AI godfather Yann LeCun calls Elon Musk's xAI a failure, says it cannot match Anthropic and OpenAI

Yann LeCun has called Elon Musk's xAI a failure and questioned its ability to challenge OpenAI and Anthropic. He also warned that heavy AI spending and weak economics could trigger a wider industry correction.

In Short

• Several co-founders and senior xAI members have left over the past year
• LeCun said hiring leading AI researchers has become harder for Musk
• He argued vast data centres alone may not close the competitive gap

Yann LeCun has delivered a blunt assessment of Elon Musk’s AI venture xAI, calling it a “failure” and questioning whether it can keep up with rivals such as OpenAI and Anthropic. LeCun, often referred to as one of the godfathers of AI for his pioneering work in the field, made the remarks during an interview with CNBC. His comments add another chapter to a years-long public disagreement between the AI researcher and Musk, who have frequently clashed over the future of artificial intelligence and the direction of the industry.

The criticism comes at a time when competition among AI companies is intensifying. While OpenAI and Anthropic continue to attract users, investment and top talent, xAI is trying to establish itself as a serious challenger with massive computing infrastructure and ambitious plans. LeCun did not hold back when discussing Musk’s AI company.

“XAI is kind of a failure, frankly, because the founding team has” departed, he said.

According to LeCun, the departure of several key figures from xAI has left the company in a difficult position. He argued that attracting leading AI researchers has become increasingly challenging for Musk.

“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,” LeCun said.

Over the past year, multiple co-founders and senior members of xAI have exited the company. Despite those departures, Musk has continued to invest heavily in AI infrastructure. Earlier this year, xAI was merged with SpaceX in a deal that valued the combined business at around $1.25 trillion.

LeCun also suggested that xAI’s enormous computing facilities may not be enough to close the gap with its competitors. He pointed to the company’s large data centre operations and claimed that renting computing capacity to outside firms has become an important way to recover costs.

“I'm not very positive about the prospect of xAI,” LeCun said, adding that he does not expect the company to compete successfully against OpenAI and Anthropic.

Warning of an AI spending bubble

LeCun's criticism was not limited to xAI. He also expressed concern about the economics of the wider AI industry.

The race to build more capable AI systems has led companies to spend billions of dollars on data centres, specialised chips and the computing power needed to keep their models running. According to LeCun, investors are currently helping keep the industry moving forward, but that situation may not last forever.

“The prices are going up of those AI services, but the cost of running them is going down, but not nearly fast enough. And so 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 right?” he said.

LeCun said the industry cannot depend on investor funding indefinitely, adding that AI companies may eventually need to charge more for their services, reduce costs, or find a clearer path to profitability. If that does not happen, LeCun believes the sector could face a painful correction.

“They’re going to have to increase prices, they’re going to have to cut costs, or there’s going to be a big bubble explosion,” he said.

LeCun has long argued that the current generation of large language models, which power many popular AI chatbots, has limitations. Instead, he believes future progress will depend on so-called “world models,” systems designed to better understand how the real world works through objects, actions and cause-and-effect relationships.

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