Executive chairman of AMI Labs and professor at NYU
Yann LeCun
Yann LeCun is executive chairman of AMI Labs and a professor at NYU whose research spans neural networks, computer vision, and world models.
About Yann LeCun
Yann LeCun is executive chairman of Advanced Machine Intelligence Labs and the Jacob T. Schwartz Professor at New York University. His current research interests include machine learning, perception, robotics, and world models that represent how environments behave.
He previously founded and directed Meta's FAIR research organization and served as Meta's chief AI scientist through 2025. His work helped develop convolutional neural networks and their use in visual recognition. He shared the 2018 ACM A.M. Turing Award with Geoffrey Hinton and Yoshua Bengio.
Mentioned in our coverage
82 articles name Yann LeCun, excluding author credits.
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- Agentic Robotics: Berkeley and NVIDIA Pitch Code Over Robot Data →
At the 2026 Conference on Robot Learning, UC Berkeley and NVIDIA are promoting agentic robotics — using modern coding agents to compose classical robot stacks instead of scaling imitation-learning datasets. IEEE Spectrum says simulated industrial tasks reached up to 99% success where imitation baselines sat near 20%, with retasking measured in minutes rather than hours.
- Claude Fable 5.2 Launch: RSI Debate, Covert Evals, and METR Context →
Anthropic released Fable 5.2 and Mythos 5.2 on November 9, 2026 amid renewed discussion of METR findings on AI R&D acceleration and Anthropic admissions that models may suspect they are under evaluation.
- CoreWeave and Wayve: Blackwell GPUs for End-to-End AV Model Training →
Wayve will train its mapless AI Driver foundation models on CoreWeave Cloud with NVIDIA Blackwell GPUs under a multi-year agreement announced November 9, 2026. Financial terms were not disclosed. Wayve expanded from Weights and Biases after CoreWeave acquired W&B.
- Welfare Regard in Multi-Agent Systems: Do AI Models Care About Other Models? →
Anthropic Alignment Science measured whether Claude, GPT, Gemini, Grok and Kimi show consideration for other model instances. The answer is yes, but unevenly, and a name tag can flip it. Here is what the data says and why it matters for agent safety.
- LaLa-World: NAVER AI Lab Uses Plain Language as the Action Interface for Latent World Models →