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Tag: Ben Horowitz

  • What’s Next for AI? Andreessen Horowitz Founders Share Their Thoughts

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    Stocks of companies tied to artificial intelligence have been hitting stratospheric levels for over a year now, thrilling investors, but also causing concerns about a potential AI bubble. As startups close breathtaking funding rounds, like the $40 billion OpenAI collected in March of this year, fears of an AI bubble are growing – and some say a burst could be even bigger than the dotcom bubble of the late 1990s.

    The bubble theory is hotly debated. Some within the industry say they agree the investment landscape is bloated, including OpenAI co-founded Sam Altman. Other experts, like Goldman Sachs, however, say we’re not in one (yet) – and Fed Chair Jerome Powell has been skeptical of the bubble calls. As that debate rages, investors continue to fund AI startups.

    Few investors are in as deep as Marc Andreessen and Ben Horowitz. Their venture firm, Andreessen Horowitz (commonly called a16z) has sunk billions into the AI space. In April, it was reported the company was in early talks to raise a massive $20 billion AI-focused fund. The two investors recently came together at a16z’s Runtime conferences to talk about where AI can go beyond chatbots.

    Neither was willing to make any specific predictions about AI’s forthcoming capabilities, saying it’s too early to even imagine that. Andreessen likened AI to the personal computer in 1975, noting there was no way at that time to imagine what PCs would be capable of today. However, he expects similar levels of advancement – from a stronger starting point.

    AI, he said, is already approaching levels of human creativity – and while Andreessen would love to see humans continue to have superiority in that area, he thinks it’s unlikely. Tools like OpenAI’s Sora 2 video, for instance, are already capable of creating realistic scenes, animations, and special effects – and the introduction of AI Actress Tilly Norwood has caused an outcry and prompted debate in Hollywood. 

    “I wanna like hold out hope that there is still something special about human creativity,” he said. “And I certainly believe that, and I very much want to believe that. But, I don’t know. When I use these things, I’m like, Wow, they seem to be awfully smart and awfully creative. So I’m pretty convinced that they’re gonna clear the bar.”

    Horowitz agreed, saying that while AI might not currently create at the same level as human artists, whether painters or hip-hop performers, that’s largely due to how little it has learned so far. It’s just a matter of time before it has an equal or superior level of talent. And some artists are already looking to use AI to collaborate, he said.

    “With the current state of the technology, kind of the pre-training doesn’t have quite the right data to get to what you really wanna see, but, you know, it’s pretty good,” he said. “Hip hop guys are interested because it’s almost like a replay of what they did—they took other music and built new music out of it. AI is a fantastic creative tool. It way opens up the palette.”

    While AI can devour as many data sets as programmers throw at it, that doesn’t give the technology situational awareness. It is, in essence, book smarts vs. street smarts. But the robotics field is expanding quickly. Elon Musk and Tesla are working on humanoid robots and Robotics company 1X has already started to take preorders for a $20,000 humanoid robot that will ‘live’ and work around your home.

    Once that technology and AI are blended, Andreessen said, AI will see a significant jump in actionable intelligence.

    “When we put AI in physical objects that move around the world, you’re gonna be able to get closer to having that integrated intellectual, physical experience,” he said. “Robots that are gonna be able to gather a lot more real-world data. And so, maybe you can start to actually think about synthesizing a more advanced model of cognition.”

    While there are plenty of experts who warn the AI market could be in a bubble right now, including OpenAI CEO and co-founder Sam Altman, Horowitz dismisses the idea, saying bubbles occur when supply outstrips demand – and that’s not the case with AI.

    “We don’t have a demand problem right now,” he said. “The idea that we’re going to have a demand problem five years from now, to me, seems quite absurd. Could there be weird bottlenecks that appear, like we don’t have enough cooling or something like that? Maybe. But, right now, if you look at demand and supply and what’s going on and multiples against growth, it doesn’t look like a bubble at all to me.”

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    Chris Morris

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  • Andreessen Horowitz Founders Notice A.I. Models Are Hitting a Ceiling

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    The investment firm was founded by Ben Horowitz and Marc Andreessen in 2009. Photos by Phillip Faraone/Getty Images for WIRED and Paul Chinn/The San Francisco Chronicle via Getty Images

    Despite continuing to bet big on A.I. startups and chip programs, the founders of the venture capital firm Andreessen Horowitz say they’ve noticed a drop off in A.I. model capability improvements in recent years. Two years ago, OpenAI’s GPT-3.5 model was “way ahead of everybody else’s,” said Marc Andreessen, who co-founded Andreessen Horowitz alongside Ben Horowitz in 2009, on a podcast released yesterday (Nov. 5). “Sitting here today, there’s six that are on par with that. They’re sort of hitting the same ceiling on capabilities,” he added.

    That’s not to say the investment firm doesn’t have faith in the new technology. One of the most aggressive investors in the A.I. space, Andreessen Horowitz earlier this year earmarked $2.25 billion in funding for A.I.-focused applications and infrastructure and has led investments in notable companies including Mistral AI, a French startup founded by former DeepMind and Meta (META) researchers, and Air Space Intelligence, an aerospace company using A.I. to enhance air travel.

    Despite their embrace of the new technology, Andreessen and Horowitz concede there are growth limitations. In the case of OpenAI’s models, the difference in capability growth between its GPT-2.0, GPT-3 and GPT-3.5 models compared to the difference between GPT-3.5 and GPT-4 show that “we’ve really slowed down in terms of the amount of improvement,” said Horowitz.

    One of the primary challenges for A.I. developers has been a global shortage of graphics processing units (GPUs), the chips that power A.I. models. OpenAI CEO Sam Altman last week cited needs to allocate compute as causing the company to “face a lot of limitations and hard decisions” about what projects they focus on. Nvidia, the leading GPU maker, has previously described the shortage as making clients “tense” and “emotional.”

    In response to this demand, Andreessen Horowitz recently established a chip-lending program that provides GPUs to its portfolio companies in exchange for equity. The firm reportedly has been working on building a stockpile chip cluster of 20,000 GPUs, including Nvidia’s. However, chips aren’t the only aspect of compute that is of concern, according to Horowitz, who pointed to the need for more powering and cooling across the data centers housing GPUs. “Once they get chips we’re not going to have enough power, and once we have the power we’re not going to have enough cooling,” he said on yesterday’s podcast.

    But compute needs might not actually be the largest barrier when it comes to improving A.I. model capabilities, according to the venture capital firm. It’s the availability of training data needed to teach A.I. models how to behave that is increasingly becoming a problem. “The big models are trained by scraping the internet and pulling in all human-generated training data, all-human generated text and increasingly video and audio and everything else, and there’s just literally only so much of that,” said Andreessen.

    Between April of 2024 and 2023, 5 percent of all data and 25 percent of data from the highest quality sources was restricted by websites cracking down on the use of their text, images and videos in training A.I., according to a recent study from the Data Provenance Initiative.

    The issue has become so large that major A.I. labs are “hiring thousands of programmers and doctors and lawyers to actually handwrite answers to questions for the purpose of being able to train their A.I.’s—it’s at that level of constraint,” added Andreessen. OpenAI, for example, has a “Human Data Team” that works with A.I. trainers on gathering specialized data to train and evaluate models. And numerous A.I. companies have begun working with startups like Scale AI and Invisible Tech that hire human experts with specialized knowledge across medicine, law and other areas to help fine-tune A.I. model answers.

    Such practices fly in the face of fears relating to A.I.-driven unemployment, according to Andreessen, who noted that the dwindling supply of data has led to an unexpected A.I. hiring boom to help train models. “There’s an irony to this.”

    Andreessen Horowitz Founders Notice A.I. Models Are Hitting a Ceiling

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    Alexandra Tremayne-Pengelly

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