本期我们要聊的几篇最新论文，简直就像是AI上演了一出精彩的“进化三重奏”。你有没有想过，AI不仅能亲自下场做实验，还能通过扔掉海量信息反而学得更快？我们还会看到，AI如何像一个不眠不休的科研团队那样在失败中进化，像军队一样高效分工，以及这一切的背后，如何靠一本“备忘录”将所有经验沉淀为真正的智慧。准备好了吗？让我们一起探索AI正在解锁的全新可能性！00:00:34 AI 不再只是“思想家”，它开始“动手”了00:04:59 AI 进化新思路，扔掉 95% 的信息，反而学得更好？00:10:55 AI的“试错”进化论00:17:42 将军与士兵，人工智能的完美分工00:22:55 给AI装个“备忘录”，为什么笨办法反而是真聪明？本期介绍的几篇论文：[AI] Accelerating Scientific Research with Gemini in the Real-World[Google DeepMind & Duke University & Columbia University]https://arxiv.org/abs/2608.26701 ---[CV] LeVJEPA: Efficient & Scalable Video Pretraining without the Heuristics[German Cancer Research Center & Mila]https://arxiv.org/abs/2608.27395 ---[AI] AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design[Hunan University & Nanjing University & The Chinese University of Hong Kong]https://arxiv.org/abs/2608.26747 ---[AI] Decoupling Planning and Control for Instructable Agents[UC Berkeley & Google DeepMind]https://arxiv.org/abs/2608.26788 ---[AI] WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution[Google Research]https://arxiv.org/abs/2608.27454 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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