AI会因为“全军覆没”而心态崩溃吗？本期，我们将探讨一篇最新论文如何用“全局视野”为AI建立稳定心态。接着，我们会揭示AI如何通过构建“世界模型”学会预判，真正从“知道”走向“行动”。我们还会聊聊，怎样给AI作画模型装上一个“未来探测器”，让它更听话、更有创造力。最后，我们将看到大小模型间“四两拨千斤”的师徒协作模式，并解剖一个反常识的发现：大模型变聪明，靠的可能不是层层递进的深度，而是“人多力量大”的朴素智慧。00:00:41 高手过招，如何不让“一题之失”毁了心态？00:06:19 让AI“涨记性”，它怎样才能不犯“想当然”的错？00:11:40 AI作画不听话？给它装个“未来探测器”00:16:40 AI世界的“四两拨千斤”，如何让小模型拥有大智慧？00:22:02 大模型变聪明的秘密，不是靠层层深入，而是靠人多力量大？本期介绍的几篇论文：[LG] EBPO: Empirical Bayes Shrinkage for Stabilizing Group-Relative Policy Optimization[Meta AI]https://arxiv.org/abs/2602.05165---[CL] Reinforcement World Model Learning for LLM-based Agents[Columbia University & Microsoft Research & Dartmouth College]https://arxiv.org/abs/2602.05842---[LG] Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps[MIT CSAIL & CMU & TU Munich]https://arxiv.org/abs/2602.05993---[CL] MentorCollab: Selective Large-to-Small Inference-Time Guidance for Efficient Reasoning[UIUC & University of Washington]https://arxiv.org/abs/2602.05307---[LG] Inverse Depth Scaling From Most Layers Being Similar[MIT & Harvard University]https://arxiv.org/abs/2602.05970

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

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