Yann LeCun, the computer scientist often dubbed a "godfather of AI" and now founder of AMI Labs, has dismissed Elon Musk's xAI as a "failure" that will be unable to compete at the frontier of artificial intelligence. In a wide-ranging interview with CNBC published June 18, LeCun also warned that the AI industry is risking a "big bubble explosion" if companies do not raise prices and cut costs.
The remarks renew a long-running and increasingly personal feud between two of the field's most prominent figures, while casting fresh doubt over the valuations of the world's largest AI companies. For more context on this story, see our ongoing AI trends.
A Failure Built on Departures
LeCun, who was previously Meta's chief AI scientist, argued that xAI's problems stem from its inability to retain and attract top talent. "xAI is kind of a failure, frankly, because the founding team has departed," he told CNBC. "Elon is now in a position that is very, very difficult for him to kind of hire top people in AI, because he's kind of, you know, not behaved in sort of very good ways toward the previous team."
Over the past year, several of xAI's co-founders have left the organization. In February, Musk merged SpaceX with xAI in a deal that valued the combined entity at approximately $1.25 trillion. According to CNBC, the SpaceX AI segment — which includes xAI — posted a $2.5 billion operating loss in the three months ended March 31.
Despite those losses, xAI has built substantial infrastructure. The company operates its Colossus 1 and Colossus 2 data centers in Memphis, Tennessee, and LeCun noted that xAI rents computing capacity to other companies — including Google and Anthropic — "because that's the only way he can recoup the cost."
"I'm not very positive about the prospect of xAI," LeCun said, adding that he does not expect the company to compete with industry heavyweights OpenAI and Anthropic.
A Warning of a Big Bubble Explosion
Perhaps the broader significance of LeCun's comments lies in his assessment of the industry's economics. Enterprise spending on AI has come under intensifying scrutiny in recent months as the technology proves more expensive to run than many anticipated. OpenAI CEO Sam Altman reportedly said this month, during a company livestream, that AI costs are a "huge issue" and that companies are increasingly discussing how much they are spending.
LeCun framed the problem in stark terms. "The prices are going up of those AI services, but the cost of running them is going down, but not nearly fast enough," he said. "All of those companies are losing money, and basically, the use for most people is funded by the investors. That can't go on for a very long time."
He warned that labs like OpenAI and Anthropic are "going to have to increase prices, they're going to have to cut costs, or there's going to be a big bubble explosion." It is a pointed critique from someone who has spent decades inside the field, and it echoes growing unease among analysts about whether the enormous capital flowing into AI infrastructure will generate commensurate returns.
The Case for World Models
LeCun has long been a vocal critic of the limitations of large language models, the foundation of the current generation of leading AI products. Instead, he advocates for "world models" — systems that aim to build an understanding of how the real or simulated world works, encompassing objects, cause and effect, and actions.
LLMs learn language patterns to predict what comes next, which makes them well-suited to tasks like reasoning and coding. World models take a fundamentally different approach. "I personally don't think we're going to have generalized reliable agentic systems until they're based on world models," LeCun said.
That conviction is the animating force behind AMI Labs, which LeCun founded after departing Meta. In March, the startup raised $1 billion in a funding round at a pre-money valuation of $3.5 billion to pursue world model research. Major AI companies, from Anthropic to OpenAI, are racing to build AI agents — systems capable of carrying out complex tasks autonomously — and LeCun believes the path to reliable agents runs through world models rather than through ever-larger language models alone.
LeCun acknowledged that LLMs remain useful in domains such as coding and mathematics. But he cautioned that "the cost of running those systems with this kind of performance is very high compared to the amount of money that users are ready to pay."
A Long-Running Feud
The exchange is the latest chapter in a years-long spat between LeCun and Musk. The two have clashed over everything from technical approaches to AI to what LeCun has described as Musk's "conspiracy theories" on social media. Musk, for his part, has accused LeCun of being "out of touch with AI for a long time."
SpaceX and xAI were not immediately available for comment when contacted by CNBC.
For the broader market, LeCun's dual warnings — that xAI cannot compete and that the industry's economics are unsustainable — raise uncomfortable questions at a time when AI valuations sit at historic highs. Whether his predictions prove prescient or premature, they add a prominent dissenting voice to a sector that has largely been defined by optimism and runaway investment.
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