你有没有想过，除了喂给它更多数据，还有哪些更精妙的法门能让AI变得更聪明？本期我们要聊的几篇最新论文，就揭示了AI的“成长秘籍”：它们把训练AI的视角从“下山”升级为“发射火箭”，为它设计了从通识到专业的“大学课程”，还教会了它预测“未来摘要”的远见，以及在关键时刻“喘口气”慢思考的智慧。今天，就让我们一起看看，这些研究是如何重塑AI的“学习方法论”的。

00:00:33 训练AI，你以为是爬山，其实是开火箭？

00:05:56 AI成长秘籍：多上一门“专业课”

00:11:26 AI模型的终极瘦身术：如何让大象既轻盈又聪明？

00:16:53 AI的远见：不只关心下一个词

00:21:10 AI的“沉思时刻”：快与慢的智慧

本期介绍的几篇论文：

[LG] Optimal Control Theoretic Neural Optimizer: From Backpropagation to Dynamic Programming

[Meta & Georgia Institute of Technology & Apple]

https://arxiv.org/abs/2510.14168

---

[CL] Midtraining Bridges Pretraining and Posttraining Distributions

[CMU]

https://arxiv.org/abs/2510.14865

---

[LG] BitNet Distillation

[Microsoft Research]

https://arxiv.org/abs/2510.13998

---

[LG] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

[FAIR at Meta & CMU]

https://arxiv.org/abs/2510.14751

---

[CL] Catch Your Breath: Adaptive Computation for Self-Paced Sequence Production

[Google DeepMind]

https://arxiv.org/abs/2510.13879