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9 件
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スライド 5 枚22:17EN
Matthew Berman· 2024年3月21日Q* 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.Reasoning & test-time computeモデルと学習AI research+2
スライド 7 枚12:34EN
Matthew Berman· 2024年3月14日Figure 01 and the Path Toward More Capable RobotsMatthew Berman, Lex Fridman, Yann Lecun · Forward FutureMatthew Berman surveys humanoid and other robotics demonstrations, then shares Yann LeCun’s view on the work still needed for general-purpose robots.RoboticsWorld modelsHuman-AI Collaboration+2
2:47:17EN
Lex Fridman· 2024年3月7日ポッドキャスト · 2 人If You Want Human-Level AI, Abandon Generative Modelsゲスト Yann Lecun · ホスト 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.モデルと学習World modelsAGI(汎用人工知能)+3
33:23EN
20VC with Harry Stebbings· 2023年11月24日ポッドキャスト · 11 人AI Leaders Debate Open Models, Pricing and the Future of Searchゲスト Emad Mostaque, Des Traynor, Jeff Seibert, Yann Lecun, Richard Socher, Cris Valenzuela, Douwe Kiela, Tomasz Tunguz, Miles Grimshaw, Christian Lanng · ホスト Harry StebbingsA compilation of separate interviews brings together competing 2023 predictions about model economics, assistants and the largest technology companies.Foundation ModelsOpen-weight modelsAI Strategy+2
1:06:02EN
20VC with Harry Stebbings· 2023年5月15日ポッドキャスト · 2 人Yann LeCun on Open AI Models, Safety and the Future of Researchゲスト Yann Lecun · ホスト Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.AI researchAI SafetyOpen-weight models+2
2:45:10EN
Lex Fridman· 2022年1月22日ポッドキャスト · 2 人A Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.ゲスト Yann Lecun · ホスト 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.モデルと学習World modelsComputer Vision+3
1:15:58EN
Lex Fridman· 2019年8月31日ポッドキャスト · 2 人Human Intelligence Is a Ridiculously Narrow Sliverゲスト Yann Lecun · ホスト 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.モデルと学習機械学習の基礎AI research+3
11:11EN
Lex Fridmanポッドキャスト · 2 人Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not Generalゲスト Yann Lecun · ホスト 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.モデルと学習BenchmarksAGI(汎用人工知能)+3
10:16EN
Lex Fridmanポッドキャスト · 2 人Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Thinkゲスト Yann Lecun · ホスト Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.モデルと学習機械学習の基礎Deep Learning+3