Yann LeCun Raises $1 Billion to Build AI That Understands the Physical World

Advanced artificial intelligence (AMI), a new Paris-based startup co-founded by Yann LeCun, former chief AI scientist at Meta, announced Monday that it has raised more than $1 billion to develop global AI models.

LeCun argues that most human reasoning is based in the physical world, not language, and that global AI models are necessary to develop true human-level intelligence. “The idea that you are going to expand the capabilities of LLM [large language models] to the point that they’re going to have human-level intelligence, it’s completely absurd,” he said in an interview with WIRED.

The funding, which values ​​the startup at $3.5 billion, was co-led by investors including Cathay Innovation, Greycroft, Hiro Capital, HV Capital and Bezos Expeditions. Other notable backers include Mark Cuban, former Google CEO Eric Schmidt, and French billionaire and telecommunications executive Xavier Niel.

AMI (pronounced like the French word for friend) aims to build “a new generation of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe,” the company says in a press release. The startup says it will be global from day one, with offices in Paris, Montreal, Singapore and New York, where LeCun will continue to work as a professor at New York University in addition to leading the startup. AMI will be LeCun’s first commercial venture since leaving Meta in November 2025.

LeCun’s startup represents a bet against many of the world’s largest AI labs like OpenAI, Anthropic and even his former workplace, Meta, who believe the development of LLMs will eventually deliver AI systems with human-level intelligence, or even superintelligence. LLMs have fueled viral products like ChatGPT and Claude Code, but LeCun has been one of the AI ​​industry’s most prominent researchers calling out the limitations of these AI models. LeCun is well known for his outspokenness, but as a pioneer of modern AI who won a Turing Award in 2018, his skepticism carries weight.

LeCun says AMI aims to work with companies in manufacturing, biomedical, robotics and other data-rich sectors. For example, he says AMI could build a realistic global model of an aircraft engine and work with the manufacturer to help it optimize efficiency, minimize emissions or ensure reliability.

AMI was co-founded by LeCun and several executives he worked with at Meta, including the company’s former director of scientific research, Michael Rabbat; the former vice-president of Europe, Laurent Solly; and former Senior Director of AI Research, Pascale Fung. Other co-founders include Alexandre LeBrun, former CEO of AI healthcare startup Nabla, who will serve as AMI’s CEO, and Saining Xie, a former Google DeepMind researcher who will serve as the startup’s chief scientific officer.

The case for global models

LeCun does not reject the overall usefulness of LLMs. He said these AI models are just the latest promising trend in the tech industry, and their success has created a “kind of illusion” among those who build them. “It’s true that [LLMs] “That’s a lot of applications, but it’s not going to lead to human-level intelligence at all.”

LeCun has been working on global models for years at Meta, where he founded the company’s fundamental AI research lab, FAIR. But he’s now convinced it’s best to do his research outside of the social media giant. He says it’s become clear to him that the most powerful applications of the global models will be to sell them to other companies, which doesn’t fit neatly into Meta’s core consumer business.

As global AI models such as Meta’s Jointly Integrative Predictive Architecture (JEPA) have become more sophisticated, “there’s been a shift in Meta’s strategy where it’s had to basically catch up with the industry in LLM and sort of do the same thing as other LLM companies, which is not my interest,” says LeCun. “So in November I went to Mark Zuckerberg and told him. He’s always been very supportive of [world model research]but I told him I could do it faster, cheaper and better outside of Meta. I can share the cost of development with other companies… His response was: OK, we can work together.