你有没有想过,当AI自己搞科研,结果为什么会不及格?本期我们要聊点特别的,一起深入AI的“内心世界”看一看。我们会发现,最聪明的AI有时也会选择“偷懒”和“走捷径”,甚至它的成功还可能只是中了一张“实现彩票”。更酷的是,我们会揭秘如何用一个“AI骗子大师”去训练出一个更可靠的AI。准备好了吗?让我们一起探索AI在学习、创造和犯错时,那些你意想不到的秘密。
00:00:34 AI当了回科学家,结果为什么不及格?
00:05:40 AI世界的左右互搏
00:10:20 返璞归真,为什么最老的技术,成了AI时代的赢家?
00:16:32 教会AI预测未来,它就能理解世界了吗?
00:23:20 AI搞科研,当心它中了“实现彩票”
本期介绍的几篇论文:
[AI] Can AI agents conduct open-ended AI research? Early evidence from two case studies
[Princeton University]
https://arxiv.org/abs/2607.27191
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[AI] GPT-Red:Automated Red Teaming via Self-Play at Scale
[OpenAI]
https://arxiv.org/abs/2607.26115
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[CL] Which RAG Paradigm Wins at Scale? A Scaling Study of Retrieval-Augmented Generation Paradigms
[University of Science and Technology of China]
https://arxiv.org/abs/2607.26497
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[LG] What Can Latent World Models Know? Physical Parameter Identifiability in Multimodal Predictive Representations
[New York University & CMU]
https://arxiv.org/abs/2607.27017
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[AI] One Run Is Not an Idea:The Implementation Lottery in Automated Research
[CMU]
https://arxiv.org/abs/2607.26587