AI的“内心世界”到底是什么样的？本期我们将一起打开AI的“黑箱”，看看它脑中的概念是不是像一张清晰的地图；它又是如何像玩乐高一样，用旧知识拼出新世界的？当AI学画画时，我们该给它请一位“博学”还是“懂行”的老师？又该怎样为它修一条又快又好的创作高速路？最后，我们还将探讨，如何让机器通过“抬杠”的方式，反过来帮我们理清自己的主观想法。00:00:35 驯服“黑箱”：AI世界的一条极简法则00:05:30 拼凑“旧知识”，创造“新世界”00:10:22 AI绘画的“老师”，聪明和懂行哪个更重要？00:15:48 造物者的新工具：AI画画怎样才能又快又好？00:21:10 如何让机器学会你的“个人口味”？本期介绍的几篇论文：[LG] Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality[CMU]https://arxiv.org/abs/2512.10720---[LG] Learning by Analogy: A Causal Framework for Composition Generalization[CMU & Amazon]https://arxiv.org/abs/2512.10669---[CV] What matters for Representation Alignment: Global Information or Spatial Structure?[Adobe Research & ANU]https://arxiv.org/abs/2512.10794---[LG] Bidirectional Normalizing Flow: From Data to Noise and Back[MIT]https://arxiv.org/abs/2512.10953---[CV] Agile Deliberation: Concept Deliberation for Subjective Visual Classification[Google Research]https://arxiv.org/abs/2512.10821

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

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