Michael Burry, the investor made famous by “The Big Short,” has accused the leaders of major U.S. artificial intelligence companies of using warnings about AI’s potential to destroy humanity to strengthen their own market positions and boost the perception of their power ahead of potential public listings.
Burry’s comments came after Anthropic CEO Dario Amodei called on the AI industry to “slow the pace” of technological development, arguing that risk prevention needs more time to catch up with rapidly advancing AI capabilities.
OpenAI CEO Sam Altman, xAI CEO Elon Musk and Alphabet’s Google DeepMind chief Demis Hassabis subsequently expressed support for Amodei’s position, producing an unusual moment of agreement among leaders whose companies are otherwise competing aggressively to build more capable AI systems.
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Burry, however, sees a different motivation.
“Let’s all take a moment to understand how self-serving it is for OpenAI, Anthropic and other execs of big hyperscalers to talk of slowing things down,” he wrote in a late Sunday post on X.
He laid out four arguments for his view. First, Burry said he does not believe today’s large language models are on a path toward artificial general intelligence, arguing that “LLMs are not AI and won’t be AGI.”
Second, he said a slowdown would benefit established AI companies by limiting the ability of smaller competitors to catch up.
Third, Burry argued that portraying AI as an existential threat contributes to the “hype & puffery” surrounding the technology, which can ultimately support public-market valuations.
Finally, he suggested that calls for a deliberate slowdown could provide “cover for real uncontrollable slowing growth.”
The comments turn the AI safety debate into a question not only of technology and existential risk, but also of corporate incentives.
Burry Sees An IPO Motive Behind AI Safety Warnings
Writing separately on his Substack, Cassandra Unchained, Burry argued that executives at Anthropic and OpenAI are supporting slower AI development partly “to increase the perception of their power before their IPOs.”
His argument is particularly pointed because frontier AI companies have accumulated extraordinary private valuations while spending enormous sums on computing infrastructure, talent and model development. A public offering would expose those valuations to a much broader group of investors, making expectations about future growth more consequential.
Burry has been one of the more prominent skeptics of the financial structure surrounding the AI boom. He has warned about excessive infrastructure investment, aggressive accounting practices, hidden debt, and transactions in which capital effectively circulates among companies within the same AI ecosystem.
Against that backdrop, his suggestion that safety rhetoric could influence AI valuations is consistent with his broader criticism of the sector’s financial model.
Burry also said he does not believe systems such as Anthropic’s Claude or OpenAI’s ChatGPT will develop “true capacity for reason,” arguing that there is therefore little immediate reason to fear an extinction-level outcome from current large language models.
The disagreement is significant because Burry is challenging an argument being advanced by some of the industry’s most influential executives at a moment when concerns about frontier AI capabilities are becoming more public.
Amodei’s call followed warnings from former researchers about the pace at which frontier laboratories are developing increasingly autonomous systems. Former OpenAI and Anthropic researcher Jacob Coxon said the two companies were “racing straight to self-improving superintelligence and gambling with our lives.”
Another Anthropic researcher, Evan Hubinger, said he personally puts the probability that AI could “kill all humans” at more than 10% within the next decade.
Those are individual assessments rather than an established scientific consensus, but they have added to growing scrutiny of the industry’s development race.
Wall Street Is Already Pricing The AI Race
The debate is no longer confined to researchers and technology executives. Investors have begun responding to the possibility that AI development could face greater constraints.
AI-related stocks fell sharply on Monday after the latest warnings. Nvidia, the world’s most valuable public company and one of the central suppliers of the computing infrastructure required to train and operate advanced AI models, fell 3% in premarket trading.
Intel, Micron and SK Hynix also dropped more than 5%.
The reaction illustrates the financial sensitivity of the AI ecosystem to assumptions about continued expansion. Nvidia’s business depends heavily on demand for accelerators used by AI developers and data-center operators. Memory manufacturers such as Micron and SK Hynix have also benefited from the enormous hardware requirements associated with AI infrastructure.
A meaningful slowdown in frontier model development could therefore affect much more than the laboratories themselves. It could ripple through semiconductor manufacturers, data-center operators, cloud providers, networking companies and the energy infrastructure being built to support AI computing.
That helps explain why Burry’s criticism has attracted attention. If the leading AI companies voluntarily slow development, the consequences would extend throughout an industry that has been built around the expectation of rapidly increasing compute demand.
Washington Wants The Opposite
The safety argument is also running into political pressure. President Donald Trump said over the weekend that “very negative forces” were behind what he described as apocalyptic discussions about AI. He said the worst outcome “won’t happen” and emphasized that the United States must beat China in the AI race. That puts Washington’s priorities in direct tension with the most cautious interpretation of Amodei’s proposal.
The U.S. government has strong incentives to preserve its lead over China in advanced AI, while American technology companies have billions of dollars invested in maintaining that lead. Slowing frontier development could reduce some safety risks, but it could also create opportunities for competitors to move ahead.
This is the central problem Burry is highlighting.
A voluntary slowdown only works as a competitive strategy if major players slow together. If OpenAI, Anthropic and other U.S. laboratories restrain themselves while rivals continue advancing, the companies that comply could surrender technological and commercial ground.
At the same time, if every company is encouraged to move as quickly as possible because of competitive pressure, safety research may struggle to keep pace with the capabilities being developed. The result is an uncomfortable conflict between two incentives: the incentive to move fast and capture the economic value of AI, and the incentive to avoid developing systems whose risks may eventually exceed the ability of their creators to control them.
Burry’s intervention adds another layer by questioning whether the companies making the warnings can be trusted to define the appropriate speed themselves. His record gives the argument additional weight among investors. He became famous for correctly betting against the U.S. housing market before the financial crisis and has spent much of the past year publicly criticizing the economics of the AI boom and highlighting what he sees as signs of overinvestment.
But his skepticism does not settle the underlying safety question. Whether current large language models can ultimately produce artificial general intelligence, whether more capable systems could become uncontrollable, and how likely an extinction scenario might be remain deeply contested questions.
What Burry has put squarely on the table is a different question: who benefits when the companies at the center of the AI race tell the world that the race itself needs to slow down?
That question will matter more if Anthropic and other frontier AI laboratories approach the public markets. Investors will have to assess not only the technological claims and safety risks, but also whether the industry’s warnings, growth projections, and competitive strategies are sometimes serving the same corporate interests.