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スライド 5 枚15:33EN
Matthew Berman· 2025年2月13日Latent Reasoning and Recurrent Depth: Scaling Compute Before the Next TokenMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines a 3.5-billion-parameter research model that repeats internal computations, and asks how it relates to language, planning and chain of thought.Reasoning & test-time computeモデルと学習AI research+2
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
52:06EN
Matthew Berman· 2024年3月16日Yann LeCun on World Models, Open AI and the Path to Advanced IntelligenceMatthew Berman, Yann Lecun, Lex Fridman · Forward FutureMatthew Berman reacts to excerpts from LeCun’s 2024 conversation with Lex Fridman, covering language models, JEPA, robotics, AI safety and economic incentives.World modelsAI researchOpen-weight models+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