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