今天，我们将一起“拆开”AI的大脑，看看做决策的竟然只有8个“员工”？我们还会揭秘AI排行榜的“偏科”陷阱，并为它请来一位完美的“虚拟陪练”和一位全能“秘书”。最后，再用一个简单又奇妙的几何学秘密，看穿AI决策的本质。让我们一同进入AI内部，一探究竟！

00:00:23 AI做决策，到底需要多少“人”帮忙？

00:05:38 AI排行榜的秘密，为什么第一名可能不是你想要的全才？

00:11:01 给AI请个“陪练”，它就能开窍？

00:16:09 给高手配个秘书，怎样才能让他越用越顺手？

00:21:46 AI决策的“保守”秘密

本期介绍的几篇论文：

[CL] Through the Looking Glass: Directly Reading and Writing Transformers
[University of Washington]
https://arxiv.org/abs/2609.10210
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[CL] What Does MMLU Actually Measure? A Psychometric Audit of Difficulty Structure in Aggregate Benchmark Scores
[Stanford University]
https://arxiv.org/abs/2609.09372
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[LG] World-Time Compute with Verified Code World Models
[Quome, Inc.]
https://arxiv.org/abs/2609.09163
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[CL] Osprey: Target-agnostic Pre-training Makes Stronger Drafters in Speculative Decoding
[Together AI]
https://arxiv.org/abs/2609.09338
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[LG] Exact-Form Regret for Gradient Descent, Mirror Descent and Follow-the-Regularized-Leader
[MIT]
https://arxiv.org/abs/2609.09466