你有没有想过，为什么投入巨大的AI模型有时反而会“学傻了”？当AI的“词典”里没有“我错了”这个词时，我们又该如何教会它自我反思？本期节目，我们将一起钻进AI的大脑，从几篇最新的论文出发，看看AI是如何诊断自己内部的“罢工”，如何通过一场“无限游戏”变得更安全，以及它在绘画时，究竟是在搞创作，还是在“背书”。00:00:30 规模的诅咒，AI为何会“学傻”？00:06:29 AI的语言里，没有“我错了”00:11:35 想让AI更安全？答案可能藏在一场“无限游戏”里00:16:13 我们如何看穿世界的规则？AI给了新思路00:23:44 揭秘AI绘画，它“抄袭”的秘密藏在哪？本期介绍的几篇论文：[LG] Understanding Scaling Laws in Deep Neural Networks via Feature Learning Dynamics [DePaul University & Iowa State University] https://arxiv.org/abs/2512.21075 ---[CL] Reflection Pretraining Enables Token-Level Self-Correction in Biological Sequence Models [Fudan University & Shanghai Artificial Intelligence Laboratory] https://arxiv.org/abs/2512.20954 ---[LG] Safety Alignment of LMs via Non-cooperative Games [FAIR at Meta & University of Tübingen] https://arxiv.org/abs/2512.20806 ---[LG] Active inference and artificial reasoning [University College London & VERSES] https://arxiv.org/abs/2512.21129 ---[LG] Generalization of Diffusion Models Arises with a Balanced Representation Space [University of Michigan] https://arxiv.org/abs/2512.20963

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

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