[人人能懂] AI的系统之美：当“设计”比“天才”更重要

00:01:37 你的 AI，是“记性好”还是“真会学”？

00:06:19 管好AI的“注意力”：一个“分而治之”的智慧 

00:10:22 造个“世界”给AI：为什么光看视频还不够？ 

00:16:51 AI团队管理的终极难题：既要、又要、还要，怎么办？ 

00:21:45 想把AI训练好？别等“秋后算账” 

今天介绍的五篇论文：

[LG] Memory Mosaics at scale

[New York University & FAIR, Meta Inc]

https://arxiv.org/abs/2507.03285

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[CL] RAT: Bridging RNN Efficiency and Attention Accuracy in Language Modeling

[CLAIRE, EPFL & Google DeepMind]

https://arxiv.org/abs/2507.04416

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[LG] Critiques of World Models

[CMU]

https://arxiv.org/abs/2507.05169

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[LG] Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards

[Stanford University]

https://arxiv.org/abs/2507.03041

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[LG] Discrete Diffusion Trajectory Alignment via Stepwise Decomposition

[Stanford University & Caltech]

https://arxiv.org/abs/2507.04832