Sam Altman's goal of raising about $7 trillion to make artificial-intelligence chips tells a story beyond his borderline-insane ambitions. First, the infrastructure needed to build AI has become exorbitantly expensive. Second, most of that value is still — still! — held by a handful of large technology companies — and the oligopoly is only going to get worse.
For all the competition that was spurred by the launch of ChatGPT in late 2022, and the flurry of new startups that jumped into the hyped-up generative AI market, most of those new players will likely fold or be folded into the incumbents over the next year or so. The costs of doing business are too high for them to survive on their own.
Take Sasha Haco, the chief executive officer of Unitary, which scans videos on social media for rule-breaking content. It would cost her company 100 times more than it charges clients to subscribe to OpenAI's video-scanning AI tools. So Unitary makes its own models, which is a high-wire balancing act in itself. Her startup needs to rent access to those rare AI chips via cloud vendors like Microsoft Corp. and Amazon.com Inc.'s Amazon Web Services. Those chips have doubled in price since 2020, Haco says, and they're difficult to reserve. “We've had times when we can't get access to what we need and so we have to pay 10 times the price,” she told me.
Unitary makes it work, but Haco admits that no generative AI startup has figured out how to run a low-cost business at scale, at least not in the same way that large tech firms have. Another AI founder in San Francisco tells me that some of his peers who have to rent AI chips and cloud computing find that the only way they make money “is if people don't use the product.”
“The best analogy is electricity,” says Ronald Ashri, CEO of startup Dialogue.ai, which creates tailored chatbots for regulated industries. “You're plugged into a foundation model and that is your electricity, and you are consuming it constantly. The consumption
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