你有没有想过，AI画画也能像我们一样进行“刻意练习”，通过精准对比找到最佳进步方向吗？面对复杂变化的世界，为什么“慢半拍”的决策反而更准确？我们还将揭示AI训练中“又快又好”的秘密课程表，探讨项目延期背后的沟通艺术，并告诉你，你对AI的每一次追问，都在如何悄悄地训练它。本期，让我们一起从几篇最新论文中，窥探AI正在学习的那些“人间智慧”。00:00:34 AI绘画的“刻意练习法”00:05:25 做对事情，只需一个“时间差”00:11:31 快与好，为什么不能兼得？AI训练中的“学霸心法”00:17:02 为什么你的项目总在延期？答案可能不在技术，在沟通00:22:27 你的每一次追问，都在悄悄训练AI本期介绍的几篇论文：[CV] Finite Difference Flow Optimization for RL Post-Training of Text-to-Image Models [NVIDIA & UC Berkeley] https://arxiv.org/abs/2603.12893 ---[LG] A Reduction Algorithm for Markovian Contextual Linear Bandits [University of California, Los Angeles & Meta] https://arxiv.org/abs/2603.12530 ---[LG] Curriculum Sampling: A Two-Phase Curriculum for Efficient Training of Flow Matching [Stanford University] https://arxiv.org/abs/2603.12517 ---[LG] Optimizing Task Completion Time Updates Using POMDPs [Stanford University & Rensselaer Polytechnic Institute] https://arxiv.org/abs/2603.12340 ---[CL] Aligning Language Models from User Interactions [ETH Zurich] https://arxiv.org/abs/2603.12273

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

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