As summer fades into fall, many in the tech world are worried about winter. Late last month, a Bloomberg columnist asked “is the AI winter finally upon us?” British newspaper The Telegraph was more definitive. “The next AI winter is coming,” it declared. Meanwhile, social media platform X was filled with chatter about a possible AI winter.
An “AI winter” is what folks in artificial intelligence call a period in which enthusiasm for the idea of machines that can learn and think like people wanes—and investment for AI products, companies, and research dries up. There’s a reason this phrase comes so naturally to the lips of AI pundits: We’ve already lived through several AI winters over the 70-year history of artificial intelligence as a research field. If we’re about to enter another one, as some suspect, it’ll be at least the fourth.
The most recent talk of a looming winter has been triggered by growing concerns among investors that AI technology may not live up to the hype surrounding it—and that the valuations of many AI-related companies are far too highl. In a worst case scenario, this AI winter could be accompanied by the popping of an AI-inflated stock market bubble, with reverberations across the entire economy. While there have been AI hype cycles before, they’ve never involved anything close to the multiple hundreds of billions of dollars that investors have sunk into the generative AI boom. And so if there is another AI winter, it could involve polar vortex levels of pain.
The markets have been spooked recently by comments from OpenAI CEO Sam Altman, who told reporters he thought some venture-backed AI startups were grossly overvalued (although not OpenAI, of course, which is one of the most highly-valued venture-backed startups of all time). Hot on the heels of Altman’s remarks came a study from MIT that concluded that 95% of AI pilot projects fail.
