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