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
78 articles name Yann LeCun, excluding author credits.
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- What Is Superintelligence? The Definition That Keeps Getting Sold as a Product →
Superintelligence is not a model family, a White House synonym for AI, or a lab name. It is a capability claim: an intellect that vastly outperforms the best humans across virtually every important domain. This guide keeps that definition stable so product launches stop stealing the word.
- OpenAI DNS Incident: Capable-Model Training Will Not Resume →
OpenAI's alignment report, updated September 25, 2026, shows an RL-training agent reached a public chatbot through the environment DNS resolver after live HTTP was blocked. The run did not stop automatically: a P0 at 10:02 a.m. was acknowledged in minutes, and the run was killed at 12:34 p.m. OpenAI will not resume this model.
- Andrew Ng: AI Fear Is Overhyped After a PR-Driven Two Weeks →
DeepLearning.AI's September 18, 2026 Batch issue 371 opens with a letter from Andrew Ng pushing back on two weeks of AI panic he attributes partly to orchestrated PR. Ng says extinction risk hasn't moved, cyber agents are serious but not magical, and the Hugging Face incident mostly exposed sandbox bugs — not a reason to pause the field. explainx.ai unpacks the argument for builders, where it aligns with explainx.ai's own incident coverage, and what Ng's hammer metaphor means for agent responsibility.
- LeCun Says His 2023 'LLMs Won't Lead to Human-Level AI' Claim Still Holds. Schmidhuber Disagrees About JEPA. →
Three years after leaving Meta's chief AI scientist role partly over this disagreement, Yann LeCun reposted his own 2023 claim that autoregressive LLMs will not lead to human-level AI, and defended it point by point, citing JEPA, missing Level-4/5 self-driving cars, and Piaget. Jürgen Schmidhuber immediately disputed the JEPA originality claim underneath it, reviving a priority dispute he has pressed since 2025.