你是否想过，给AI的“私教”偷看标准答案，究竟是作弊还是神操作？为什么机器人模仿完美师傅反而会碰壁，甚至有时需要“闭着眼睛”走路？本期节目，我们将从几篇最新论文出发，揭示AI如何从模仿走向探索，以及强大的模型是如何在你的手机里实现性能飞跃的。让我们一起探寻这些AI“反常识”行为背后的智慧吧！00:00:29 AI界的“陪练”与“私教”00:06:33 机器人学艺，师傅领进门，修行靠自己00:11:55 机器人为什么要“闭着眼睛”走路？00:18:01 你的手机，为什么能越来越“聪明”？00:22:35 高手与笨蛋的分界线，在于如何面对复杂本期介绍的几篇论文：[LG] Le Critique: Privileged Value Functions for LLM Reinforcement Learning[Mistral AI]https://arxiv.org/abs/2608.16739 ---[RO] FetchMan: Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences[University of California, Los Angeles & Allen Institute for AI]https://arxiv.org/abs/2608.17027 ---[RO] Revisiting Open-Loop Execution in Robotics: Toward Reactive, Higher-Performing Policies[MIT & UC Berkeley]https://arxiv.org/abs/2608.15938 ---[LG] FlashAttention for Scalable Vector Architectures[Chalmers University of Technology & University of Glasgow]https://arxiv.org/abs/2608.18656 ---[CV] Falcon Perception-HD: High Density Perception via Reinforcement Learning[Technology Innovation Institute]https://arxiv.org/abs/2608.18881 在小宇宙查看该单集文稿

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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