AI画画写代码，怎样才能告别蛮力，像高手一样把力气用在刀刃上，又像学徒一样得到名师指点，快速开窍呢？它的学习过程到底是充满“顿悟”的跳跃，还是一分耕耘一分收获的苦功？更进一步，当规则完全未知时，AI能像我们玩密室逃脱一样，自己摸索出世界的法则吗？本期节目，我们就从四篇最新论文出发，一起探寻AI从“聪明”走向“智慧”的秘密。

00:00:31 生成AI的“节拍器”，如何把算力用在刀刃上？

00:06:13 AI当码农，如何从“笨徒弟”进化成“老师傅”？

00:12:35 AI学习的秘密，顿悟与苦功，本来就是一回事

00:19:14 AI的下一个考场，在规则未知的世界里摸索

00:24:27 AI养娃，要从胎教开始

本期介绍的几篇论文：

[LG] The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity

[M J. Wainwright, MIT]

https://arxiv.org/abs/2608.13520

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[LG] CAKE: Compiler-Agent Co-Design for Frontier Kernel Evolution

[Z Ye, Y Huang, H Jin, B Hou… (NVIDIA & CMU)]

https://arxiv.org/abs/2608.12629

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[LG] Neural Quadratic Forms: A Unified Minimal Model for Sudden Learning and Scaling Laws

[L Ziyin, Y Xu, T Poggio, I Chuang (MIT & EPFL)]

https://arxiv.org/abs/2608.13335

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[LG] DiG-bench: Discovery in Games

[R M. Battleday, K Sandbrink, J Cullen-Drohan, Z Yan… (Thinking About Thinking)]

https://arxiv.org/abs/2608.12593

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[LG] Synthetic Persona Pretraining: Alignment from Token Zero

[J Minder, V Moskvoretskii, R Singhal, D Jiao,… (EPFL)]

https://arxiv.org/abs/2608.13482