你有没有想过，两个顶尖AI在“囚徒困境”里，竟然会不约而同地选择信任彼此？大模型又是如何像继承“传家宝”一样，瞬间读懂小模型的记忆？甚至，机器人和AI自己，也学会了拥有“节奏感”和使用“错题本”来不断进化。本期节目，我们就从几篇最新论文出发，一起探寻AI世界里那些反直觉的智慧。

00:00:27 AI的信任游戏，为什么聪明的它，会选择合作而非背叛？

00:05:45 AI 家族的“传家宝”，大模型如何继承小模型的“记忆”？

00:10:40 机器人也需要“节奏感”？

00:15:58 AI也需要一个“错题本”？

本期介绍的几篇论文：

[AI] A game theory for foundation models shows new paths to rational cooperation through similarity inference

[Google]

https://arxiv.org/abs/2608.03958

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[LG] Cross-Model KV Cache Transfer in LLM Families: A Closed-Form Linear Mapping for Prefill Reuse

[NVIDIA]

https://arxiv.org/abs/2608.03893

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[RO] Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution

[Microsoft Research Asia & Peking University]

https://arxiv.org/abs/2608.03483

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[CL] FLARE: Few-shot Learning-based Adaptive Reflective Engine

[Microsoft]

https://arxiv.org/abs/2608.02919