你有没有想过，我们该如何为AI的高速公路设计智能的交通规则，又该如何教会一颗活的“迷你大脑”摸盲文？如果让AI来炒股，市场会更疯狂还是更理性？本期，我们将从几篇最新的论文出发，揭开AI从一个工具箱进化为发明家，并学会复杂推理的底层设计图。

00:00:26 给AI修路，为什么“车道”越多反而越容易“堵车”？

00:05:32 如果让AI来炒股，它会比你更贪婪吗？

00:11:24 当你的电脑开始用“脑子”摸盲文

00:16:21 你的AI助手，应该是个工具箱，还是个发明家？

00:21:28 AI变聪明的“导航系统”，一份来自底层的设计图

本期介绍的几篇论文：

[CL] mHC: Manifold-Constrained Hyper-Connections

[DeepSeek-AI]

https://arxiv.org/abs/2512.24880

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[AI] Can Generative AI agents behave like humans? Evidence from laboratory market experiments

[College London & CENTAI Institute & Bank of Canada]

https://arxiv.org/abs/2505.07457

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[RO] Encoding Tactile Stimuli for Organoid Intelligence in Braille Recognition

[University of Bristo]

https://arxiv.org/abs/2508.20850

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[AI] Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

[Princeton University & Tsinghua University & Shanghai Jiao Tong University]

https://arxiv.org/abs/2505.20286

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[LG] On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning

[University of California, Los Angeles]

https://arxiv.org/abs/2505.17508