你有没有想过，当AI把全世界的书都“读完”了，它该如何变得更聪明？本期节目，我们将从五篇最新论文出发，揭晓AI的奇妙“进阶之路”：看它如何成为自己的老师，如何亲手绘制新的科学地图，甚至在资源耗尽时组建一支“虚拟专家团”，最终实现从速度到创造力的终极飞跃！

00:00:25 AI训练的内卷，自己监督自己

00:05:23 AI科学家的新玩法，发现，原来是升级地图

00:11:26 当数据喂到头，聪明的大脑该怎么练？

00:17:15 机器人教练的终极难题，如何凭空造师傅？

00:23:25 从“一步到位”到“条条大路通罗马”，AI生成的新思路

本期介绍的几篇论文：

[LG] Self-Distilled Policy Gradient

[University of California, Los Angeles & Princeton University]

https://arxiv.org/abs/2606.04036

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[LG] Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence

[MIT]

https://arxiv.org/abs/2606.01444

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[LG] q0: Primitives for Hyper-Epoch Pretraining

[Q Labs & Princeton University]

https://arxiv.org/abs/2606.03938

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[RO] GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors

[NVIDIA]

https://arxiv.org/abs/2606.05160

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[LG] Strong Stochastic Flow Maps

[University of Bath & AITHYRA]

https://arxiv.org/abs/2606.01086