00:01:07 AI当学徒：如何把“笨学生”调教成“优化大师”？

00:05:48 AI专家速成指南：换个姿势，我们能造出“神医”吗？

00:10:48 从“大力出奇迹”到“精准打击”：AI的进化新思路

00:14:59 AI的“偏见”：它如何看透纷繁信息，抓住本质？

00:19:50 让AI学会“多想一步”：笨办法里的真智慧

本期介绍的几篇论文：

[LG] CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning  

[DeepReinforce Team]  

https://arxiv.org/abs/2507.14111  

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[CL] Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need  

[Princeton University]  

https://arxiv.org/abs/2507.13966  

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[LG] Reframing attention as a reinforcement learning problem for causal discovery  

[University of Tübingen & University of Amsterdam]  

https://arxiv.org/abs/2507.13920  

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[LG] Provable Low-Frequency Bias of In-Context Learning of Representations  

[University of Michigan & Harvard University]  

https://arxiv.org/abs/2507.13540  

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[LG] Change of Thought: Adaptive Test-Time Computation  

[Google Research & Georgia State University & Maynooth University]  

https://arxiv.org/abs/2507.13569