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Matthew Berman· 21 mar 2024Q* Rumors, Energy-Based Models, and Research on ReasoningMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines an anonymous, unverified account of Q* and compares its ideas with published research on teaching language models to reason.
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Lex Fridman· 7 mar 2024Pódcast · 2 vocesIf You Want Human-Level AI, Abandon Generative ModelsInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.
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20VC with Harry Stebbings· 15 may 2023Pódcast · 2 vocesYann LeCun on Open AI Models, Safety and the Future of ResearchInvitado: Yann Lecun · Presenta: Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.
2:45:10ENLex Fridman· 22 ene 2022Pódcast · 2 vocesA Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.Invitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.
1:15:58ENLex Fridman· 31 ago 2019Pódcast · 2 vocesHuman Intelligence Is a Ridiculously Narrow SliverInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why giant nets plus gradient descent broke the textbooks, why "AGI" is the wrong word, and why the next leap is a world model learned like a baby.
11:11ENLex FridmanPódcast · 2 vocesYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralInvitado: Yann Lecun · Presenta: Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
10:16ENLex FridmanPódcast · 2 vocesReasoning Without Logic: Yann LeCun on Teaching Neural Networks to ThinkInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.