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Tag: algorithms

  • Marc Andreessen Once Called Online Safety Teams an Enemy. He Still Wants Walled Gardens for Kids

    Marc Andreessen Once Called Online Safety Teams an Enemy. He Still Wants Walled Gardens for Kids

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    In his polarizing “Techno-Optimist Manifesto” last year, venture capitalist Marc Andreessen listed a number of enemies to technological progress. Among them were “tech ethics” and “trust and safety,” a term used for work on online content moderation, which he said had been used to subject humanity to “a mass demoralization campaign” against new technologies such as artificial intelligence.

    Andreessen’s declaration drew both public and quiet criticism from people working in those fields—including at Meta, where Andreessen is a board member. Critics saw his screed as misrepresenting their work to keep internet services safer.

    On Wednesday, Andreessen offered some clarification: When it comes to his 9-year-old son’s online life, he’s in favor of guardrails. “I want him to be able to sign up for internet services, and I want him to have like a Disneyland experience,” the investor said in an onstage conversation at a conference for Stanford University’s Human-Centered AI research institute. “I love the internet free-for-all. Someday, he’s also going to love the internet free-for-all, but I want him to have walled gardens.”

    Contrary to how his manifesto may have read, Andreessen went on to say he welcomes tech companies—and by extension their trust and safety teams—setting and enforcing rules for the type of content allowed on their services.

    “There’s a lot of latitude company by company to be able to decide this,” he said. “Disney imposes different behavioral codes in Disneyland than what happens in the streets of Orlando.” Andreessen alluded to how tech companies can face government penalties for allowing child sexual abuse imagery and certain other types of content, so they can’t be without trust and safety teams altogether.

    So what kind of content moderation does Andreessen consider an enemy of progress? He explained that he fears two or three companies dominating cyberspace and becoming “conjoined” with the government in a way that makes certain restrictions universal, causing what he called “potent societal consequences” without specifying what those might be. “If you end up in an environment where there is pervasive censorship, pervasive controls, then you have a real problem,” Andreessen said.

    The solution as he described it is ensuring competition in the tech industry and a diversity of approaches to content moderation, with some having greater restrictions on speech and actions than others. “What happens on these platforms really matters,” he said. “What happens in these systems really matters. What happens in these companies really matters.”

    Andreessen didn’t bring up X, the social platform run by Elon Musk and formerly known as Twitter, in which his firm Andreessen Horowitz invested when the Tesla CEO took over in late 2022. Musk soon laid off much of the company’s trust and safety staff, shut down Twitter’s AI ethics team, relaxed content rules, and reinstated users who had previously been permanently banned.

    Those changes paired with Andreessen’s investment and manifesto created some perception that the investor wanted few limits on free expression. His clarifying comments were part of a conversation with Fei-Fei Li, codirector of Stanford’s HAI, titled “Removing Impediments to a Robust AI Innovative Ecosystem.”

    During the session, Andreessen also repeated arguments he has made over the past year that slowing down development of AI through regulations or other measures recommended by some AI safety advocates would repeat what he sees as the mistaken US retrenchment from investment in nuclear energy several decades ago.

    Nuclear power would be a “silver bullet” to many of today’s concerns about carbon emissions from other electricity sources, Andreessen said. Instead the US pulled back, and climate change hasn’t been contained the way it could have been. “It’s an overwhelmingly negative, risk-aversion frame,” he said. “The presumption in the discussion is, if there are potential harms therefore there should be regulations, controls, limitations, pauses, stops, freezes.”

    For similar reasons, Andreessen said, he wants to see greater government investment in AI infrastructure and research and a freer rein given to AI experimentation by, for instance, not restricting open-source AI models in the name of security. If he wants his son to have the Disneyland experience of AI, some rules, whether from governments or trust and safety teams, may be necessary too.

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  • Google’s AI Overviews Will Always Be Broken. That’s How AI Works

    Google’s AI Overviews Will Always Be Broken. That’s How AI Works

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    A week after its algorithms advised people to eat rocks and put glue on pizza, Google admitted Thursday that it needed to make adjustments to its bold new generative AI search feature. The episode highlights the risks of Google’s aggressive drive to commercialize generative AI—and also the treacherous and fundamental limitations of that technology.

    Google’s AI Overviews feature draws on Gemini, a large language model like the one behind OpenAI’s ChatGPT, to generate written answers to some search queries by summarizing information found online. The current AI boom is built around LLMs’ impressive fluency with text, but the software can also use that facility to put a convincing gloss on untruths or errors. Using the technology to summarize online information promises can make search results easier to digest but it is hazardous when online sources are contractionary or when people may use the information to make important decisions.

    “You can get a quick snappy prototype now fairly quickly with an LLM, but to actually make it so that it doesn’t tell you to eat rocks takes a lot of work,” says Richard Socher, who made key contributions to AI for language as a researcher and in late 2021 launched an AI-centric search engine called You.com.

    Socher says wrangling LLMs takes considerable effort because the underlying technology has no real understanding of the world and because the web is riddled with untrustworthy information. “In some cases it is better to actually not just give you an answer, or to show you multiple different viewpoints,” he says.

    Google’s head of search Liz Reid said in the company’s blog post late Thursday that it did extensive testing ahead of launching AI Overviews. But she added that errors like the rock eating and glue pizza examples, in which Google’s algorithms pulled information from a satirical article and jocular Reddit comment respectively, had prompted additional changes. They include better detection of “nonsensical queries,” Google says, and making the system rely less heavily on user-generated content.

    You.com routinely avoids the kinds of errors displayed by Google’s AI Overviews, Socher says, because his company developed about a dozen tricks to keep LLMs from misbehaving when used for search.

    “We are more accurate because we put a lot of resources into being more accurate,” Socher says. Among other things, You.com uses a custom-built web index designed to help LLMs steer clear of incorrect information. It also selects from multiple different LLMs to answer specific queries, and it uses a citation mechanism that can explain when sources are contradictory. Still, getting AI search right is tricky. WIRED found on Friday that You.com failed to correctly answer a query that has been known to trip up other AI systems, stating that “Based on the information available, there are no African nations whose names start with the letter ‘K.’” In previous tests, it had aced the query.

    Google’s generative AI upgrade to its most widely used and lucrative product is part of a tech industry-wide reboot inspired by OpenAI’s release of the chatbot ChatGPT in November 2022. A couple of months after ChatGPT debuted, Microsoft, a key partner of OpenAI, used its technology to upgrade its also-ran search engine Bing. The upgraded Bing was beset by AI-generated errors and odd behavior but the company’s CEO, Satya Nadella, said that the move was designed to challenge Google, saying “I want people to know we made them dance.”

    Some experts feel that Google rushed its AI upgrade. “I’m surprised they launched it as it is for as many queries—medical, financial queries—I thought they’d be more careful,” says Barry Schwartz, news editor at Search Engine Land, a publication that tracks the search industry. The company should have better anticipated that some people would intentionally try to trip up AI Overviews, he adds. “Google has to be smart about that,” Schwartz says, especially when they’re showing the results as default on their most valuable product.

    Lily Ray, a search engine optimization (SEO) consultant, was for a year a beta tester of the prototype that preceded AI Overviews, which Google called Search Generative Experience. She says she was unsurprised to see the errors that appeared last week given how the previous version tended to go awry. “I think it’s virtually impossible for it to always get everything right,” Ray says. “That’s the nature of AI.”



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  • Google Admits Its New AI Overviews Search Feature Screwed Up

    Google Admits Its New AI Overviews Search Feature Screwed Up

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    When bizarre and misleading answers to search queries generated by Google’s new AI Overview feature went viral on social media last week, the company issued statements that generally downplayed the notion the technology had problems. Late Thursday, the company’s head of search Liz Reid admitted the flubs had highlighted areas that needed improvement, writing that “we wanted to explain what happened and the steps we’ve taken.”

    Reid’s post directly referenced two of the most viral, and wildly incorrect, AI Overview results. One saw Google’s algorithms endorse eating rocks because doing so “can be good for you,” and the other suggested using nontoxic glue to thicken pizza sauce.

    Rock eating is not a topic many people were ever writing or asking questions about online, so there aren’t many sources for a search engine to draw on. According to Reid, the AI tool found an article from The Onion, a satirical website, that had been reposted by a software company, and misinterpreted the information as factual.

    As for Google telling its users to put glue on pizza, Reid effectively attributed the error to a sense of humor failure. “We saw AI Overviews that featured sarcastic or troll-y content from discussion forums,” she wrote. “Forums are often a great source of authentic, first-hand information, but in some cases can lead to less-than-helpful advice, like using glue to get cheese to stick to pizza.”

    It’s probably best not to make any kind of AI-generated dinner menu without carefully reading it through first.

    Reid also suggested that judging the quality of Google’s new take on search based on viral screenshots would be unfair. She claimed the company did extensive testing before its launch and that the company’s data shows people value AI Overviews, including by indicating that people are more likely to stay on a page discovered that way.

    Why the embarassing failures? Reid characterized the mistakes that won attention as the result of an internet-wide audit that wasn’t always well intended. “There’s nothing quite like having millions of people using the feature with many novel searches. We’ve also seen nonsensical new searches, seemingly aimed at producing erroneous results.”

    Google claims some widely distributed screenshots of AI Overviews gone wrong were fake, which seems to be true based on WIRED’s own testing. For example, a user on X posted a screenshot that appeared to be an AI Overview responding to the question “Can a cockroach live in your penis?” with an enthusiastic confirmation from the search engine that this is normal. The post has been viewed over five million times. Upon further inspection though, the format of the screenshot doesn’t align with how AI Overviews are actually presented to users. WIRED was not able to recreate anything close to that result.

    And it’s not just users on social media who were tricked by misleading screenshots of fake AI Overviews. The New York Times issued a correction to its reporting about the feature and clarified that AI Overviews never suggested users should jump off the Golden Gate Bridge if they are experiencing depression—that was just a dark meme on social media. “Others have implied that we returned dangerous results for topics like leaving dogs in cars, smoking while pregnant, and depression,” Reid wrote Thursday. “Those AI Overviews never appeared.”

    Yet Reid’s post also makes clear that not all was right with the original form of Google’s big new search upgrade. The company made “more than a dozen technical improvements” to AI Overviews, she wrote.

    Only four are described: better detection of “nonsensical queries” not worthy of an AI Overview; making the feature rely less heavily on user-generated content from sites like Reddit; offering AI Overviews less often in situations users haven’t found them helpful; and strengthening the guardrails that disable AI summaries on important topics such as health.

    There was no mention in Reid’s blog post of significantly rolling back the AI summaries. Google says it will continue to monitor feedback from users and adjust the features as needed.

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  • Most US TikTok Creators Don’t Think a Ban Will Happen

    Most US TikTok Creators Don’t Think a Ban Will Happen

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    A majority of US TikTok creators don’t believe the platform will be banned within a year, and most haven’t seen brands they work for shift their marketing budgets away from the app, according to a new survey of people who earn money from posting content on TikTok shared exclusively with WIRED.

    The findings suggest that TikTok’s influencer economy largely isn’t experiencing existential dread after Congress passed a law last month that put the future of the app’s US operations in jeopardy. The bill demands that TikTok separate from its Chinese parent company within a year or face a nationwide ban; TikTok is challenging the constitutionality of the measure in court.

    Fohr, an influencer marketing platform that connects creators with clients for sponsored content, polled US-based TikTok creators on its platform with at least 10,000 followers. It got 200 responses, half from people who rely on influencing as their sole source of income. Out of the respondents, 62 percent said they didn’t think TikTok would be banned by 2025, while the remaining 38 percent said they believed it would be.

    Some creators may be skeptical that a ban will really happen after they watched the Trump White House and Congress try and fail several times to crack down on TikTok over the past few years. The platform has so far only continued to grow more popular in the US, sparking alarm in Silicon Valley over the threat its competition poses. There’s also the possibility TikTok will be sold to a group of American investors—several interested bidders have emerged—though TikTok has made it clear that such an acquisition would be practically impossible.

    Some creators are simply struggling to believe the bizarre situation their favorite app has landed in. “I’m in denial, because I think the TikTok ban is ridiculous,” one anonymous creator told Fohr through its survey. “I think our government has bigger things to worry about than banning a platform where people are allowed to express their views and opinions.”

    Most creators said they haven’t lost business from brands that pay for marketing content on TikTok since the new law was signed: 83 percent of the influencers who responded said their sponsorships have been unaffected. But the rest had seen signs of brands pulling back from the app or at least diversifying their marketing. Some 7 percent said a brand had paused or canceled a campaign they worked on, and 8 percent said a brand had asked to shift a deliverable to another social media platform or at least inquired about such a change.

    Companies may be reluctant to walk away from TikTok because it’s become one of the most popular avenues for consumers to discover new products, particularly from small businesses. Over the past year, TikTok has tried to leverage that influence into a new revenue stream through an ecommerce feature called TikTok Shop. Over 11 percent of US households have made a purchase through TikTok Shop since September 2023, according to credit card transaction data published in April by the research firm Earnest Analytics.

    It doesn’t look as though the passage of the divestiture bill last month prompted people to spend significantly less time on TikTok or avoid the app altogether. The popularity of the platform in US app stores has remained largely consistent over the past month, according to the market-intelligence firm Sensor Tower. And Fohr found that 60 percent of creators said their video views have remained the same, 28 percent said they had seen them fall, and 10 percent reported their engagement increased. These shifts could simply be caused by routine changes TikTok makes to its algorithm, variability of the content that influencers are sharing, or the whims of users consuming videos.

    TikTok’s rise has spurred US tech giants to mimic many of its features, with Google’s YouTube pushing its Shorts format and Meta’s Instagram launching Reels. Fohr’s survey suggests that if creators start leaving TikTok because of uncertainty about the app’s future or a ban, Instagram stands to benefit the most. A clear majority of creators—67 percent—said they saw it as the best alternative for growing their audience, while 22 percent cited YouTube. Only a small fraction pointed to Snapchat, Pinterest, and other platforms.

    Several of the creators, however, said that it’s harder to gain traction on Instagram compared to TikTok, and one noted that Meta’s platform doesn’t offer anything equivalent to TikTok’s Creativity Program, which pays users based on how many views and other engagement metrics their videos receive.

    Across social platforms, the most common way for creators to get paid is by signing deals with brands to make posts featuring their products. But Fohr’s survey also showed the growth of a novel monetization scheme called the TikTok Creative Challenge, which the app launched last year. It allows companies to post requests for creators to make marketing videos that brands can then use on their own channels. Influencers are compensated based on how well their video performs in terms of views and engagement.

    In Fohr’s survey, that type of content, known as UGC, represented the largest TikTok revenue stream for 18 percent of creators. Whatever happens to TikTok in the US, history suggests that it may not be long before its American competitors begin rolling out their own user-generated content initiatives.

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  • AI Is a Black Box. Anthropic Figured Out a Way to Look Inside

    AI Is a Black Box. Anthropic Figured Out a Way to Look Inside

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    Last year, the team began experimenting with a tiny model that uses only a single layer of neurons. (Sophisticated LLMs have dozens of layers.) The hope was that in the simplest possible setting they could discover patterns that designate features. They ran countless experiments with no success. “We tried a whole bunch of stuff, and nothing was working. It looked like a bunch of random garbage,” says Tom Henighan, a member of Anthropic’s technical staff. Then a run dubbed “Johnny”—each experiment was assigned a random name—began associating neural patterns with concepts that appeared in its outputs.

    “Chris looked at it, and he was like, ‘Holy crap. This looks great,’” says Henighan, who was stunned as well. “I looked at it, and was like, ‘Oh, wow, wait, is this working?’”

    Suddenly the researchers could identify the features a group of neurons were encoding. They could peer into the black box. Henighan says he identified the first five features he looked at. One group of neurons signified Russian texts. Another was associated with mathematical functions in the Python computer language. And so on.

    Once they showed they could identify features in the tiny model, the researchers set about the hairier task of decoding a full-size LLM in the wild. They used Claude Sonnet, the medium-strength version of Anthropic’s three current models. That worked, too. One feature that stuck out to them was associated with the Golden Gate Bridge. They mapped out the set of neurons that, when fired together, indicated that Claude was “thinking” about the massive structure that links San Francisco to Marin County. What’s more, when similar sets of neurons fired, they evoked subjects that were Golden Gate Bridge-adjacent: Alcatraz, California Governor Gavin Newsom, and the Hitchcock movie Vertigo, which was set in San Francisco. All told the team identified millions of features—a sort of Rosetta Stone to decode Claude’s neural net. Many of the features were safety-related, including “getting close to someone for some ulterior motive,” “discussion of biological warfare,” and “villainous plots to take over the world.”

    The Anthropic team then took the next step, to see if they could use that information to change Claude’s behavior. They began manipulating the neural net to augment or diminish certain concepts—a kind of AI brain surgery, with the potential to make LLMs safer and augment their power in selected areas. “Let’s say we have this board of features. We turn on the model, one of them lights up, and we see, ‘Oh, it’s thinking about the Golden Gate Bridge,’” says Shan Carter, an Anthropic scientist on the team. “So now, we’re thinking, what if we put a little dial on all these? And what if we turn that dial?”

    So far, the answer to that question seems to be that it’s very important to turn the dial the right amount. By suppressing those features, Anthropic says, the model can produce safer computer programs and reduce bias. For instance, the team found several features that represented dangerous practices, like unsafe computer code, scam emails, and instructions for making dangerous products.

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  • The US Is Forming a Global AI Safety Network With Key Allies

    The US Is Forming a Global AI Safety Network With Key Allies

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    The US is widely seen as the global leader in artificial intelligence, thanks to companies like OpenAI, Google, and Meta. But the US government says it needs help from other nations to manage the risks posed by AI technology.

    At an international summit on AI Safety in Seoul on Tuesday, the US delivered a message from Secretary of Commerce Gina Raimondo announcing that a global network of AI safety institutes spanning the US, UK, Japan, Canada, and other allies will collaborate to contain the technology’s risks. She also urged other countries to join up.

    “Recent advances in AI carry exciting, life-changing potential for our society, but only if we do the hard work to mitigate the very real dangers,” Secretary Raimondo said in a statement released ahead of the announcement. “It is paramount that we get this right and that we do so in concert with our partners around the world to ensure the rules of the road on AI are written by societies that uphold human rights, safety, and trust.”

    The US government has previously said advances in AI create national security risks, including the potential to automate or accelerate the development of bioweapons, or to enable more damaging cyberattacks on critical infrastructure.

    One challenge for the US, alluded to in Raimondo’s statement, is that some national governments may not be eager to fall in line with its approach to AI. She said the US, the UK, Japan, Canada, Singapore, and the European AI Office would work together as the founding members of a “global network of AI safety institutes.”

    The Commerce Department declined to comment on whether China had been invited to join the new AI safety network. Fears that China will use advanced AI to empower its military or threaten the US led first the Trump administration and now the Biden administration to roll out a series of restrictions on Chinese access to key technology.

    The US and China have at least opened a line of communication. A meeting between US President Joe Biden and Chinese President Xi Jinping last November saw the two superpowers agree to hold talks on AI risks and safety. Representatives from the nations met in Switzerland last week to hold the first round of discussions.

    The Commerce Department said that representatives of the new global AI safety network’s members will meet in San Francisco later this year. A blueprint issued by the agency says that the network will work together to develop and agree upon methodologies and tools for evaluating AI models and ways to mitigate the risks of AI. “We hope to help develop the science and practices that underpin future arrangements for international AI governance,” the document says. A commerce department spokesperson said that the network would help nations tap into talent, experiment more quickly, and agree on AI standards.

    The Seoul summit on AI safety this week is co-hosted by the UK government, which convened the first major international meeting on the topic last November. That summit culminated in more than 28 countries including the US, members of the EU, and China signing a declaration warning that artificial intelligence is advancing with such speed and uncertainty that it could cause “serious, even catastrophic, harm.”

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  • It’s Time to Believe the AI Hype

    It’s Time to Believe the AI Hype

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    Folks, when dogs talk, we’re talking Biblical disruption. Do you think that future models will do worse on the law exams?

    If nothing else, this week proves that the rate of AI progress isn’t slowing at all. Just ask the people building these models. “A lot of things have happened—internet, mobile,” says Demis Hassabis, cofounder of DeepMind and now Google’s AI czar, in a post-keynote chat at I/O. “AI is going maybe three or four times faster than those other revolutions. We’re in a period of 25 or 30 years of massive change.” When I asked Google search VP Liz Reid to name a big challenge, she didn’t say it was to keep the innovation going—instead, she cited the difficulty of absorbing the pace of change. “As the technology is early, the biggest challenge is about even what’s possible,” she says. “It’s understanding what the models are great at today, and what they are not great at but will be great at in three months or six months. The technology is changing so fast that you can get two researchers in the room who are working on the same project, and they’ll have totally different views when something is possible.”

    There’s universal agreement in the tech world that AI is the biggest thing since the internet, and maybe bigger. And when non-techies see the products for themselves, they most often become believers too. (Including Joe Biden, after a March 2023 demo of ChatGPT.) That’s why Microsoft is well along on a total AI reinvention, why Mark Zuckerberg is now refocusing Meta to create artificial general intelligence, why Amazon and Apple are desperately trying to keep up, and why countless startups are focusing on AI. And because all of these companies are trying to get an edge, the competitive fervor is ramping up new innovations at a frantic page. Do you think it was a coincidence that OpenAI made its announcement a day before Google I/O?

    Skeptics might try to claim that this is an industry-wide delusion, fueled by the prospect of massive profits. But the demos aren’t lying. We will eventually become acclimated to the AI marvels unveiled this week. The smartphone once seemed exotic; now it’s an appendage no less critical to our daily life than an arm or a leg. At a certain point AI’s feats, too, may not seem magical any more. But the AI revolution will change our lives, and change us, for better or worse. And we haven’t even seen GPT-5 yet.

    Image may contain Label Text Symbol and Sign

    Time Travel

    Sure, I could be wrong about AI. But consider the last time I made such a call. In 1995, I joined Newsweek—the same organ where Clifford Stoll had just dismissed the internet as a hoax—and at the end of the year argued of this new digital medium, “This Changes Everything.” Some of my colleagues thought I’d bought into overblown hype. Actually, reality exceeded my hyperbole.

    In 1995, the Internet ruled. You talk about a revolution? For once, the shoe fits. “In the long run it’s hard to exaggerate the importance of the Internet,” says Paul Moritz, a Microsoft VP. “It really is about opening communications to the masses.” And 1995 was the year that the masses started coming. “If you look at the numbers they’re quoting, with the Web doubling every 53 days, that’s biological growth, like a red tide or population of lemmings,” says Kevin Kelly, executive editor of WIRED. “I don’t know if we’ve ever seen technology exhibit that sort of growth.” In fact, there’s a raging controversy over exactly how many people regularly use the Net. A recent Nielsen survey pegged the number at an impressive 24 million North Americans. During the course of the year the discussion of the Internet ranged from sex to stock prices to software standards. But the most significant aspect of the Internet has nothing to do with money or technology, really. It’s us.

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  • Maven Is a New Social Network That Eliminates Followers—and Hopefully Stress

    Maven Is a New Social Network That Eliminates Followers—and Hopefully Stress

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    “It’s really radical,” Stanley told me of Maven, “We got rid of likes and follows. That’s like insanity.” Some early adopters seem to be on board. “I quit all social media about three years ago because of the hostility, disinformation, brain rot, and advertising,” Benjamin Scott, a philosophy student, says. “A lot of this I believe was an unintended consequence of popularity metrics which tended to boost false, inflammatory, and shocking content.” He says he has been “pleasantly surprised” by Maven.

    Martin Laskowski, a programmer, says he’s been impressed by how well Maven helps users “find conversations in that valuable space between ‘I know and love this topic’ and ‘this seems adjacent enough to my interests, but new, and I probably want to check it out.’”

    Secretan, Maven’s CTO, says that even though discussions of contentious topics can turn tense, they’re typically fruitful. “It’s not just getting in some great one-liner or dunking on the other person, because that just doesn’t get you much on this site.” Without a way to gain personal followers, or an algorithm boosting posts that win attention, there’s not much incentive. Personally, I’ve found conversations to be civil and meaningful on a range of topics—Maven lists interests as varied and specific as “guinea pigs” and “gravitational time dilation”—though one factor is surely the type of person who has joined the network so far, many within a couple degrees of separation from the three founders. (That would also explain why men noticeably outnumber women.)

    As for moderation, users can report posts or other users, and they can mute threads, interests, or users. AI also flags potentially problematic content. “We want to make sure that diverse and open expression remains the prevailing theme,” Stanley says, “so we try not to be heavy-handed.”

    Maven’s network is still small. Stanley declines to disclose any metrics but says he’s already seen some serendipitous interactions in his own feed, although it sounds more rarified than typical online chatter. One researcher posted a link to a paper he had just published titled “Open-Endedness in Synthetic Biology” that was inspired by Stanley and then posted again to say that he had a hobby of inventing new flavors by mixing amino acids and other ingredients. Another user commented saying they were also inventing new flavors as a hobby. Stanley suggested they team up.

    Maven’s cofounders work with a few contractors but no other full-time employees. They say they haven’t settled on a business model yet, but it could involve ads based on people’s declared interests. They’ll need more funding in a few months.

    Williams, the Twitter cofounder, got involved in the project serendipitously, through his appreciation of Stanley’s ideas. “Why Greatness Cannot Be Planned is my favorite book, and I’ve recommended it to like a hundred people,” Williams says. One of those recommendations led to a meeting with Stanley. The development of Maven was itself an exercise in open-ended exploration, as they tossed around ideas, the founders say. Williams says that although he could have offered advice on building social networks, “my guidance most of the time has just been to help them feel their way through.” Other investors include Rana el Kaliouby, CEO and cofounder of Affectiva, Alex Pall of the electronic music duo the Chainsmokers, and VC firm Lux Capital.

    Williams says he doesn’t use X, the platform once known as Twitter, much anymore, as discussions tend to focus on news, which isn’t evergreen. Moros says one of his favorite emergent features of Maven is a phenomenon known as forever threads, in which discussions can span months and keep popping up in people’s feed. One of his favorites collects people’s short, impactful life lessons (Moros’ contribution was “Follow your curiosity”).

    Reddit also hosts long-running discussions focused on specific interests, but its subreddits are somewhat siloed, Stanley says. Reddit has separate forums on NYC and urban planning, but if someone posts on Maven about urban planning in NYC, the AI-added tags will bring together people following both interests. “You can think of it as a self-organizing forum,” he says.

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  • Prepare to Get Manipulated by Emotionally Expressive Chatbots

    Prepare to Get Manipulated by Emotionally Expressive Chatbots

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    The emotional mimicry of OpenAI’s new version of ChatGPT could lead AI assistants in some strange—even dangerous—directions.

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  • OpenAI’s Chief AI Wizard, Ilya Sutskever, Is Leaving the Company

    OpenAI’s Chief AI Wizard, Ilya Sutskever, Is Leaving the Company

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    Ilya Sutskever, cofounder and chief scientist at OpenAI, has left the company. The former Google AI researcher was one of the four board members who voted in November to fire OpenAI CEO Sam Altman, triggering days of chaos that saw staff threaten to quit en masse and Altman ultimately restored.

    Altman confirmed Sutskever’s departure Tuesday in a post on the social platform X. In the months after Altman’s return to OpenAI, Sutskever had rarely made public appearances for the company. On Monday, OpenAI showed off a new version of ChatGPT capable of rapid-fire, emotionally tinged conversation. Sutskever was conspicuously absent from the event, streamed from the company’s San Francisco offices.

    “OpenAI would not be what it is without him,” Altman wrote in his post on Sutskever’s departure. “I am happy that for so long I got to be close to such [a] genuinely remarkable genius, and someone so focused on getting to the best future for humanity.”

    Altman’s post announced that Jakub Pachocki, OpenAI’s research director, would be the company’s new chief scientist. Pachocki has been with OpenAI since 2017.

    In his own post on X, Sutskever acknowledged his departure and hinted at future plans. “After almost a decade, I have made the decision to leave OpenAI. The company’s trajectory has been nothing short of miraculous, and I’m confident that OpenAI will build AGI that is both safe and beneficial” under its current leadership team, he wrote. “I am excited for what comes next—a project that is very personally meaningful to me about which I will share details in due time.”

    Sutskever has not spoken publicly in detail about his role in the ejection of Altman last year, but after the CEO was restored he expressed regrets. “I deeply regret my participation in the board’s actions. I never intended to harm OpenAI,” he posted on X in November.

    Sutskever blazed a trail in machine learning from an early age, becoming a protégé of deep-learning pioneer Geoffrey Hinton at the University of Toronto. With Hinton and fellow grad student Alex Krizhevsky he cocreated an image-recognition system called AlexNet that stunned the world of AI with its accuracy and helped set off a flurry of investment in the then unfashionable technique of artificial neural networks.

    Sustskever later worked on AI research at Google, where he helped establish the modern era of neural-network-based AI. In 2015 Altman invited him to dinner with Elon Musk and Greg Brockman to talk about the idea of starting a new AI lab to challenge corporate dominance of the technology. Sutskever, Musk, Brockman, and Altman became key founders of OpenAI, which was announced in December 2015. It later pivoted its model, creating a for-profit arm and taking huge investment from Microsoft and other backers. Musk left OpenAI in 2018 after disagreeing with the company’s strategy, and he filed a lawsuit against the company in March this year claiming it had abandoned its founding mission.

    Sutskever’s departure leaves just one of the four OpenAI board members who voted for Altman’s ouster with a role at the company. Adam D’Angelo, an early Facebook employee and CEO of Q&A site Quora, was the only existing member of the board to remain as a director when Altman returned as CEO.



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