你有没有想过，为什么AI能从互联网的海量垃圾中炼出真金，而不是变成一个只会死记硬背的书呆子？当AI犯错时，我们是该让它闭嘴，还是有更聪明的办法让它学会“谦逊”？本期节目，我们将通过几篇最新的AI论文，揭示AI如何像一个并行专家团队一样解决难题，又是如何受困于一个惊人简洁的“瓶颈定律”，带你一窥AI大脑中那些优雅而深刻的学习法则。

00:00:33 最优解的密码，藏在并行的智慧里

00:05:55 AI怎么才能不说谎？答案藏在一种人类智慧里

00:10:13 AI训练场上的“隐形杀手”

00:16:52 AI怎么从一堆垃圾里炼出真金？

00:23:33 增长的瓶颈定律，规模不是优势，弱点才是关键

本期介绍的几篇论文：

[LG] Black-box optimization of noisy functions with unknown smoothness

[INRIA Lille & Google DeepMind]

https://arxiv.org/abs/2605.02462

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[CL] Hallucinations Undermine Trust; Metacognition is a Way Forward

[Google Research & Tel Aviv University]

https://arxiv.org/abs/2605.01428

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[LG] Generalized Distributional Alignment Games for Unbiased Answer-Level Fine-Tuning

[Google Research]

https://arxiv.org/abs/2605.02435

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[LG] A Theory of Generalization in Deep Learning

[Stanford University]

https://arxiv.org/abs/2605.01172

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[LG] A Theory of Saddle Escape in Deep Nonlinear Networks

[UC Berkeley]

https://arxiv.org/abs/2605.01288