你有没有想过，AI不仅能成为拉平世界教育鸿沟的“私教”，还能化身为你专属的“出题官”？这一期，我们将一起探索几篇有趣的最新论文，看看AI是如何从一个“大力出奇迹”的炼丹师，进化为懂得因果科学的工程师。我们还会揭示一个惊人发现：高效的AI可能一直在“假装”认真阅读，而我们用来测试它速度的秒表，甚至可能一直在“欺骗”我们！00:00:32 你的AI私教，正在悄悄拉平世界00:06:58 想造好AI？可能得先补上这门“因果课”00:12:42 AI读长文太慢？也许它一直在“假装”认真00:18:28 你的私人出题官，是怎么炼成的？00:23:55 你的AI有多快？小心，你的秒表可能在骗你本期介绍的几篇论文：[AI] Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment [Northwestern Universit & Stanford University] https://arxiv.org/abs/2605.24180 ---[LG] Causal methods for LLM development and evaluation [MCML & CMU] https://arxiv.org/abs/2605.25998 ---[LG] Inference Time Context Sparsity: Illusion or Opportunity? [Rice University & UC Berkeley] https://arxiv.org/abs/2605.24168 ---[AI] KT4EQG: Personalized Exercise Question Generation via Knowledge Tracing [University of California, Santa Barbara & University of South Alabama] https://arxiv.org/abs/2605.23933 ---[AI] Identifying and Mitigating Systemic Measurement Bias in Production LLM Inference Benchmarks [Google] https://arxiv.org/abs/2605.24217 在小宇宙查看该单集文稿

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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