AI如何才能学会自我进化，最终成为自己的师傅？为什么解决顶级难题要靠“AI专家团”，而不是一个超级大脑？本期节目，我们将从几篇最新论文出发，探讨AI如何从别人的失败中汲取智慧，看懂“剩饭”为何难倒英雄汉，并理解“看得懂”与“会动手”之间那道巨大的鸿沟。

00:00:26 那个“笨”徒弟，正在悄悄学会自己当师傅

00:07:02 AI解题的秘密，不是一个大脑，而是一套系统

00:11:44 AI的“偏食症”，为什么聪明的模型更讨厌“剩饭”？

00:17:21 人工智能看得懂，但不会干

00:21:56 如何变得更聪明？答案是，多看看笨蛋是怎么想的

本期介绍的几篇论文：

[LG] The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

[Shanghai Jiao Tong University]

https://arxiv.org/abs/2609.11873

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[AI] An Open Recipe for IMO Gold: Training Nemotron for Olympiad Mathematics

[NVIDIA]

https://arxiv.org/abs/2609.10712

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[LG] Data Scarcity and Model Sparsity: Mixtures-of-Experts Overfit More to Repeated Data

[Stanford University]

https://arxiv.org/abs/2609.11917

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[AI] MindTopo: Can Foundation Models Reason in Topological Space?

[Northwestern University]

https://arxiv.org/abs/2609.11900

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[CL] Negative Self-Distillation: Learning to Reason by Avoiding Flaws

[University of Virginia]

https://arxiv.org/abs/2609.11699