Tag: fast forward

  • The Fear That Inspired Elon Musk and Sam Altman to Create OpenAI

    The Fear That Inspired Elon Musk and Sam Altman to Create OpenAI

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    Elon Musk last week sued two of his OpenAI cofounders, Sam Altman and Greg Brockman, accusing them of “flagrant breaches” of the trio’s original agreement that the company would develop artificial intelligence openly and without chasing profits. Late on Tuesday, OpenAI released partially redacted emails between Musk, Altman, Brockman, and others that provide a counternarrative.

    The emails suggest that Musk was open to OpenAI becoming more profit-focused relatively early on, potentially undermining his own claim that it deviated from its original mission. In one message Musk offers to fold OpenAI into his electric-car company Tesla to provide more resources, an idea originally suggested by an email he forwarded from an unnamed outside party.

    The newly published emails also imply that Musk was not dogmatic about OpenAI having to freely provide its developments to all. In response to a message from chief scientist Ilya Sutskevar warning that open sourcing powerful AI advances could be risky as the technology advances, Musk writes, “Yup.” That seems to contradict the arguments in last week’s lawsuit that it was agreed from the start that OpenAI should make its innovations freely available.

    Putting the legal dispute aside, the emails released by OpenAI show a powerful cadre of tech entrepreneurs founding an organization that has grown to immense power. Strikingly, although OpenAI likes to describe its mission as focused on creating artificial general intelligence—machines smarter than humans—its founders spend more time discussing fears about the rising power of Google and other deep-pocketed giants than excited about AGI.

    “I think we should say that we are starting with a $1B funding commitment. This is real. I will cover whatever anyone else doesn’t provide,” Musk wrote in a missive discussing how to introduce OpenAI to the world. He dismissed a suggestion to launch by announcing $100 million in funding, citing the huge resources of Google and Facebook.

    Musk cofounded OpenAI with Altman, Brockman, and others in 2015, during another period of heady AI hype centered around Google. A month before the nonprofit was incorporated, Google’s AI program AlphaGo had learned to play the devilishly tricky board game Go well enough to defeat a champion human player for the first time. The feat shocked many AI experts who had thought Go too subtle for computers to master anytime soon. It also showed the potential for AI to master many seemingly impossible tasks.

    The text of Musk’s lawsuit confirms some previously reported details of the OpenAI backstory at this time, including the fact that Musk was first made aware of the possible dangers posed by AI during a 2012 meeting with Demis Hassabis, cofounder and CEO of DeepMind, the company that developed AlphaGo and was acquired by Google in 2014. The lawsuit also confirms that Musk disagreed deeply with Google cofounder Larry Page over the future risks of AI, something that apparently led to the pair falling out as friends. Musk eventually parted ways with OpenAI in 2018 and has apparently soured further on the project since the wild success of ChatGPT.

    Since OpenAI released the emails with Musk this week, speculation has swirled about the names and other details redacted from the messages. Some turned to AI as a way to fill in the blanks with statistically plausible text.

    “This needs billions per year immediately or forget it,” Musk wrote in one email about the OpenAI project. “Unfortunately, humanity’s future is in the hands of [redacted],” he added, perhaps a reference to Google cofounder Page.

    Elsewhere in the email change, the AI software—like some commentators on Twitter—guessed Musk had forwarded arguments that Google had a powerful advantage in AI from Hassabis.

    Whoever it was, the relationships on display in the emails between OpenAI’s cofounders have since become fractured. Musk’s lawsuit seeks to force the company to stop licensing technology to its primary backer, Microsoft. In a blog post accompanying the emails released this week, OpenAI’s other cofounders expressed sorrow at how things had soured.

    “We’re sad that it’s come to this with someone whom we’ve deeply admired,” they wrote. “Someone who inspired us to aim higher, then told us we would fail, started a competitor, and then sued us when we started making meaningful progress towards OpenAI’s mission without him.”



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  • The AI Culture Wars Are Just Getting Started

    The AI Culture Wars Are Just Getting Started

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    Google apologized after its Gemini model caused offense by being too “woke.” Expect political fights over AI’s values to worsen as the technology becomes more capable.

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  • Intel’s CEO Says AI Is the Key to the Company’s Comeback

    Intel’s CEO Says AI Is the Key to the Company’s Comeback

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    When veteran engineer and executive Pat Gelsinger returned to Intel as CEO in 2021, the once-great chipmaker was in a slump. After failing to adapt to the mobile era and then missing several steps in cutting-edge microprocessor manufacturing, it was now also falling behind in supplying chips to feed the tech industry’s growing hunger for artificial intelligence.

    With optimism that at times seemed reckless, Gelsinger promised that Intel would make an epic comeback. He vowed to shake up its sleepy corporate culture, refocus on core engineering, and deliver a revitalized manufacturing plan that would put rivals TSMC and Samsung on notice.

    This week, Gelsinger declared Intel’s comeback plan well and truly on track. He announced a rebrand of the company’s “foundry” business, which manufactures chips designed by other companies, saying that Intel’s latest manufacturing process would later this year yield silicon chips as efficient and capable as ones from TSMC. Microsoft is the first big customer for this new chipmaking technology—a key coup for Intel as it tries to convince the industry that it can offer competitive products suited to the age of AI.

    Pat Gelsinger spoke to WIRED senior writer Will Knight about Intel’s AI reboot over Zoom from his home in Santa Clara, California. The conversation has been lightly edited for length and clarity.

    Will Knight: You announced this week that Intel will relaunch its business that manufactures chips on behalf of other companies as an “AI-era system foundry.” What does that mean?

    Pat Gelsinger: I began Intel’s strategy two plus years ago, and for the company, generative AI has been this unexpected surge. This has been the land of Nvidia, but we’re the one company that actually has the opportunity to participate in 100 percent of the AI market. We know how to connect up networks and memory and [provide] supply chains and all of these other elements that we’re finding customers are super excited to take advantage of.

    Speaking of the AI surge, what did you make of reports suggesting OpenAI’s CEO Sam Altman wants to raise $7 trillion to develop and manufacture chips needed to guarantee progress in AI?

    My first reaction was, that’s a mind-bogglingly big number. And then I had to do the math. Today, the biggest AI models were generated on about 10,000 GPUs. The belief is there that we probably need to be 10 million for the biggest AI models that get produced in the future.

    We’re already saying we may spend a couple billion dollars training the most advanced models today. Plus, the math in the $7 trillion also includes power and data centers.

    This week you said Intel is on track to deliver its new “18A” manufacturing process, which will compete with TSMC’s best offerings. What else are you doing to regain an edge?

    The whole industry is pursuing this next generation transistor, what we call ribbonFET. I think everybody’s [asking] who’s going to produce the next best transistor on the planet.

    But the thing that everybody is giving us credit for is backside power, this new way of delivering power into the device, which gives you better current resistance performance, but it’s also improving the density of the chip. That means the same wafer, instead of producing 100 chips, can produce 120 chips. It’s a huge value proposition.

    You announced Microsoft as a customer of your foundry business. But Intel previously fell behind the competition in this market. How will you convince customers that things are different this time?

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  • Some People Actually Kind of Love Deepfakes

    Some People Actually Kind of Love Deepfakes

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    A month ago, the consulting company Accenture presented a potential client an unusual and attention-grabbing pitch for a new project. Instead of the usual slide deck, the client saw deepfakes of several real employees standing on a virtual stage, offering perfectly delivered descriptions of the project they hoped to work on.

    “I wanted them to meet our team,” says Renato Scaff, a senior managing director at Accenture who came up with the idea. “It’s also a way for us to differentiate ourselves from the competition.”

    The deepfakes were generated—with employees’ consent—by Touchcast, a company Accenture has invested in that offers a platform for interactive presentations featuring avatars of real or synthetic people. Touchcast’s avatars can respond to typed or spoken questions using AI models that analyze relevant information and generate answers on the fly.

    “There’s an element of creepy,” Scaff says of his deepfake employees. “But there’s a bigger element of cool.”

    Deepfakes are a potent and dangerous weapon of disinformation and reputational harm. But that same technology is being adopted by companies that see it instead as a clever and catchy new way to reach and interact with customers.

    Those experiments aren’t limited to the corporate sector. Monica Arés, executive director of the Innovation, Digital Education, and Analytics Lab at Imperial College Business School in London, has created deepfakes of real professors that she hopes could be a more engaging and effective way to answer students’ questions and queries outside of the classroom. Arés says the technology has the potential to increase personalization, provide new ways to manage and assess students, and boost student engagement. “You still have the likeness of a human speaking to you, so it feels very natural,” she says.

    As is often the case these days, we have AI to thank for this unraveling of reality. It has long been possible for Hollywood studios to copy actors’ voices, faces, and mannerisms with software, but in recent years AI has made similar technology widely accessible and virtually free. Besides Touchcast, companies including Synthesia and HeyGen offer businesses a way to generate avatars of real or fake individuals for presentations, marketing, and customer service.

    Edo Segal, founder and CEO of Touchcast, believes that digital avatars could be a new way of presenting and interacting with content. His company has developed a software platform called Genything that will allow anyone to create their own digital twin.

    At the same time, deepfakes are becoming a major concern as elections loom in many countries, including the US. Last month, AI-generated robocalls featuring a fake Joe Biden were used to spread election disinformation. Taylor Swift also recently became a target of deepfake porn generated using widely available AI image tools.

    “Deepfake images are certainly something that we find concerning and alarming,” Ben Buchanan, the White House Special Adviser for AI, told WIRED in a recent interview. The Swift deepfake “is a key data point in a broader trend which disproportionately impacts women and girls, who are overwhelmingly targets of online harassment and abuse,” he said.

    A new US AI Safety Institute, created under a White House executive order issued last October, is currently developing standards for watermarking AI-generated media. Meta, Google, Microsoft, and other tech companies are also developing technology designed to spot AI forgeries in what is becoming a high-stakes AI arms race.

    Some political uses of deepfakery, however, highlight the dual potential of the technology.

    Imran Khan, Pakistan’s former prime minister, delivered a rallying address to his party’s followers last Saturday despite being stuck behind bars. The former cricket star, jailed in what his party has characterized as a military coup, gave his speech using deepfake software that conjured up a convincing copy of him sitting behind a desk and speaking words that he never actually uttered.

    As AI-powered video manipulation improves and becomes easier to use, business and consumer interest in legitimate uses of the technology is likely to grow. The Chinese tech giant Baidu recently developed a way for users of its chatbot app to create deepfakes for sending Lunar New Year greetings.

    Even for early adopters, the potential for misuse isn’t entirely out of mind. “There’s no question that security needs to be paramount,” says Accenture’s Scaff. “Once you have a synthetic twin, you can make them do and say anything.”



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  • AI Tools Like GitHub Copilot Are Rewiring Coders’ Brains. Yours May Be Next

    AI Tools Like GitHub Copilot Are Rewiring Coders’ Brains. Yours May Be Next

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    Many people—like, say, journalists—are understandably antsy about what generative artificial intelligence might mean for the future of their profession. It doesn’t help that expert prognostications on the matter offer a confusing cocktail of wide-eyed excitement, trenchant skepticism, and dystopian despair.

    Some workers are already living in one potential version of the generative AI future, though: computer programmers.

    “Developers have arrived in the age of AI,” says Thomas Dohmke, CEO of GitHub. “The only question is, how fast do you get on board? Or are you going to be stuck in the past, on the wrong side of the ‘productivity polarity’?”

    In June 2021, GitHub launched a preview version of a programming aid called Copilot, which uses generative AI to suggest how to complete large chunks of code as soon as a person starts typing. Copilot is now a paid tool and a smash hit. GitHub’s owner, Microsoft, said in its latest quarterly earnings that there are now 1.3 million paid Copilot accounts—a 30 percent increase over the previous quarter—and noted that 50,000 different companies use the software.

    Dohmke says the latest usage data from Copilot shows that almost half of all the code produced by users is AI-generated. At the same time, he claims there is little sign that these AI programs can operate without human oversight. “There’s clear consensus from the developer community after using these tools that it needs to be a pair-programmer copilot,” Dohmke says.

    Copilot’s power is in how it abstracts away complexity for a programmer trying to work through a problem, Dohmke says. He likens that to the way modern programming languages hide fiddly details that earlier, lower-level languages required coders to wrangle. Dohmke adds that younger programmers are particularly accepting of Copilot, and that it seems especially helpful in solving novice coding problems. (This makes sense if you consider that Copilot learned from reams of code posted online, where solutions to beginner problems outnumber examples of abstruse and rarified coding craft.)

    “We’re seeing the evolution of software development,” Dohmke says.

    None of that means demand for developers’ labor won’t be altered by AI. GitHub research in collaboration with MIT shows that Copilot allowed coders faced with relatively simple tasks to complete their work, on average, 55 percent more quickly. This increase in productivity suggests that companies could get the same work done with fewer programmers, but companies could use those savings to spend more on labor in other projects.

    Even for non-coders, these findings—and the rapid uptake of Copilot—are potentially instructive. Microsoft is developing AI Copilots, as it calls them, designed to help write emails, craft spreadsheets, or analyze documents for its Office software. It even introduced a Copilot key to the latest Windows PCs, its first major keyboard button change in decades. Competitors like Google are building similar tools. GitHub’s success might be helping to drive this push to give everyone an AI workplace assistant.

    “There’s good empirical evidence and data around the GitHub Copilot and the productivity stats around it,” Microsoft’s CEO, Satya Nadella, said on the company’s most recent earnings call. He added that he expects similar gains to be felt among users of Microsoft’s other Copilots. Microsoft has created a site where you can try its Copilot for Windows. I confess it isn’t clear to me how similar the tasks you might want to do on Windows are to the ones you do in GitHub Copilot, where you use code to achieve clear objectives.

    There are other potential side effects of tools like GitHub Copilot besides job displacement. For example, increased reliance on automation might lead to more errors creeping into code. One recent study claimed to find evidence of such a trend—although Dohmke says that it reported only a general increase in mistakes since Copilot was introduced, not direct evidence that the AI helper was causing an increase in errors. While this is true, it seems fair to worry that less experienced coders might miss errors when relying on AI help, or that the overall quality of code might decrease thanks to autocomplete.

    Given Copilot’s popularity, it won’t be long before we have more data on that question. Those of us who work in other jobs may soon find out whether we’re in for the same productivity gains as coders—and the corporate upheavals that come with them.

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  • I Tested a Next-Gen AI Assistant. It Will Blow You Away

    I Tested a Next-Gen AI Assistant. It Will Blow You Away

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    The most famous virtual valets around today—Siri, Alexa, and Google Assistant—are a lot less impressive than the latest AI-powered chatbots like ChatGPT or Google Bard. When the fruits of the recent generative AI boom get properly integrated into those legacy assistant bots, they will surely get much more interesting.

    To get a preview of what’s next, I took an experimental AI voice helper called vimGPT for a test run. When I asked it to “subscribe to WIRED,” it got to work with impressive skill, finding the correct web page and accessing the online form. If it had access to my credit card details I’m pretty sure it would have nailed it.

    Although hardly an intelligence test for a human, buying something online on the open web is a lot more complicated and challenging than the tasks that Siri, Alexa, or the Google Assistant typically handle. (Setting reminders and getting sports results are so 2010.) It requires making sense of the request, accessing the web to find the correct site, then correctly interacting with the relevant page or forms. My helper correctly navigated to WIRED’s subscription page and even found the form there—presumably impressed by the prospect of receiving all WIRED’s entertaining and insightful journalism for only $1 a month—but fell at the final hurdle because it lacked a credit card. VimGPT makes use of Google’s open source browser Chromium that doesn’t store user information. My other experiments showed that the agent is, however, very adept at searching for funny cat videos or finding cheap flights.

    VimGPT is an experimental open-source program built by Ishan Shah, a lone developer, not a product in development, but you can bet that Apple, Google, and others are doing similar experiments with a view to upgrading Siri and other assistants. VimGPT is built on GPT-4V, the multimodal version of OpenAI’s famous language model. By analyzing a request it can determine what to click on or type more reliably than text-only software can, which has to attempt to make sense of the web by untangling messy HTML. “A year from now, I would expect the experience of using a computer to look very different,” says Shah, who says he built vimGPT in only a few days. “Most apps will require less clicking and more chatting, with agents becoming an integral part of browsing the web.”

    Shah is not the only person who believes that the next logical step after chatbots like ChatGPT is agents that use computers and roam the Web. Ruslan Salakhutdinov, a professor at Carnegie Mellon University who was Apple’s director of AI research from 2016 to 2020, believes that Siri and other assistants are in line for an almighty AI upgrade. “The next evolution is going to be agents that can get useful tasks done,” Salakhutdinov says. Hooking Siri up to AI like that powering ChatGPT would be useful, he says, “but it will be so much more impactful if I ask Siri to do stuff, and it just goes and solves my problems for me.”

    Salakhutdinov and his students have developed several simulated environments designed for testing and honing the skills of AI helpers that can get things done. They include a dummy ecommerce website, a mocked-up version of a Reddit-like message board, and a website of classified ads. This virtual testing ground for putting agents through their paces is called VisualWebArena.

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