EP20: Yann LeCun

Yann LeCun – Why LLMs Will Never Get Us to AGI "The path to superintelligence - just train up the LLMs, train on more synthetic data, hire thousands of people to school your system in post-training, invent new tweaks on RL-I think is complete bullshit. It's just never going to work." After 12 years at Meta, Turing Award winner Yann LeCun is betting his legacy on a radically different vision of AI. In this conversation, he explains why Silicon Valley's obsession with scaling language models is a dead end, why the hardest problem in AI is reaching dog-level intelligence (not human-level), and why his new company AMI is building world models that predict in abstract representation space rather than generating pixels. Timestamps (00:00:14) – Intro and welcome (00:01:12) – AMI: Why start a company now? (00:04:46) – Will AMI do research in the open? (00:06:44) – World models vs LLMs (00:09:44) – History of self-supervised learning (00:16:55) – Siamese networks and contrastive learning (00:25:14) – JEPA and learning in representation space (00:30:14) – Abstraction hierarchies in physics and AI (00:34:01) – World models as abstract simulators (00:38:14) – Object permanence and learning basic physics (00:40:35) – Game AI: Why NetHack is still impossible (00:44:22) – Moravec's Paradox and chess (00:55:14) – AI safety by construction, not fine-tuning (01:02:52) – Constrained generation techniques (01:04:20) – Meta's reorganization and FAIR's future (01:07:31) – SSI, Physical Intelligence, and Wayve (01:10:14) – Silicon Valley's "LLM-pilled" monoculture (01:15:56) – China vs US: The open source paradox (01:18:14) – Why start a company at 65? (01:25:14) – The AGI hype cycle has happened 6 times before (01:33:18) – Family and personal background (01:36:13) – Career advice: Learn things with a long shelf life (01:40:14) – Neuroscience and machine learning connections (01:48:17) – Continual learning: Is catastrophic forgetting solved? Music: "Kid Kodi" — Blue Dot Sessions — via Free Music Archive — CC BY-NC 4.0. "Palms Down" — Blue Dot Sessions — via Free Music Archive — CC BY-NC 4.0. Changes: trimmed About The Information Bottleneck is hosted by Ravid Shwartz-Ziv and Allen Roush, featuring in-depth conversations with leading AI researchers about the ideas shaping the future of machine learning.