define its own unique brand of innovation. Think Albany but on a far grander scale. To demonstrate how important these high-tech clusters are to productivity growth, Moretti recently showed what happened to innovation in Rochester after the fortunes of Kodak began to decline in the late 1960s. The company had helped make Rochester one of the country’s wealthiest cities during the 20th century—but then came the invention of digital photography. Kodak’s business, which by then centered on selling film rather than making cameras, collapsed. As Moretti documented, the damage to the city was not just the loss of Kodak jobs, but a parallel collapse of its ability to invent new technologies. He found that even non-Kodak inventors, who had nothing to do with the photography business, also became far less productive—as measured by number of patents—after Kodak’s decline. The benefits of a flourishing community of innovators interacting with each other, as well as the legal and financial services that facilitate startups and entrepreneurs, had seemingly left town with Kodak. Now Syracuse wants to run what happened to Rochester in reverse, hoping a large corporate presence will kick-start its own innovation cluster around semiconductors. “Syracuse has won the economic development lottery,” says Dan Breznitz, a professor of innovation studies at the University of Toronto. Besides the size of the investment, Micron has a long-term track record in chip manufacturing and commitment to building its own production capacity. But, Breznitz suggests, the community now needs a pragmatic vision for what the region and its economy will look like in 15 to 20 years, aside from the Micron fabs. Having won the lottery, he says, the community and local businesses can say either “We don’t need to worry anymore” or “This is our moment to create a local vision of how we can become an important location for the global semiconductor industry or related industries.” Shared prosperity? When I spoke to Kevin Younis in late April, he appeared to be fully aware that he and Syracuse had won the lottery. As chief operating officer of Empire State Development, the agency responsible for promoting economic growth, Younis had helped lead the effort to recruit Micron. Now, sitting outside on the patio of a bustling downtown food market that he had chosen for the meeting, he basked in the recent revival of the city and its potential prospects. Younis grew up a mile away, and he says the city has slowly been rebounding in recent years. “When I was a kid in the ’80s and for sure in the ’90s, the downtown was emptying out. I would come down with friends to go to the comic-book store, and we’d be the only people down here,” he says. Now, on a late Thursday afternoon, the market, which has kiosks serving food from all over the world, is busy with young families, businesspeople, and 20-somethings grabbing a beer after work. New homes for sale. Hopes are high that the Micron facility will help the local real estate market take off. But it’s that lottery ticket that Younis knows could change everything, helping a city that has been crawling its way back to reach or exceed its old success. Beyond the $100 billion to build the fabs, there is another $70 billion in operational costs, meaning $170 billion that will be spent in central New York over the next 20 years. “It is something like a $15-billion-a-year GDP impact in central New York on average over the next 30 years,” says Younis. (The GDP of the Syracuse metro area is roughly $42 billion now, according to the Federal Reserve Bank of New York. ) And that, he says, is probably a conservative estimate. Younis, however, is definitely not the type of person who wins the lottery and sits around without any worries. “A lot of things keep me up at night,” he admits. Housing. Infrastructure. “Nobody has ever done anything like this at this scale,” he says. The state is trying to be strategic, he says, pointing to the plan announced earlier this year to open its first Office of Semiconductor Expansion, Management, and Integration. And when he talks about the existing expertise in the region around smart sensors, drones, and automation, one can see the clear threads of the type of strategic vision that the University of Toronto’s Breznitz talks about. “A lot of things keep me up at night. Nobody has ever done anything like this at this scale.” But there is another challenge on Younis’s mind these days, one that feels very personal. It goes back to growing up as one of 12 children in a working-class Syracuse family. “Central New York has among the most entrenched poverty in the nation. Having grown up in that poverty and having an opportunity to change that is a generational opportunity,” he says. Poverty is all around, he says: “It’s where we’re at—it’s right here. It’s where I grew up. These are among the poorest Census tracts in the nation. Imagine living and raising a family on less than $10,000 a year. That’s insane! That’s what keeps me up at night, where I would feel like I failed if we don’t do something about that.” Perhaps the ultimate test of the Syracuse experiment will be whether, in addition to boosting the opportunities in the largely middle-class suburbs around Clay, the Micron investment also lifts up those living in poverty in the downtown Syracuse neighborhoods that Younis talks about. Can the inevitable economic growth benefit a broad swath of the community? Or will it exacerbate inequality? The results in other booming innovation clusters are not particularly encouraging. Can Syracuse be different? Robert Simpson, president of the CenterState Corporation for Economic Opportunity and a close collaborator with Younis in recruiting Micron, puts the challenge this way: “Economic growth is no guarantee of a greater measure of shared prosperity. You can grow without improving the quality of life for a lot of people in the region. However, economic growth is a necessary precondition for a greater level of shared prosperity. You need growth—otherwise you’re just redistributing income and wealth from one place to the next. And that gets people understandably upset and nervous.” The massive Micron investment, says Simpson, “gives us a chance to do something we have wanted to do for a long time, but we didn’t have the tools to do: bridge the socioeconomic divides that have held our region back.” It’s a lofty goal that will no doubt be challenged over the coming years. There will be inevitable fights over housing and where and how to invest the hundreds of millions earmarked for community development. There will certainly continue to be skeptics, especially given the state’s hugely generous incentives and the number of years it will take to get the fabs fully up and running. Transforming a city and its economy is not easy work. It comes with enormous risks. But in many ways, Syracuse has no choice. The great experiment unfolding there is one that the city—indeed, the country—badly needs to succeed. by David Rotman Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Social media is polluting society. Moderation alone won’t fix the problem | MIT Technology Review"

"https://www.technologyreview.com/2022/08/09/1057171/social-media-polluting-society-moderation-alone-wont-fix-the-problem"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Social media is polluting society. Moderation alone won’t fix the problem Companies already have the systems in place that are needed to evaluate their deeper impacts on the social fabric. By Nathaniel Lubin archive page Thomas Krendl Gilbert archive page Ms Tech | Getty We all want to be able to speak our minds online—to be heard by our friends and talk (back) to our opponents. At the same time, we don’t want to be exposed to speech that is inappropriate or crosses a line. Technology companies address this conundrum by setting standards for free speech, a practice protected under federal law. They hire in-house moderators to examine individual pieces of content and remove them if posts violate predefined rules set by the platforms. The approach clearly has problems: harassment , misinformation about topics like public health, and false descriptions of legitimate elections run rampant. But even if content moderation were implemented perfectly, it would still miss a whole host of issues that are often portrayed as moderation problems but really are not. To address those non-speech issues, we need a new strategy: treat social media companies as potential polluters of the social fabric, and directly measure and mitigate the effects their choices have on human populations. That means establishing a policy framework—perhaps through something akin to an Environmental Protection Agency or Food and Drug Administration for social media—that can be used to identify and evaluate the societal harms generated by these platforms. If those harms persist, that group could be endowed with the ability to enforce those policies. But to transcend the limitations of content moderation, such regulation would have to be motivated by clear evidence and be able to have a demonstrable impact on the problems it purports to solve. Moderation (whether automated or human) can potentially work for what we call “acute” harms: those caused directly by individual pieces of content. But we need this new approach because there are also a host of “structural” problems —issues such as discrimination, reductions in mental health, and declining civic trust—that manifest in broad ways across the product rather than through any individual piece of content. A famous example of this kind of structural issue is Facebook’s 2012 “emotional contagion” experiment , which showed that users’ affect (their mood as measured by their behavior on the platform) shifted measurably depending on which version of the product they were exposed to. In the blowback that ensued after the results became public, Facebook (now Meta) ended this type of deliberate experimentation. But just because they stopped measuring such effects does not mean product decisions don’t continue to have them. Structural problems are direct outcomes of product choices. Product managers at technology companies like Facebook, YouTube, and TikTok are incentivized to focus overwhelmingly on maximizing time and engagement on the platforms. And experimentation is still very much alive there: almost every product change is deployed to small test audiences via randomized controlled trials. To assess progress, companies implement rigorous management processes to foster their central missions (known as Objectives and Key Results, or OKRs), even using these outcomes to determine bonuses and promotions. The responsibility for addressing the consequences of product decisions is often placed on other teams that are usually downstream and have less authority to address root causes. Those teams are generally capable of responding to acute harms—but often cannot address problems caused by the products themselves. With attention and focus, this same product development structure could be turned to the question of societal harms. Consider Frances Haugen’s congressional testimony last year, along with media revelations about Facebook’s alleged impact on the mental health of teens. Facebook responded to criticism by explaining that it had studied whether teens felt that the product had a negative effect on their mental health and whether that perception caused them to use the product less, and not whether the product actually had a detrimental effect. While the response may have addressed that particular controversy, it illustrated that a study aiming directly at the question of mental health—rather than its impact on user engagement—would not be a big stretch. Incorporating evaluations of systemic harm won’t be easy. We would have to sort out what we can actually measure rigorously and systematically, what we would require of companies, and what issues to prioritize in any such assessments. Companies could implement protocols themselves, but their financial interests too often run counter to meaningful limitations on product development and growth. That reality is a standard case for regulation that operates on behalf of the public. Whether through a new legal mandate from the Federal Trade Commission or harm mitigation guidelines from a new governmental agency, the regulator’s job would be to work with technology companies’ product development teams to design implementable protocols measurable during the course of product development to assess meaningful signals of harm. That approach may sound cumbersome, but adding these types of protocols should be straightforward for the largest companies (the only ones to which regulation should apply), because they have already built randomized controlled trials into their development process to measure their efficacy. The more time-consuming and complex part would be defining the standards; the actual execution of the testing would not require regulatory participation at all. It would only require asking diagnostic questions alongside normal growth-related questions and then making that data accessible to external reviewers. Our forthcoming paper at the 2022 ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization will explain this procedure in more detail and outline how it could effectively be established. When products that reach tens of millions are tested for their ability to boost engagement, companies would need to ensure that those products—at least in aggregate—also abide by a “don’t make the problem worse” principle. Over time, more aggressive standards could be established to roll back existing effects of already-approved products. There are many methods that might be suitable for this type of process. These include protocols like the photographic affect meter , which has been used diagnostically to assess how exposure to products and services affects mood. Technology platforms are already using surveys to assess product changes; according to reporters Cecilia Kang and Sheera Frankel, Mark Zuckerberg looks at survey-based growth metrics for most every product decision, the results of which were part of his choice to roll back the “nicer” version of Facebook’s news feed algorithm after the 2020 election. It would be reasonable to ask whether the technology industry sees this approach as feasible and whether companies would fight against it. While any potential regulation might engender such a response, we have received positive feedback from early conversations about this framework—perhaps because under our approach, most product decisions would pass muster. (Causing measureable harms of the sort described here is a very high bar, one that most product choices would clear.) And unlike other proposals, this strategy sidesteps direct regulation of speech, at least outside the most extreme cases. At the same time, we don’t have to wait for regulators to take action. Companies could readily implement these procedures on their own. Establishing the case for change, however, is difficult without first starting to collect the sort of high-quality data we’re describing here. That is because one cannot prove the existence of these types of harms without real-time measurement, creating a chicken-and-egg challenge. Proactively monitoring structural harms won’t resolve platforms’ content issues. But it could allow us to meaningfully and continuously verify whether the public interest is being subverted. The US Environmental Protection Agency is an apt analogy. The original purpose of the agency was not to legislate environmental policy, but to enact standards and protocols so that policies with actionable outcomes could be made. From that point of view, the EPA’s lasting impact was not to resolve environmental policy debates (it hasn’t), but to make them possible. Likewise, the first step for fixing social media is to create the infrastructure that we’ll need in order to examine outcomes in speech, mental well-being, and civic trust in real time. Without that, we will be prevented from addressing many of the most pressing problems these platforms create. Nathaniel Lubin is a fellow at the Digital Life Initiative at Cornell Tech and the former director of the Office of Digital Strategy at the White House under President Barack Obama. Thomas Krendl Gilbert is a postdoctoral fellow at Cornell Tech and received an interdisciplinary PhD in machine ethics and epistemology at UC Berkeley. hide by Nathaniel Lubin & Thomas Krendl Gilbert Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Humans and technology Why embracing complexity is the real challenge in software today In the midst of industry discussions about productivity and automation, it’s all too easy to overlook the importance of properly reckoning with complexity. By Ken Mugrage archive page Turning medical data into actionable knowledge Technology can transform patient care by bringing together data from a variety of sources By Siemens Healthineers archive page Moving data through the supply chain with unprecedented speed Tackle supply chain visibility and customer engagement with standards and “phygital” technology. By MIT Technology Review Insights archive page Customer experience horizons The big ideas that define the future of customer and employee experience. By MIT Technology Review Insights archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Vinge’s Singular Vision | MIT Technology Review"

"https://www.technologyreview.com/2006/07/01/228762/vinges-singular-vision"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Vinge’s Singular Vision By Stewart Brand archive page Vernor Vinge dedicates his new novel, Rainbows End , “To the Internet-based cognitive tools that are changing our lives – Wikipedia, Google, eBay, and the others of their kind, now and in the future.” The book is an imagining of how those technologies might develop over the next two decades. But publication of Rainbows End is not only a literary event. The question arises, “Will Vinge influence the actual evolution of the technology?” He has done so before. Many coders and system designers, as well as those who market their work, read science fiction for ideas as well as entertainment. A few fictional ideas gain such currency that they affect the real world. In 1984, the “cyberspace” of William Gibson’s Neuromancer inspired a generation of early netheads as they imagined the “consensual hallucination” (to use Gibson’s phrase) that became the World Wide Web. Equally, Neal Stephenson’s “Metaverse,” the massively shared virtual reality in his 1992 novel Snow Crash , helped lead to multiplayer worlds such as Second Life. But the earliest fictional evocation of an immersive virtual world came back in 1981 with Vernor Vinge’s novella “True Names,” in which the secretly powerful alternate reality was called “the Other Plane.” By 1995 Kevin Kelly would observe in Wired magazine, “Many Net veterans cite True Names as a seminal influence that shaped their ideas about Net policy. … It became a cult classic among hackers and presaged everything from Internet interactive games to Neuromancer. ” In 1984 and 1986, Vinge struck again. With a pair of novels later published together as Across Realtime , Vinge proposed that technological progress would soon accelerate to a spike of such intense change that on the other side of it, humanity would be unrecognizable. His description of that metamorphosis, which he dubbed “the Singularity,” has since guided many visions of 21st-century technology. In a departure from Vinge’s recent heavy-duty space operas, the Hugo Award winners A Fire upon the Deep and A Deepness in the Sky , Rainbows End is short. It’s a picaresque of sorts, set in the 2025 San Diego first explored in Vinge’s 2002 story “Fast Times at Fairmont High.” In the book, everybody’s real world is draped with arrays of private and shared virtual realities, and “Search and Analysis” is the core skill taught to the young and the rejuvenated old as “the heart of the economy.” It turns out that the crux of a Search and Analysis world (and of Vinge’s narrative) is this: who knows what, and how, and how is their knowing displayed or cloaked? Setting the story in the near future lets Vinge build on his own real-world career teaching math and computer science at San Diego State University, as well as consulting for commercial and government organizations and writing science fiction. The novel teases and advises all those communities. Setting the plot in motion, ultranetworked spies discover that a project for subtle, targeted mind control is under way in a fortresslike bioscience lab on the campus of the University of California, San Diego. And so this university tale features steam tunnel adventures, an extravagantly exploited graduate student, and lifelong academic vendettas (a downside of life extension). Google’s current Book Search project is both praised and satirized. Why shouldn’t humanity’s entire intellectual past be as indexed, organized, linked, and searchable as information that was digital from its creation? Too bad the books themselves are destroyed as they are scanned. (The real Google is more careful.) National-security analysis, in Rainbows End , is conducted by free-floating swarms of analysts who can generate and sift a thousand conjectures simultaneously but can also collapse into procedural dispute. Surveillance is done competently by obsessive hobbyists. Military action consists mainly of signals intelligence. Vinge has a high old time with the conventions of science fiction and fantasy. Of course, the fate of everything is at stake. The world is in a permanent state of dread that some evildoer might convert one of the innumerable new cyber- and bio- and cogno- and nanotools into a weapon of annihilation. Even the coolest new technologies are beset with problems. Yes, you can absorb a skill like a new language with “just-in-time training,” but the process is so immersive you might get permanently stuck in it. Yes, you can live a lot longer, but different ailments are differentially susceptible to cure, and some people are more fully rejuvenated than others. Fantasy fandom is a huge force in Vinge’s world, where massively multiplayer games are the dominant entertainment medium, and the legions of enthusiasts in “belief circles” can not only project their fantasies onto the increasingly attenuated fabric of the real world but pit their fictional worlds against each other in epistemological combat. Heroic figures like Dangerous Knowledge and Librarians Militant (both from a Terry Pratchett-like fantasy domain) and the Greater Scooch-a-mout and Mind Sum (from a Pokémon-like franchise) duke it out in front of a real library and an online flash crowd of millions. Vinge’s technological speculations are among the book’s chief pleasures. His professional association with the Internet, which dates to its beginning, allows him to make some interesting proposals. How about a “Secure Hardware Environment” as the deeply reliable and unhackable foundation of everything online and virtual? How about “certificate authorities” that offer people the option of accountability amid the blizzard of faux personalities lashing through cyberspace? See Vinge rejoice in the nuances of a network decaying toward breakdown: The network problems were getting a lot worse. There were strange latencies, maybe real partitions. Blocks of the virtual audience were being run on cache. Single-hop still mostly worked, but routed communication was in trouble. Huynh stepped a few feet to the side and managed to find a good diagnostic source. There were certificate failures at the lowest levels. He had never seen that before. Even the localizer mesh was failing. Like the holes in a threadbare carpet, splotches of plain reality grew around him. The most intriguing character in Rainbows End is its hidden hero, the enigmatic figure Rabbit, a faux being whose puissance is matched by his juvenile humor. Is he an artificial intelligence? If so, what does that portend? Happily, Vinge is planning a sequel that will explore the matter further. Stewart Brand was the founder of the Whole Earth Catalog and a cofounder of the WELL, Global Business Network, and the Long Now Foundation. Rainbows End By Vernor Vinge Tor, 2006, $25.95 hide by Stewart Brand Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window This story was part of our July/August 2006 issue. Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Uncategorized The Download: how to fight pandemics, and a top scientist turned-advisor Plus: Humane's Ai Pin has been unveiled By Rhiannon Williams archive page The race to destroy PFAS, the forever chemicals Scientists are showing these damaging compounds can be beat. By John Wiegand archive page How scientists are being squeezed to take sides in the conflict between Israel and Palestine Tensions over the war are flaring on social media—with real-life ramifications. By Antonio Regalado archive page These new tools could make AI vision systems less biased Two new papers from Sony and Meta describe novel methods to make bias detection fairer. By Melissa Heikkilä archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"How China takes extreme measures to keep teens off TikTok | MIT Technology Review"

"https://www.technologyreview.com/2023/03/08/1069527/china-tiktok-douyin-teens-privacy"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts How China takes extreme measures to keep teens off TikTok TikTok announced a one-hour daily limit for users under 18, but authorities in China have pushed the domestic version, Douyin, much further. By Zeyi Yang archive page Stephanie Arnett/MITTR | Envato China Report is MIT Technology Review’s newsletter about technology developments in China. Sign up to receive it in your inbox every Tuesday. As I often say, the American people and the Chinese people have much more in common than either side likes to admit. For example, take the shared concern about how much time children and teenagers are spending on TikTok (or its Chinese domestic version, Douyin). On March 1, TikTok announced that it’s setting a 60-minute default time limit per day for users under 18. Those under 13 would need a code entered by their parents to have an additional 30 minutes, while those between 13 and 18 can make that decision for themselves. While the effectiveness of this measure remains to be seen (it’s certainly possible, for example, to lie about your age when registering for the app), TikTok is clearly responding to popular requests from parents and policymakers who are concerned that kids are overly addicted to it and other social media platforms. In 2022, teens spent on average 103 minutes per day on TikTok , beating Snapchat (72 minutes) and YouTube (67). The app has also been found to promote content about eating disorders and self-harm to young users. Lawmakers are taking notice: several US senators have pushed for bills that would restrict underage users’ access to apps like TikTok. But ByteDance, the parent company of TikTok, is no stranger to those requests. In fact, it has been dealing with similar government pressures in China since at least 2018. That year, Douyin introduced in-app parental controls, banned underage users from appearing in livestreams, and released a “teenager mode” that only shows whitelisted content, much like YouTube Kids. In 2019, Douyin limited users in teenager mode to 40 minutes per day, accessible only between the hours of 6 a.m. and 10 p.m. Then, in 2021, it made the use of teenager mode mandatory for users under 14. So a lot of the measures that ByteDance is now starting to introduce outside China with TikTok have already been tested aggressively with Douyin. Why has it taken so long for TikTok to impose screen-time limits? Some right-wing politicians and commentators are alleging actual malice from ByteDance and the Chinese government (“It’s almost like they recognize that technology is influencing kids’ development, and they make their domestic version a spinach version of TikTok, while they ship the opium version to the rest of the world,” Tristan Harris, cofounder of the Center for Humane Technology and a former Google employee, told 60 Minutes. ) But I don’t think that the difference between the two platforms is the result of some sort of conspiracy. Douyin would probably look very similar to TikTok were it not for how quickly and forcefully the Chinese government regulates digital platforms. The Chinese political system allows the government to react swiftly to the consequences of new tech platforms. Sometimes it’s in response to a widespread concern, such as teen addiction to social media. Other times it’s more about the government’s interests, like clamping down on a new product that makes censorship harder. But the shared result is that the state is able to ask platforms to make changes quickly without much pushback. You can see that clearly in the Chinese government’s approach to another tech product commonly accused of causing teen addiction: video games. After denouncing the games for many years, the government implemented strict restrictions in 2021: people under 18 in China are allowed to play video games only between 8 and 9 p.m. on weekends and holidays ; they are supposed to be blocked from using them outside those hours. Gaming companies are punished for violations, and many have had to build or license costly identity verification systems to enforce the rule. Related Story TikTok bugs keep frustrating the app's marginalized users. It's a familiar problem. When the crackdown on video games happened in 2021, the social media industry was definitely spooked, because many Chinese people were already comparing short-video apps like Douyin to video games in terms of addictiveness. It seemed as though the sword of Damocles could drop at any time. That possibility seems even more certain now. On February 27, the National Radio and Television Administration, China’s top authority on media production and consumption, said it had convened a meeting to work on “enforcing the regulation of short videos and preventing underage users from becoming addicted.” News of the meeting sent a clear signal to Chinese social media platforms that the government is not pleased with the current measures and needs them to come up with new ones. What could those new measures look like? It could mean even stricter rules around screen time and content. But the announcement also mentioned some other interesting directions, like requiring creators to obtain a license to provide content for teenagers and developing ways for the government to regulate the algorithms themselves. As the situation develops, we should expect to see more innovative measures taken in China to impose limits on Douyin and similar platforms. As for the US, even getting to the level of China’s existing regulations around social media would require some big changes. To ensure that no teens in China are using their parents’ accounts to watch or post to Douyin, every account is linked to the user’s real identity, and the company says facial recognition tech is used to monitor the creation of livestream content. Sure, those measures help prevent teens from finding workarounds, but they also have privacy implications for all users , and I don’t believe everyone will decide to sacrifice those rights just to make sure they can control what children get to see. We can see how the control vs. privacy trade-off has previously played out in China. Before 2019, the gaming industry had a theoretical daily play-time limit for underage gamers, but it couldn’t be enforced in real time. Now there is a central database created for gamers, tied to facial recognition systems developed by big gaming publishers like Tencent and NetEase, that can verify everyone’s identity in seconds. On the content side of things, Douyin’s teenager mode bans a slew of content types from being shown, including videos of pranks, “superstitions,” or “entertainment venues”—places like dance or karaoke clubs that teenagers are not supposed to enter. While the content is likely selected by ByteDance employees, social media companies in China are regularly punished by the government for failing to conduct thorough censorship, and that means decisions about what is suitable for teens to watch are ultimately made by the state. Even the normal version of Douyin regularly takes down pro-LGBTQ content on the basis that they present “unhealthy and non-mainstream views on marriage and love.” There is a dangerously thin line between content moderation and cultural censorship. As people lobby for more protection for their children, we’ll have to answer some hard questions about what those social media limits should look like—and what we’re willing to trade for them. Do you think a mandatory daily TikTok time limit for teenagers is necessary? Let me know what you think at [email protected]. Catch up with China 1. Over the weekend, the Chinese government held its “two sessions”—an annual political gathering that often signals government plans for the next year. Li Keqiang, China’s outgoing premier, set the annual GDP growth target as 5%, the lowest in nearly 30 years. ( New York Times $ ) Because the government is often cryptic about its policy priorities, it becomes an annual tradition to analyze what words are mentioned the most in the premier’s report. This year, “stability,” “food,” and “energy” took center stage. ( Nikkei Asia $ ) Some political representatives come from the tech industry, and it’s common (and permissible) for them to make policy recommendations that are favorable to their own business interests. I called it “the Chinese style of lobbying” in a report last year. ( Protocol ) 2. Wuxi, a second-tier city in eastern China, announced that it has deliberately destroyed a billion pieces of personal data, as part of its process of decommissioning pandemic surveillance systems. ( CNN ) 3. Diversifying from manufacturing in China, Foxconn plans to increase production in India from 6 million iPhones a year to 20 million, and to triple the number of workers to 100,000 by 2024. ( Wall Street Journal $ ) 4. Chinese diplomats are being idolized like pop-culture celebrities by young fans on social media. ( What’s on Weibo $ ) 5. China is planning on creating a new government agency that has concentrated authority on various data-related issues, anonymous sources said. ( Wall Street Journal $ ) 6. Activists and investors are criticizing Volkswagen after its CEO toured the company’s factories in Xinjiang and said he didn’t see any sign of forced labor. ( Reuters $ ) 7. Wuling, the Chinese tiny-EV brand that outsold Tesla in 2021, has found its first overseas market in Indonesia, and its cars have become the most popular choice of EV there. ( Rest of World ) 8. The US government added 37 more Chinese companies, some in genetics research and cloud computing, to its trade blacklist. ( Reuters $ ) Lost in translation As startups swarm to develop the Chinese version of ChatGPT, Chinese publication Leiphone made an infographic comparing celebrity founders in China to determine who’s most likely to win the race. The analysis takes into consideration four dimensions: academic reputation and influence, experience working with corporate engineers, resourcefulness within the Chinese political and business ecosystem, and proclaimed interest in joining the AI chatbot arms race. The two winners of the analysis are Wang Xiaochuan, the CEO of Chinese search engine Sogou, and Lu Qi, a former executive at Microsoft and Baidu. Wang has embedded himself deeply in the circles of Tsinghua University (China’s top engineering school) and Tencent, making it possible for him to assemble a star team quickly. Meanwhile, Lu’s experience working on Microsoft’s Bing and Baidu’s self-driving unit makes him extremely relevant. Plus, Lu is now the head of Y Combinator China and has personal connections to Sam Altman, the CEO of OpenAI and the former president of Y Combinator. One more thing Recently, a video went viral in China that shows a driver kneeling in front of his electric vehicle to scan his face. An app in the car system required the driver to verify his identity through facial recognition, and since there’s no camera within the car, the exterior camera on the front of the car was the only option. hide by Zeyi Yang Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Why YouTube Could Give Google an Edge in AI — The Information"

"https://www.theinformation.com/articles/why-youtube-could-give-google-an-edge-in-ai"

"Exclusive: OpenAI Co-Founder Altman Plans New Venture Subscribe and Read now Why YouTube Could Give Google an Edge in AI Why YouTube Could Give Google an Edge in AI By Jon Victor [email protected] ­om Profile and archive → Follow Jon on Twitter Google last month upgraded its Bard chatbot with a new machine-learning model that can better understand conversational language and compete with OpenAI’s ChatGPT. As Google develops a sequel to that model, it may hold a trump card: YouTube. The video site, which Google owns, is the single biggest and richest source of imagery, audio and text transcripts on the internet. And Google’s researchers have been using YouTube to develop its next large-language model, Gemini, according to a person with knowledge of the situation. The value of YouTube hasn’t been lost on OpenAI, either: The startup has secretly used data from the site to train some of its artificial intelligence models, said one person with direct knowledge of the effort. Join now to read the full story Get Started - or - Already a subscriber? Sign in here Exclusive Exclusive startups ai Exclusive ai Exclusive ai Exclusive venture capital Exclusive startups Finance The Briefing Get Started © 2013-2023 The Information. All Rights Reserved. "

"How existential risk became the biggest meme in AI | MIT Technology Review"

"https://www.technologyreview.com/2023/06/19/1075140/how-existential-risk-became-biggest-meme-in-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts How existential risk became the biggest meme in AI "Ghost stories are contagious." By Will Douglas Heaven archive page Stephanie Arnett/MITTR | Getty Who’s afraid of the big bad bots? A lot of people, it seems. The number of high-profile names that have now made public pronouncements or signed open letters warning of the catastrophic dangers of artificial intelligence is striking. Hundreds of scientists, business leaders, and policymakers have spoken up, from deep learning pioneers Geoffrey Hinton and Yoshua Bengio to the CEOs of top AI firms, such as Sam Altman and Demis Hassabis , to the California congressman Ted Lieu and the former president of Estonia Kersti Kaljulaid. Related Story “I have suddenly switched my views on whether these things are going to be more intelligent than us.” The starkest assertion, signed by all those figures and many more, is a 22-word statement put out two weeks ago by the Center for AI Safety (CAIS), an agenda-pushing research organization based in San Francisco. It proclaims: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” The wording is deliberate. “If we were going for a Rorschach-test type of statement, we would have said ‘existential risk’ because that can mean a lot of things to a lot of different people,” says CAIS director Dan Hendrycks. But they wanted to be clear: this was not about tanking the economy. “That’s why we went with ‘risk of extinction’ even though a lot of us are concerned with various other risks as well,” says Hendrycks. We've been here before: AI doom follows AI hype. But this time feels different. The Overton window has shifted. What were once extreme views are now mainstream talking points, grabbing not only headlines but the attention of world leaders. “The chorus of voices raising concerns about AI has simply gotten too loud to be ignored,” says Jenna Burrell, director of research at Data and Society, an organization that studies the social impact of technology. What’s going on? Has AI really become (more) dangerous? And why are the people who ushered in this tech now the ones raising the alarm? It’s true that these views split the field. Last week, Yann LeCun, chief scientist at Meta and joint recipient with Hinton and Bengio of the 2018 Turing Award, called the doomerism “preposterously ridiculous.” Aidan Gomez, CEO of the AI firm Cohere, said it was “an absurd use of our time.” Others scoff too. “There’s no more evidence now than there was in 1950 that AI is going to pose these existential risks,” says Signal president Meredith Whittaker, who is cofounder and former director of the AI Now Institute, a research lab that studies the policy implications of artificial intelligence. “Ghost stories are contagious—it’s really exciting and stimulating to be afraid.” “It is also a way to skim over everything that’s happening in the present day,” says Burrell. “It suggests that we haven’t seen real or serious harm yet.” An old fear Concerns about runaway, self-improving machines have been around since Alan Turing. Futurists like Vernor Vinge and Ray Kurzweil popularized these ideas with talk of the so-called Singularity, a hypothetical date at which artificial intelligence outstrips human intelligence and machines take over. But at the heart of such concerns is the question of control: How do humans stay on top if (or when) machines get smarter? In a paper called “How Does Artificial Intelligence Pose an Existential Risk?” published in 2017, Karina Vold, a philosopher of artificial intelligence at the University of Toronto (who signed the CAIS statement), lays out the basic argument behind the fears. Related Story A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. There are three key premises. One, it’s possible that humans will build a superintelligent machine that can outsmart all other intelligences. Two, it’s possible that we will not be able to control a superintelligence that can outsmart us. And three, it’s possible that a superintelligence will do things that we do not want it to. Putting all that together, it is possible to build a machine that will do things that we don’t want it to—up to and including wiping us out—and we will not be able to stop it. There are different flavors of this scenario. When Hinton raised his concerns about AI in May, he gave the example of robots rerouting the power grid to give themselves more power. But superintelligence (or AGI) is not necessarily required. Dumb machines, given too much leeway, could be disastrous too. Many scenarios involve thoughtless or malicious deployment rather than self-interested bots. In a paper posted online last week, Stuart Russell and Andrew Critch, AI researchers at the University of California, Berkeley (who also both signed the CAIS statement), give a taxonomy of existential risks. These range from a viral advice-giving chatbot telling millions of people to drop out of college to autonomous industries that pursue their own harmful economic ends to nation-states building AI-powered superweapons. In many imagined cases, a theoretical model fulfills its human-given goal but does so in a way that works against us. For Hendrycks, who studied how deep-learning models can sometimes behave in unexpected and undesirable ways when given inputs not seen in their training data , an AI system could be disastrous because it is broken rather than all-powerful. “If you give it a goal and it finds alien solutions to it, it’s going to take us for a weird ride,” he says. The problem with these possible futures is that they rest on a string of what-ifs, which makes them sound like science fiction. Vold acknowledges this herself. “Because events that constitute or precipitate an [existential risk] are unprecedented, arguments to the effect that they pose such a threat must be theoretical in nature,” she writes. “Their rarity also makes it such that any speculations about how or when such events might occur are subjective and not empirically verifiable.” So why are more people taking these ideas at face value than ever before? “Different people talk about risk for different reasons, and they may mean different things by it,” says François Chollet, an AI researcher at Google. But it is also a narrative that’s hard to resist: “Existential risk has always been a good story.” “There’s a sort of mythological, almost religious element to this that can’t be discounted,” says Whittaker. “I think we need to recognize that what is being described, given that it has no basis in evidence, is much closer to an article of faith, a sort of religious fervor, than it is to scientific discourse.” The doom contagion When deep-learning researchers first started to rack up a series of successes—think of Hinton and his colleagues’ record-breaking image-recognition scores in the ImageNet competition in 2012 and DeepMind’s first wins against human champions with AlphaGo in 2015—the hype soon turned to doomsaying then too. Celebrity scientists, such as Stephen Hawking and fellow cosmologist Martin Rees, as well as celebrity tech leaders like Elon Musk, raised the alarm about existential risk. But these figures weren’t AI experts. Eight years ago, deep learning pioneer Andrew Ng, who was chief scientist at Baidu at the time, stood on a stage in San Jose and laughed off the entire idea. Related Story Experts at RightsCon want us to focus less on existential threats, and more on the harms here and now. “There could be a race of killer robots in the far future,” Ng told the audience at Nvidia’s GPU Technology Conference in 2015. “But I don’t work on not turning AI evil today for the same reason I don’t worry about the problem of overpopulation on the planet Mars.” ( Ng’s words were reported at the time by tech news website The Register.) Ng, who cofounded Google’s AI lab in 2011 and is now CEO of Landing AI, has repeated the line in interviews since. But these days he’s less sanguine. “I’m keeping an open mind and am speaking with a few people to learn more,” he tells me. “The rapid pace of development has led scientists to rethink the risks.” Like many, Ng is concerned by the rapid progress of generative AI and its potential for misuse. He notes that a widely shared AI-generated image of an explosion at the Pentagon spooked people last month so much that the stock market dropped. “With AI being so powerful, unfortunately it seems likely that it will also lead to massive problems,” says Ng. But he stops short of killer robots: “Right now, I still struggle to see how AI can lead to our extinction.” Something else that's new is the widespread awareness of what AI can do. Late last year, ChatGPT brought this technology to the public. “AI is a popular topic in the mainstream all of a sudden,” says Chollet. “People are taking AI seriously because they see a sudden jump in capabilities as a harbinger of more future jumps.” The experience of conversing with a chatbot can also be unnerving. Conversation is something that is typically understood as something people do with other people. “It added a kind of plausibility to the idea that AI was human-like or a sentient interlocutor,” says Whittaker. “I think it gave some purchase to the idea that if AI can simulate human communication, it could also do XYZ.” “That is the opening that I see the existential risk conversation sort of fitting into—extrapolating without evidence,” she says. Look to the future There’s reason to be cynical, too. With regulators catching up to the tech industry, the issue on the table is what sorts of activity should and should not get constrained. Highlighting long-term risks rather than short-term harms (such as discriminatory hiring or misinformation) refocuses regulators’ attention on hypothetical problems down the line. Related Story Let us walk you through all the most (and least) promising efforts to govern AI around the world. “I suspect the threat of genuine regulatory constraints has pushed people to take a position,” says Burrell. Talking about existential risks may validate regulators’ concerns without undermining business opportunities. “Superintelligent AI that turns on humanity sounds terrifying, but it’s also clearly not something that’s happened yet,” she says. Inflating fears about existential risk is also good for business in other ways. Chollet points out that top AI firms need us to think that AGI is coming, and that they are the ones building it. “If you want people to think what you’re working on is powerful, it’s a good idea to make them fear it,” he says. Whittaker takes a similar view. “It’s a significant thing to cast yourself as the creator of an entity that could be more powerful than human beings,” she says. None of this would matter much if it were simply about marketing or hype. But deciding what the risks are, and what they’re not, has consequences. In a world where budgets and attention spans are limited, harms less extreme than nuclear war may get overlooked because we’ve decided they aren’t the priority. “It’s an important question, especially with the growing focus on security and safety as the narrow frame for policy intervention,” says Sarah Myers West, managing director of the AI Now Institute. When Prime Minister Rishi Sunak met with heads of AI firms, including Sam Altman and Demis Hassabis, in May, the UK government issued a statement saying: “The PM and CEOs discussed the risks of the technology, ranging from disinformation and national security, to existential threats.” The week before, Altman told the US Senate his worst fear was that the AI industry would cause significant harm to the world. Altman’s testimony helped spark calls for a new kind of agency to address such unprecedented harm. With the Overton window shifted, is the damage done? “If we’re talking about the far future, if we’re talking about mythological risks, then we are completely reframing the problem to be a problem that exists in a fantasy world and its solutions can exist in a fantasy world too,” says Whittaker. But Whittaker also points out that policy discussions around AI have been going on for years, longer than this recent buzz of fear. “I don’t believe in inevitability,” she says. “We will see a beating back of this hype. It will subside.” hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Five big takeaways from Europe's AI Act | MIT Technology Review"

"https://www.technologyreview.com/2023/06/19/1075063/five-big-takeaways-from-europes-ai-act"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Five big takeaways from Europe’s AI Act The AI Act vote passed with an overwhelming majority, but the final version is likely to look a bit different By Tate Ryan-Mosley archive page Stephanie Arnett/MITTR | Envato, Midjourney This article is from The Technocrat, MIT Technology Review's weekly tech policy newsletter about power, politics, and Silicon Valley. To receive it in your inbox every Friday, sign up her e. It was a big week in tech policy in Europe with the European Parliament’s vote to approve its draft rules for the AI Act on the same day EU lawmakers filed a new antitrust lawsuit against Google. The AI Act vote passed with an overwhelming majority, and has been heralded as one of the world’s most important developments in AI regulation. The European Parliament’s president, Roberta Metsola, described it as “legislation that will no doubt be setting the global standard for years to come.” Don’t hold your breath for any immediate clarity, though. The European system is a bit complicated. Next, members of the European Parliament will have to thrash out details with the Council of the European Union and the EU’s executive arm, the European Commission, before the draft rules become legislation. The final legislation will be a compromise between three different drafts from the three institutions, which vary a lot. It will likely take around two years before the laws are actually implemented. What Wednesday’s vote accomplished was to approve the European Parliament’s position in the upcoming final negotiations. Structured similarly to the EU’s Digital Services Act, a legal framework for online platforms, the AI Act takes a “risk-based approach” by introducing restrictions based on how dangerous lawmakers predict an AI application could be. Businesses will also have to submit their own risk assessments about their use of AI. Some applications of AI will be banned entirely if lawmakers consider the risk “unacceptable,” while technologies deemed “high risk” will have new limitations on their use and requirements around transparency. Here are some of the major implications: Ban on emotion-recognition AI. The European Parliament’s draft text bans the use of AI that attempts to recognize people’s emotions in policing, schools, and workplaces. Makers of emotion-recognition software claim that AI is able to determine when a student is not understanding certain material, or when a driver of a car might be falling asleep. The use of AI to conduct facial detection and analysis has been criticized for inaccuracy and bias , but it has not been banned in the draft text from the other two institutions, suggesting there’s a political fight to come. Ban on real-time biometrics and predictive policing in public spaces. This will be a major legislative battle , because the various EU bodies will have to sort out whether, and how, the ban is enforced in law. Policing groups are not in favor of a ban on real-time biometric technologies, which they say are necessary for modern policing. Some countries, like France, are actually planning to increase their use of facial recognition. Ban on social scoring. Social scoring by public agencies, or the practice of using data about people's social behavior to make generalizations and profiles, would be outlawed. That said, the outlook on social scoring, commonly associated with China and other authoritarian governments, isn’t really as simple as it may seem. The practice of using social behavior data to evaluate people is common in doling out mortgages and setting insurance rates, as well as in hiring and advertising. New restrictions for gen AI. This draft is the first to propose ways to regulate generative AI, and ban the use of any copyrighted material in the training set of large language models like OpenAI’s GPT-4. OpenAI has already come under the scrutiny of European lawmakers for concerns about data privacy and copyright. The draft bill also requires that AI generated content be labeled as such. That said, the European Parliament now has to sell its policy to the European Commission and individual countries, which are likely to face lobbying pressure from the tech industry. New restrictions on recommendation algorithms on social media. The new draft assigns recommender systems to a “high risk” category , which is an escalation from the other proposed bills. This means that if it passes, recommender systems on social media platforms will be subject to much more scrutiny about how they work, and tech companies could be more liable for the impact of user-generated content. The risks of AI as described by Margrethe Vestager, executive vice president of the EU Commission, are widespread. She has emphasized concerns about the future of trust in information, vulnerability to social manipulation by bad actors, and mass surveillance. “If we end up in a situation where we believe nothing, then we have undermined our society completely,” Vestager told reporters on Wednesday. What I am reading this week A Russian soldier surrendered to a Ukrainian assault drone, according to video footage published by the Wall Street Journal. The surrender took place back in May in the eastern city of Bakhmut, Ukraine. The drone operator decided to spare the life of the soldier, according to international law, upon seeing his plea via video. Drones have been critical in the war, and the surrender is a fascinating look at the future of warfare. Many Redditors are protesting changes to the site’s API that would eliminate or reduce the function of third-party apps and tools many communities use. In protest, those communities have “gone private,” which means that the pages are no longer publicly accessible. Reddit is known for the power it gives to its user base, but the company may now be regretting that, according to Casey Newton’s sharp assessment. Contract workers who trained Google’s large language model, Bard, say they were fired after raising concerns about their working conditions and safety issues with the AI itself. The contractors say they were forced to meet unreasonable deadlines, which led to concerns about accuracy. Google says the responsibility lies with Appen, the contract agency employing the workers. If history tells us anything, there will be a human cost in the race to dominate generative AI. What I learned this week This week, Human Rights Watch released an in-depth report about an algorithm used to dole out welfare benefits in Jordan. The agency found some major issues with the algorithm, which was funded by the World Bank, and says the system was based on incorrect and oversimplified assumptions about poverty. The report’s authors also called out the lack of transparency and cautioned against similar projects run by the World Bank. I wrote a short story about the findings. Meanwhile, the trend toward using algorithms in government services is growing. Elizabeth Renieris, author of Beyond Data: Reclaiming Human Rights at the Dawn of the Metaverse , wrote to me about the report, and emphasized the impact these sort of systems will have going forward: “As the process to access benefits becomes digital by default, these benefits become even less likely to reach those who need them the most and only deepen the digital divide. This is a prime example of how expansive automation can directly and negatively impact people, and is the AI risk conversation that we should be focused on now.” hide by Tate Ryan-Mosley Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Policy Three things to know about the White House’s executive order on AI Experts say its emphasis on content labeling, watermarking, and transparency represents important steps forward. By Tate Ryan-Mosley archive page Melissa Heikkilä archive page How generative AI is boosting the spread of disinformation and propaganda In a new report, Freedom House documents the ways governments are now using the tech to amplify censorship. By Tate Ryan-Mosley archive page Government technology is famously bad. It doesn’t have to be. New York City is fixing the relationship between government and technology–and not in the ways you’d expect. By Tate Ryan-Mosley archive page It’s shockingly easy to buy sensitive data about US military personnel A new report exposes the privacy and national security concerns created by data brokers. US senators tell MIT Technology Review the industry needs to be regulated. By Tate Ryan-Mosley archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"How to talk about AI (even if you don’t know much about AI) | MIT Technology Review"

"https://www.technologyreview.com/2023/05/30/1073680/how-to-talk-about-ai-even-if-you-dont-know-much-about-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts How to talk about AI (even if you don’t know much about AI) Plus: Catching bad content in the age of AI. By Melissa Heikkilä archive page Stephanie Arnett/MITTR | Getty This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Everyone is talking about AI, it seems. But if you feel overwhelmed or uncertain about what the hell people are talking about, don’t worry. I’ve got you. I asked some of the best AI journalists in the business to share their top tips on how to talk about AI with confidence. My colleagues and I spend our days obsessing over the tech, listening to AI folks and then translating what they say into clear, relatable language with important context. I’d say we know a thing or two about what we’re talking about. Here are seven things to pay attention to when talking about AI. 1. Don’t worry about sounding dumb “The tech industry is not great at explaining itself clearly, despite insisting that large language models will change the world. If you’re struggling, you aren’t alone,” says Nitasha Tiku, the Washington Post’s tech culture reporter. It doesn’t help that conversations about AI are littered with jargon, she adds. “Hallucination” is a fancy way of saying an AI system makes things up. And “prompt engineers” are just people who know how to talk to the AI to get what they want. Tiku recommends watching YouTube explainers on concepts and AI models. “Skip the AI influencers for the more subdued hosts, like Computerphile,” she says. “IBM Technology is great if you’re looking for something short and simple. There’s no channel aimed at casual observers, but it can help demystify the process.” And however you talk about AI, some people will grumble. “It sometimes feels like the world of AI has splintered into fandoms with everyone talking past each other, clinging to pet definitions and beliefs,” says Will Douglas Heaven, MIT Technology Review’s senior editor for AI. “Figure out what AI means to you, and stick to it.” 2. Be specific about what kind of AI you’re talking about “‘AI’” is often treated as one thing in public discourse, but AI is really a collection of a hundred different things,” says Karen Hao, the Wall Street Journal’s China tech and society reporter (and the creator of The Algorithm !). Hao says that it’s helpful to distinguish which function of AI you are talking about so you can have a more nuanced conversation: are you talking about natural-language processing and language models, or computer vision? Or different applications, such as chatbots or cancer detection? If you aren’t sure, here are some good definitions of various practical applications of artificial intelligence. Talking about "AI" as a singular thing obscures the reality of the tech, says Billy Perrigo, a staff reporter at Time. “There are different models that can do different things, that will respond differently to the same prompts, and that each have their own biases, too,” he says. 3. Keep it real “The two most important questions for new AI products and tools are simply: What does it do and how does it do it?” says James Vincent, senior editor at The Verge. There is a trend in the AI community right now to talk about the long-term risks and potential of AI. It’s easy to be distracted by hypothetical scenarios and imagine what the technology could possibly do in the future, but discussions about AI are usually better served by being pragmatic and focusing on the actual, not the what-ifs, Vincent adds. The tech sector also has a tendency to overstate the capabilities of their products. “Be skeptical; be cynical,” says Heaven. This is especially important when talking about AGI, or artificial general intelligence, which is typically used to mean software that is as smart as a person. (Whatever that means in itself.) “If something sounds like bad science fiction, maybe it is,” he adds. 4. Adjust your expectations Language models that power AI chatbots such as ChatGPT often “hallucinate,” or make things up. This can be annoying and surprising to people, but it’s an inherent part of how they work, says Madhumita Murgia, artificial-intelligence editor at the Financial Times. It’s important to remember that language models aren’t search engines that are built to find and give the “right” answers, and they don’t have infinite knowledge. They are predictive systems that are generating the most likely words, given your question and everything they’ve been trained on, Murgia adds. “This doesn’t mean that they can’t write anything original … but we should always expect them to be inaccurate and fabricate facts. If we do that, then the errors matter less because our usage and their applications can be adjusted accordingly,” she says. 5. Don’t anthropomorphize AI chatbots have captured the public’s imagination because they generate text that looks like something a human could have written, and they give users the illusion they are interacting with something other than a computer program. But programs are in fact all they are. It’s very important not to anthropomorphize the technology, or attribute human characteristics to it, says Chloe Xiang, a reporter at Motherboard. “Don’t give it a [gendered] pronoun, [or] say that it can feel, think, believe, et cetera.” Doing this helps feed into the misconception that AI systems are more capable and sentient than they are. I’ve found it’s really easy to slip up with this, because our language has not caught up with ways to describe what AI systems are doing. When in doubt, I replace “AI” with “computer program.” Suddenly you feel really silly saying a computer program told someone to divorce his wife ! 6. It’s all about power While hype and nightmare scenarios may dominate news headlines, when you talk about AI it is crucial to think about the role of power, says Khari Johnson, a senior staff writer at Wired. “Power is key to raw ingredients for making AI, like compute and data; key to questioning ethical use of AI; and key to understanding who can afford to get an advanced degree in computer science and who is in the room during the AI model design process,” Johnson says. Hao agrees. She says it’s also helpful to keep in mind that AI development is very political and involves massive amounts of money and many factions of researchers with competing interests: “Sometimes the conversation around AI is less about the technology and more about the people.” 7. Please, for the love of God, no robots Don’t picture or describe AI as a scary robot or an all-knowing machine. “Remember that AI is basically computer programming by humans—combining big data sets with lots of compute power and intelligent algorithms,” says Sharon Goldman, a senior writer at VentureBeat. Deeper Learning Catching bad content in the age of AI In the last 10 years, Big Tech has become really good at some things: language, prediction, personalization, archiving, text parsing, and data crunching. But it’s still surprisingly bad at catching, labeling, and removing harmful content. One simply needs to recall the spread of conspiracy theories about elections and vaccines in the United States over the past two years to understand the real-world damage this causes. The ease of using generative AI could turbocharge the creation of more harmful online content. People are already using AI language models to create fake news websites. But could AI help with content moderation? The newest large language models are much better at interpreting text than previous AI systems. In theory, they could be used to boost automated content moderation. Read more from Tate Ryan-Mosley in her weekly newsletter, The Technocrat. Bits and Bytes Scientists used AI to find a drug that could fight drug-resistant infections Researchers at MIT and McMaster University developed an AI algorithm that allowed them to find a new antibiotic to kill a type of bacteria responsible for many drug-resistant infections that are common in hospitals. This is an exciting development that shows how AI can accelerate and support scientific discovery. ( MIT News ) Sam Altman warns that OpenAI could quit Europe over AI rules At an event in London last week, the CEO said OpenAI could “cease operating” in the EU if it cannot comply with the upcoming AI Act. Altman said his company found much to criticize in how the AI Act was worded, and that there were “technical limits to what’s possible.” This is likely an empty threat. I’ve heard Big Tech say this many times before about one rule or another. Most of the time, the risk of losing out on revenue in the world’s second-largest trading bloc is too big, and they figure something out. The obvious caveat here is that many companies have chosen not to operate, or to have a restrained presence, in China. But that’s also a very different situation. ( Time ) Predators are already exploiting AI tools to generate child sexual abuse material The National Center for Missing and Exploited Children has warned that predators are using generative AI systems to create and share fake child sexual abuse material. With powerful generative models being rolled out with safeguards that are inadequate and easy to hack, it was only a matter of time before we saw cases like this. ( Bloomberg ) Tech layoffs have ravaged AI ethics teams This is a nice overview of the drastic cuts Meta, Amazon, Alphabet, and Twitter have all made to their teams focused on internet trust and safety as well as AI ethics. Meta, for example, ended a fact-checking project that had taken half a year to build. While companies are racing to roll out powerful AI models in their products, executives like to boast that their tech development is safe and ethical. But it’s clear that Big Tech views teams dedicated to these issues as expensive and expendable. ( CNBC ) hide by Melissa Heikkilä Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"AI that makes images: 10 Breakthrough Technologies 2023 | MIT Technology Review"

"https://www.technologyreview.com/2023/01/09/1064864/image-making-ai-10-breakthrough-technologies-2023"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts AI that makes images: 10 Breakthrough Technologies 2023 AI models that generate stunning imagery from simple phrases are evolving into powerful creative and commercial tools. By Will Douglas Heaven archive page Erik Carter via Dall-e 2 WHO OpenAI, Stability AI, Midjourney, Google WHEN Now OpenAI introduced a world of weird and wonderful mash-ups when its text-to-image model DALL-E was released in 2021. Type in a short description of pretty much anything, and the program spat out a picture of what you asked for in seconds. DALL-E 2, unveiled in April 2022, was a massive leap forward. Google also launched its own image-making AI, called Imagen. Yet the biggest game-changer was Stable Diffusion , an open-source text-to-image model released for free by UK-based startup Stability AI in August. Not only could Stable Diffusion produce some of the most stunning images yet, but it was designed to run on a (good) home computer. By making text-to-image models accessible to all, Stability AI poured fuel on what was already an inferno of creativity and innovation. Millions of people have created tens of millions of images in just a few months. But there are problems, too. Artists are caught in the middle of one of the biggest upheavals in a decade. And, just like language models, text-to-image generators can amplify the biased and toxic associations buried in training data scraped from the internet. The tech is now being built into commercial software, such as Photoshop. Visual-effects artists and video-game studios are exploring how it can fast-track development pipelines. And text-to-image technology has already advanced to text-to-video. The AI-generated video clips demoed by Google, Meta, and others in the last few months are only seconds long, but that will change. One day movies could be made just by feeding a script into a computer. Nothing else in AI grabbed people’s attention more last year—for the best and worst reasons. Now we wait to see what lasting impact these tools will have on creative industries—and the entire field of AI. No one knows where the rise of generative AI will leave us. Read more here. hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"What's next for AI | MIT Technology Review"

"https://www.technologyreview.com/2022/12/23/1065852/whats-next-for-ai"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts What’s next for AI Get a head start with our four big bets for 2023. By Melissa Heikkilä archive page Will Douglas Heaven archive page Stephanie Arnett/MITTR; Unsplash, Pexels, Wellcome Collection In 2022, AI got creative. AI models can now produce remarkably convincing pieces of text, pictures, and even videos, with just a little prompting. It’s only been nine months since OpenAI set off the generative AI explosion with the launch of DALL-E 2, a deep-learning model that can produce images from text instructions. That was followed by a breakthrough from Google and Meta: AIs that can produce videos from text. And it’s only been a few weeks since OpenAI released ChatGPT, the latest large language model to set the internet ablaze with its surprising eloquence and coherence. The pace of innovation this year has been remarkable—and at times overwhelming. Who could have seen it coming? And how can we predict what’s next? Luckily, here at MIT Technology Review we’re blessed with not just one but two journalists who spend all day, every day obsessively following all the latest developments in AI, so we’re going to give it a go. Here, Will Douglas Heaven and Melissa Heikkilä tell us the four biggest trends they expect to shape the AI landscape in 2023. Over to you, Will and Melissa. Get ready for multipurpose chatbots GPT-4 may be able to handle more than just language The last several years have seen a steady drip of bigger and better language models. The current high-water mark is ChatGPT , released by OpenAI at the start of December. This chatbot is a slicker, tuned-up version of the company’s GPT-3 , the AI that started this wave of uncanny language mimics back in 2020. But three years is a long time in AI, and though ChatGPT took the world by storm—and inspired breathless social media posts and newspaper headlines thanks to its fluid, if mindless , conversational skills—all eyes now are on the next big thing: GPT-4. Smart money says that 2023 will be the year the next generation of large language models kicks off. Related Story Some worry that the chatter about these tools is doing the whole field a disservice. What should we expect? For a start, future language models may be more than just language models. OpenAI is interested in combining different modalities—such as image or video recognition—with text. We’ve seen this with DALL-E. But take the conversational skills of ChatGPT and mix them up with image manipulation in a single model and you’d get something a lot more general-purpose and powerful. Imagine being able to ask a chatbot what’s in an image, or asking it to generate an image, and have these interactions be part of a conversation so that you can refine the results more naturally than is possible with DALL-E. We saw a glimpse of this with DeepMind’s Flamingo, a “visual language model” revealed in April, which can answer queries about images using natural language. And then, in May, DeepMind announced Gato , a “generalist” model that was trained using the same techniques behind large language models to perform different types of tasks, from describing images to playing video games to controlling a robot arm. If GPT-4 builds on such tech, expect the power of the best language and image-making AI (and more) in one package. Combining skills in language and images could in theory make next-gen AI better at understanding both. And it won’t just be OpenAI. Expect other big labs, especially DeepMind, to push ahead with multimodal models next year. But of course, there’s a downside. Next-generation language models will inherit most of this generation’s problems, such as an inability to tell fact from fiction, and a penchant for prejudice. Better language models will make it harder than ever to trust different types of media. And because nobody has fully figured out how to train models on data scraped from the internet without absorbing the worst of what the internet contains, they will still be filled with filth. —Will Douglas Heaven AI’s first red lines New laws and hawkish regulators around the world want to put companies on the hook Until now, the AI industry has been a Wild West, with few rules governing the use and development of the technology. In 2023 that is going to change. Regulators and lawmakers spent 2022 sharpening their claws. Next year, they are going to pounce. We are going to see what the final version of the EU’s sweeping AI law, the AI Act , will look like as lawmakers finish amending the bill, potentially by the summer. It will almost certainly include bans on AI practices deemed detrimental to human rights, such as systems that score and rank people for trustworthiness. Related Story The European Union is planning new legislation aimed at curbing the worst harms associated with artificial intelligence. The use of facial recognition in public places will also be restricted for law enforcement in Europe, and there’s even momentum to forbid that altogether for both law enforcement and private companies, although a total ban will face stiff resistance from countries that want to use these technologies to fight crime. The EU is also working on a new law to hold AI companies accountable when their products cause harm, such as privacy infringements or unfair decisions made by algorithms. In the US, the Federal Trade Commission is also closely watching how companies collect data and use AI algorithms. Earlier this year, the FTC forced weight loss company Weight Watchers to destroy data and algorithms because it had collected data on children illegally. In late December, Epic, which makes games like Fortnite, dodged the same fate by agreeing to a $520 million settlement. The regulator has spent this year gathering feedback on potential rules around how companies handle data and build algorithms, and chair Lina Khan has said the agency intends to protect Americans from unlawful commercial surveillance and data security practices with “urgency and rigor.” In China, authorities have recently banned creating deepfakes without the consent of the subject. Through the AI Act, the Europeans want to add warning signs to indicate that people are interacting with deepfakes or AI-generated images, audio, or video. All these regulations could shape how technology companies build, use and sell AI technologies. However, regulators have to strike a tricky balance between protecting consumers and not hindering innovation — something tech lobbyists are not afraid of reminding them of. AI is a field that is developing lightning fast, and the challenge will be to keep the rules precise enough to be effective, but not so specific that they become quickly outdated. As with EU efforts to regulate data protection, if new laws are implemented correctly, the next year could usher in a long-overdue era of AI development with more respect for privacy and fairness. —Melissa Heikkilä Big tech could lose its grip on fundamental AI research AI startups flex their muscles Big Tech companies are not the only players at the cutting edge of AI; an open-source revolution has begun to match, and sometimes surpass, what the richest labs are doing. In 2022 we saw the first community-built, multilingual large language model, BLOOM , released by Hugging Face. We also saw an explosion of innovation around the open-source text-to-image AI model Stable Diffusion, which rivaled OpenAI's DALL-E 2. Related Story A group of over 1,000 AI researchers has created a multilingual large language model bigger than GPT-3—and they’re giving it out for free. The big companies that have historically dominated AI research are implementing massive layoffs and hiring freezes as the global economic outlook darkens. AI research is expensive, and as purse strings are tightened, companies will have to be very careful about picking which projects they invest in—and are likely to choose whichever have the potential to make them the most money, rather than the most innovative, interesting, or experimental ones, says Oren Etzioni, the CEO of the Allen Institute for AI, a research organization. That bottom-line focus is already taking effect at Meta, which has reorganized its AI research teams and moved many of them to work within teams that build products. But while Big Tech is tightening its belt, flashy new upstarts working on generative AI are seeing a surge in interest from venture capital funds. Next year could be a boon for AI startups, Etzioni says. There is a lot of talent floating around, and often in recessions people tend to rethink their lives—going back into academia or leaving a big corporation for a startup, for example. Startups and academia could become the centers of gravity for fundamental research, says Mark Surman, the executive director of the Mozilla Foundation. “We’re entering an era where [the AI research agenda] will be less defined by big companies,” he says. “That’s an opportunity.” —Melissa Heikkilä Big Pharma is never going to be the same again From AI-produced protein banks to AI-designed drugs, biotech enters a new era In the last few years, the potential for AI to shake up the pharmaceutical industry has become clear. DeepMind's AlphaFold , an AI that can predict the structures of proteins (the key to their functions), has cleared a path for new kinds of research in molecular biology , helping researchers understand how diseases work and how to create new drugs to treat them. In November, Meta revealed ESMFold , a much faster model for predicting protein structure—a kind of autocomplete for proteins, which uses a technique based on large language models. Related Story Two groups have announced powerful new generative models that can design new proteins on demand not seen in nature. Between them, DeepMind and Meta have produced structures for hundreds of millions of proteins , including all that are known to science, and shared them in vast public databases. Biologists and drug makers are already benefiting from these resources , which make looking up new protein structures almost as easy as searching the web. But 2023 could be the year that this groundwork really bears fruit. DeepMind has spun off its biotech work into a separate company, Isomorphic Labs, which has been tight-lipped for more than a year now. There’s a good chance it will come out with something big this year. Further along the drug development pipeline, there are now hundreds of startups exploring ways to use AI to speed up drug discovery and even design previously unknown kinds of drugs. There are currently 19 drugs developed by AI drug companies in clinical trials (up from zero in 2020), with more to be submitted in the coming months. It’s possible that initial results from some of these may come out next year, allowing the first drug developed with the help of AI to hit the market. But clinical trials can take years, so don’t hold your breath. Even so, the age of pharmatech is here and there’s no going back. “If done right, I think that we will see some unbelievable and quite amazing things happening in this space,” says Lovisa Afzelius at Flagship Pioneering, a venture capital firm that invests in biotech. —Will Douglas Heaven This story is a part of MIT Technology Review’s What’s Next series , where we look across industries, trends, and technologies to give you a first look at the future. hide by Melissa Heikkilä & Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "

"Biotech labs are using AI inspired by DALL-E to invent new drugs | MIT Technology Review"

"https://www.technologyreview.com/2022/12/01/1064023/biotech-labs-are-using-ai-inspired-by-dall-e-to-invent-new-drugs"

"Featured Topics Newsletters Events Podcasts Featured Topics Newsletters Events Podcasts Biotech labs are using AI inspired by DALL-E to invent new drugs Two groups have announced powerful new generative models that can design new proteins on demand not seen in nature. By Will Douglas Heaven archive page Stephanie Arnett/MITTR; Envato, AlphaFold The explosion in text-to-image AI models like OpenAI’s DALL-E 2 —programs trained to generate pictures of almost anything you ask for—has sent ripples through the creative industries, from fashion to filmmaking, by providing weird and wonderful images on demand. The same technology behind these programs is also making a splash in biotech labs, which have started using this type of generative AI, known as a diffusion model, to conjure up designs for new types of protein never seen in nature. Related Story AlphaFold can predict the shape of proteins to within the width of an atom. The breakthrough will help scientists design drugs and understand disease. Today, two labs separately announced programs that use diffusion models to generate designs for novel proteins with more precision than ever before. Generate Biomedicines, a Boston-based startup, revealed a program called Chroma , which the company describes as the “DALL-E 2 of biology.” At the same time, a team at the University of Washington led by biologist David Baker has built a similar program called RoseTTAFold Diffusion. In a preprint paper posted online today, Baker and his colleagues show that their model can generate precise designs for novel proteins that can then be brought to life in the lab. “We’re generating proteins with really no similarity to existing ones,” says Joe Watson, one of the co-developers of RoseTTAFold Diffusion. These protein generators can be directed to produce designs for proteins with specific properties, such as shape or size or function. In effect, this makes it possible to come up with new proteins to do particular jobs on demand. Researchers hope that this will eventually lead to the development of new and more effective drugs. “We can discover in minutes what took evolution millions of years,” says Gevorg Grigoryan, CTO of Generate Biomedicines. “What is notable about this work is the generation of proteins according to desired constraints,” says Ava Amini, a biophysicist at Microsoft Research in Cambridge, Massachusetts. Proteins are the fundamental building blocks of living systems. In animals, they digest food, contract muscles, detect light, drive the immune system, and so much more. When people get sick, proteins play a part. Proteins are thus prime targets for drugs. And many of today’s newest drugs are protein based themselves. “Nature uses proteins for essentially everything,” says Grigoryan. “The promise that offers for therapeutic interventions is really immense.” But drug designers currently have to draw on an ingredient list made up of natural proteins. The goal of protein generation is to extend that list with a nearly infinite pool of computer-designed ones. Computational techniques for designing proteins are not new. But previous approaches have been slow and not great at designing large proteins or protein complexes—molecular machines made up of multiple proteins coupled together. And such proteins are often crucial for treating diseases. The two programs announced today are also not the first use of diffusion models for protein generation. A handful of studies in the last few months from Amini and others have shown that diffusion models are a promising technique, but these were proof-of-concept prototypes. Chroma and RoseTTAFold Diffusion build on this work and are the first full-fledged programs that can produce precise designs for a wide variety of proteins. Namrata Anand, who co-developed one of the first diffusion models for protein generation in May 2022, thinks the big significance of Chroma and RoseTTAFold Diffusion is that they have taken the technique and supersized it, training on more data and more computers. “It may be fair to say that this is more like DALL-E because of how they’ve scaled things up,” she says. Diffusion models are neural networks trained to remove “noise”—random perturbations added to data—from their input. Given a random mess of pixels, a diffusion model will try to turn it into a recognizable image. In Chroma, noise is added by unraveling the amino acid chains that a protein is made from. Given a random clump of these chains, Chroma tries to put them together to form a protein. Guided by specified constraints on what the result should look like, Chroma can generate novel proteins with specific properties. Baker’s team takes a different approach, though the end results are similar. Its diffusion model starts with an even more scrambled structure. Another key difference is that RoseTTAFold Diffusion uses information about how the pieces of a protein fit together provided by a separate neural network trained to predict protein structure (as DeepMind’s AlphaFold does). This guides the overall generative process. Generate Biomedicines and Baker’s team both show off an impressive array of results. They are able to generate proteins with multiple degrees of symmetry, including proteins that are circular, triangular, or hexagonal. To illustrate the versatility of their program, Generate Biomedicines generated proteins shaped like the 26 letters of the Latin alphabet and the numerals 0 to 10. Both teams can also generate pieces of proteins, matching new parts to existing structures. Related Story Most of these demonstrated structures would serve no purpose in practice. But because a protein’s function is determined by its shape, being able to generate different structures on demand is crucial. Generating strange designs on a computer is one thing. But the goal is to turn these designs into real proteins. To test whether Chroma produced designs that could be made, Generate Biomedicines took the sequences for some of its designs—the amino acid strings that make up the protein—and ran them through another AI program. They found that 55% of them would be predicted to fold into the structure generated by Chroma, which suggests that these are designs for viable proteins. Baker’s team ran a similar test. But Baker and his colleagues have gone a lot further than Generate Biomedicines in evaluating their model. They have created some of RoseTTAFold Diffusion’s designs in their lab. (Generate Biomedicines says that it is also doing lab tests but is not yet ready to share results.) “This is more than just proof of concept,” says Watson. “We’re actually using this to make really great proteins.” For Baker, the headline result is the generation of a new protein that attaches to the parathyroid hormone, which controls calcium levels in the blood. “We basically gave the model the hormone and nothing else and told it to make a protein that binds to it,” he says. When they tested the novel protein in the lab, they found that it attached to the hormone more tightly than anything that could have been generated using other computational methods—and more tightly than existing drugs. “It came up with this protein design out of thin air,” says Baker. Grigoryan acknowledges that inventing new proteins is just the first step of many. We’re a drug company, he says. “At the end of the day what matters is whether we can make medicines that work or not.” Protein based drugs need to be manufactured in large numbers, then tested in the lab and finally in humans. This can take years. But he thinks that his company and others will find ways to speed up those steps as well. “The rate of scientific progress comes in fits and starts,” says Baker. “But right now we're in the middle of what can only be called a technological revolution.” Correction: A previous version of this article misattributed Joe Watson's comments. hide by Will Douglas Heaven Share linkedinlink opens in a new window twitterlink opens in a new window facebooklink opens in a new window emaillink opens in a new window Popular This new data poisoning tool lets artists fight back against generative AI Melissa Heikkilä Everything you need to know about artificial wombs Cassandra Willyard Deepfakes of Chinese influencers are livestreaming 24/7 Zeyi Yang How to fix the internet Katie Notopoulos Deep Dive Artificial intelligence This new data poisoning tool lets artists fight back against generative AI The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. By Melissa Heikkilä archive page Deepfakes of Chinese influencers are livestreaming 24/7 With just a few minutes of sample video and $1,000, brands never have to stop selling their products. By Zeyi Yang archive page Driving companywide efficiencies with AI Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done. By MIT Technology Review Insights archive page Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work. By Will Douglas Heaven archive page Stay connected Illustration by Rose Wong Get the latest updates from MIT Technology Review Discover special offers, top stories, upcoming events, and more. Enter your email Thank you for submitting your email! It looks like something went wrong. We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at [email protected] with a list of newsletters you’d like to receive. The latest iteration of a legacy Advertise with MIT Technology Review © 2023 MIT Technology Review About About us Careers Custom content Advertise with us International Editions Republishing MIT News Help Help & FAQ My subscription Editorial guidelines Privacy policy Terms of Service Write for us Contact us twitterlink opens in a new window facebooklink opens in a new window instagramlink opens in a new window rsslink opens in a new window linkedinlink opens in a new window "