Call it the end of the beginning of the A.I. boom.

Since mid-March, the financial pressure on several signature artificial intelligence start-ups has taken a toll. Inflection AI, which raised $1.5 billion but made almost no money, has folded its original business. Stability AI has laid off employees and parted ways with its chief executive. And Anthropic has raced to close the roughly $1.8 billion gap between its modest sales and enormous expenses.

The A.I. revolution, it is becoming clear in Silicon Valley, is going to come with a very big price tag. And the tech companies that have bet their futures on it are scrambling to figure out how to close the gap between those expenses and the profits they hope to make somewhere down the line.

This problem is particularly acute for a group of high-profile start-ups that have raised tens of billions of dollars for the development of generative A.I., the technology behind chatbots such as ChatGPT. Some of them are already figuring out that competing head-on with giants like Google, Microsoft and Meta is going to take billions of dollars — and even that may not be enough.

“You can already see the writing on the wall,” said Ali Ghodsi, chief executive of Databricks, a data warehouse and analysis company that works with A.I. start-ups. “It doesn’t matter how cool it is what you do — does it have business viability?”

While plenty of money has been burned in other tech booms, the expense of building A.I. systems has shocked tech industry veterans. Unlike the iPhone, which kicked off the last technology transition and cost a few hundred million dollars to develop because it largely relied on existing components, generative A.I. models cost billions to create and maintain. The cutting-edge chips they need are expensive and in short supply. And every query of an A.I. system costs far more than a simple Google search.

Investors have poured $330 billion into about 26,000 A.I. and machine-learning start-ups over the past three years, according to PitchBook, which tracks the industry. That’s two-thirds more than the amount they spent funding 20,350 A.I. companies from 2018 through 2020.


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