In the field of artificial intelligence, renowned scientist Yann LeCun is about to launch a new company, which has attracted widespread attention. The new company, named Advanced Machine Intelligence Labs (AMI Labs), is planned to be officially established in January next year, with a target valuation of 3 billion euros (approximately 24.7 billion Chinese yuan). During his last days at Meta, driven by his passion for "world models," LeCun has chosen to take the open-source path and maintain cooperation with his former employer, Meta.
AMI Labs will focus on LeCun's long-standing advocacy for "world model" research. LeCun believes that current mainstream autoregressive large language models (LLMs) have logical flaws, as they can only predict text based on statistical probabilities, without truly understanding the laws of the physical world. He has repeatedly warned that continuing down this path would be a "dead end" toward artificial general intelligence (AGI). In contrast, AMI Labs plans to use a new technology called JEPA (Joint Embedding Prediction Architecture), which aims to understand and predict the world through "abstraction" and "planning," striving to achieve a higher level of intelligence.

Notably, LeCun himself will not serve as CEO of AMI Labs. The role will be taken over by his former subordinate — Alexandre LeBrun, founder of the medical AI company Nabla. LeBrun has a deep connection with LeCun, having worked together with him for three years at Meta's FAIR lab. Under LeCun's leadership, LeBrun gained rich experience. As he transitions into a commercial operations-focused CEO, it signals that AMI Labs will form a "dual-core structure" where LeCun focuses on internal research while LeBrun handles external business operations.
Despite being 65 years old and facing the choice of retirement, LeCun still chooses to move forward. In a recent interview, he stated that he still has a mission to "enhance human intelligence." The establishment of AMI Labs represents his latest adventure in the field of artificial intelligence, aiming to abandon the shortcuts of current large models and delve deeper into the real challenges of understanding the physical world.
