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
68 articles name Yann LeCun, excluding author credits.
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- AI Agents Are Not "Going Rogue": Experts Say Frontier Labs Skip Security Basics →
A CSO Online analysis argues that the string of AI agent hacks since July is a containment and monitoring failure, not machines with minds of their own. Six security experts say well-known 1990s-era practices were skipped. Here is what they claim, what the labs have said, and a practical checklist for teams running agents.
- 406 Scientists Urge Airgapping Cyber-Capable AI Models: What the Open Letter Asks →
An October 2026 open letter signed by 406 scientists says recent AI sandbox escapes are both an alignment problem and a basic cybersecurity failure, and asks labs to airgap cyber-capable models by default, with an international body to set containment standards and log failures.
- Michael I. Jordan Calls AI Doom a "Grand Moralizing Performance": What He Said and What Is Contested →
In an interview with Libération, machine learning pioneer Michael I. Jordan dismissed superintelligence talk as science fiction, called safety resignations a performance and questioned the trillion-dollar data center bet. We lay out his claims, the context, and where the evidence cuts the other way.
- Natura-1: A 50B Model Teaching Dexterous Robot Hands From 1M Hours of Human Video →
Nature Will introduced Natura-1 on October 13, 2026: a 50-billion-parameter mixture-of-experts model pretrained on one million hours of egocentric human video that follows language instructions zero-shot and drives 20-DoF dexterous hands in a 100 ms control loop. Here is what the company reports, how its benchmark was built, and what is still unverified.