Why Yann LeCun’s Startup Advanced Machine Intelligence Is Targeting Healthcare

Alex LeBrun, cofounder of medical scribe startup Nabla who LeCun hired to be the CEO of Advanced Machine Intelligence, thinks the startup’s new AI models could start to roll out in a year, with healthcare a major focus area.

In November, Yann LeCun, one of the world’s foremost AI experts, announced he would leave his role as Meta’s chief AI scientist to start his own company, focused on building a new type of AI called world models. He’s now executive chairman of Advanced Machine Intelligence Labs, which is seeking to raise funds at a valuation of some $3.5 billion. But he made a seemingly unusual choice for CEO: Alex LeBrun, cofounder of a health tech startup based in Paris that uses AI to transcribe doctor visits.

That might sound like a niche choice for an AI lab. But it indicates the buzzy company, whose tech attempts to understand the world by learning from videos and spatial data as well as text, will have a significant emphasis on healthcare. Its first announced partnership will be with LeBrun’s company, Nabla.

“Healthcare is my baby, and we know what problems we cannot solve today,” LeBrun said in an interview on the sidelines of the J.P. Morgan Healthcare conference in San Francisco. “We hope that this new branch [of AI] will help us move beyond what we can do today in healthcare.”

LeBrun will give up his CEO role at Nabla, but remain as chairman and chief AI scientist there. He previously worked directly for LeCun at Meta after it acquired a previous company he’d founded. LeBrun told Forbes that a big reason he wanted to become CEO of the new startup was to apply its world models to healthcare.

AMI is also targeting manufacturing and robotics, but healthcare is an important focus area because of the field’s complexity and high stakes. Hopes are high for AI to transform both operations and clinical practice. But the tendency for large language models to hallucinate or make errors is a big potential problem in healthcare, especially on the clinical side where people’s lives are involved. Fixing those hallucinations is something that proponents of world models believe they can address.

With AMI, LeCun is raising big bucks to put that research into practice: The Financial Times previously reported that the new startup has been seeking to raise nearly $600 million (at current Euro-dollar exchange rates). Others have also been developing world models, including Stanford professor Fei-Fei Li, whose World Labs came out of stealth in September 2024 with $230 million in funding at a valuation of more than $1 billion.

“The world in the past five years has become fully obsessed with LLMs. Now we have a hammer, and we see everything as a nail,” LeBrun said. “For some problems, like information retrieval, it is the best technology. But many problems do not fall into this.”

In healthcare, for example, AI scribing (including Nabla’s), clinician support (such as OpenEvidence) and discovering patterns in imaging, such as X-rays, are good uses for existing LLM technology, LeBrun said. But for other, clinical use cases, the accuracy is too low for LLMs to be deployed safely — let alone AI agents that operate autonomously without human oversight. “If you zoom out, it’s just 1% or 5% of the problems,” he said. “Nobody would claim healthcare is working well today.”

AMI plans to work in partnership with companies to bring its world models to real-life problems, though beyond Nabla, specific projects haven’t yet been announced. The French startup has raised $120 million and expects to reach annualized subscription revenue of $100 million in two years. Nabla cofounder Delphine Groll, the company’s chief operating officer, will run that company until a new CEO to replace LeBrun is named. “Alex has always been the AI visionary of the company,” she said.

LeBrun figures that it will take “about one year to get the first things we can use in the product.” The research on world models is already strong, with hundreds of papers published over the past few years alone, he said. “I felt that the time was right given the recent progress of research in world models to apply this to healthcare, so that is what we are about to do with Nabla,” he said.

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