本期节目,我们将一起探索AI智能的几种迷人形态。一个从没上过网的AI,如何靠“顿悟”来解题?一个摇摆不定的AI,如何被调教得“心中有谱”?一个笨学生,又是如何通过一套“教育学”秘籍,成为推理高手的?最后,我们还会聊聊如何给AI团队“动手”纠错,并用一把尺子精确量出它的“记忆深度”。准备好了吗?让我们一起出发!
00:00:31 造一个聪明的AI,需要喂它整个互联网吗?
00:07:16 告别左右摇摆:如何让机器学会有个“准星”?
00:12:27 如何把一个“笨学生”调教成解题高手?
00:19:59 别再当事后诸葛亮,试试“动手”来纠错
00:25:43 你的AI有多健忘?我们终于有了一把尺子
本期介绍的几篇论文:
[LG] ARC-AGI Without Pretraining
[CMU]
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[LG] Average-reward reinforcement learning in semi-Markov decision processes via relative value iteration
[University of Alberta]
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[CL] On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
[CMU]
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[AI] DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
[Microsoft & Chinese Academy of Sciences]
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[LG] Quantifying Memory Use in Reinforcement Learning with Temporal Range
[MIT]
![[人人能懂] AI的五项修炼:顿悟、定力、阶梯、纠错与度量](https://image.xyzcdn.net/FuDP4HpAp8ezgVZMmEel3mblKCmJ.jpg@small)