我们都希望AI越来越聪明，但它究竟是如何“开窍”的呢？本期节目，我们将深入AI的大脑，看看它如何拥有自己的“错题本”进行考场反思，又如何通过“自我暗示”突破学习瓶颈。我们还会探讨AI“思考”背后看不见的成本，以及一种更聪明的奖励机制，如何让AI偏爱攻克难题。最后，看看这一切如何让AI从一个工具，变成我们真正的“科研合伙人”。00:00:32 你的错题本，AI现在也学会了00:05:36 你的下一位科研合伙人，可能不是人00:12:57 为什么AI有时“装傻”，算力背后的隐形成本00:19:22 AI学习卡壳了怎么办？让它自己给自己提个醒00:23:55 AI训练的“差生”偏爱法则本期介绍的几篇论文：[CL] Test-time Recursive Thinking: Self-Improvement without External Feedback[Microsoft Research]https://arxiv.org/abs/2602.03094---[CL] Accelerating Scientific Research with Gemini: Case Studies and Common Techniques[Google Research]https://arxiv.org/abs/2602.03837---[LG] Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs[Microsoft Research & Netflix]https://arxiv.org/abs/2602.02909---[LG] Self-Hinting Language Models Enhance Reinforcement Learning[Microsoft Research]https://arxiv.org/abs/2602.03143---[LG] Maximum Likelihood Reinforcement Learning[CMU & Tsinghua University & Zhejiang University]https://arxiv.org/abs/2602.02710

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

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