今天，我们要深入AI的“内心世界”，去探寻几个颠覆性的问题：聪明的AI，是该学会“胸有成竹”的规划，还是“选择性失忆”的智慧？我们该如何教会一个AI坦然承认“我不知道”，甚至让它比“学霸”更可靠？最新几篇论文，将带我们从AI的“顿悟”规律和推理模式中，找到这些问题的答案。00:00:28 AI的“顿悟”，它如何学会把“走一步看一步”变成“胸有成竹”？00:06:42 为什么说，聪明的AI要学会“选择性失忆”？00:13:03 AI为什么总在“卡关”和“顿悟”之间横跳？00:19:26 如何让一个“学渣”AI，比“学霸”更靠谱？00:25:26 从终点出发，如何让AI学会“开窍”本期介绍的几篇论文：[LG] Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning[Google]https://arxiv.org/abs/2512.20605---[CL] ABBEL: LLM Agents Acting through Belief Bottlenecks Expressed in Language[UC Berkeley]https://arxiv.org/abs/2512.20111---[LG] Saddle-to-Saddle Dynamics Explains A Simplicity Bias Across Neural Network Architectures[University College London]https://arxiv.org/abs/2512.20607---[LG] Mitigating LLM Hallucination via Behaviorally Calibrated Reinforcement Learning[ByteDance Seed]https://arxiv.org/abs/2512.19920---[LG] Learning to Reason in LLMs by Expectation Maximization[Adobe Research & KAIST]https://arxiv.org/abs/2512.20169

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

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