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]
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[AI] Can Generative AI agents behave like humans? Evidence from laboratory market experiments
[College London & CENTAI Institute & Bank of Canada]
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[RO] Encoding Tactile Stimuli for Organoid Intelligence in Braille Recognition
[University of Bristo]
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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]
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[LG] On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning
[University of California, Los Angeles]
![[人人能懂] 从造工具、炒股票到读懂人脑](https://image.xyzcdn.net/FuDP4HpAp8ezgVZMmEel3mblKCmJ.jpg@small)