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We often wonder if AI can truly teach itself to become smarter. It's a question that feels like it's straight out of science fiction, but for the first time, we have a scientifically proven answer. In this video, we'll dive into the groundbreaking mathematical theory that demonstrates how a Transformer AI can, in fact, "bootstrap" its own intelligence, teaching itself to solve reasoning problems of ever-increasing length. But this is not a story of infinite, runaway growth. We will also explore the rigorous, provable limits to this self-improvement, uncovering the precise boundaries defined by the structure of the problem, the accumulation of error, and the finite capacity of the model itself. Prepare to move beyond the hype and into the real science of self-learning AI. all rights w/ authors: "Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization" Yu Huang∗† Zixin Wen∗‡ Aarti Singh‡ Yuejie Chi§ Yuxin Chen† from † Department of Statistics and Data Science, Wharton School, University of Pennsylvania. ‡ Machine Learning Department, Carnegie Mellon University. § Department of Statistics and Data Science, Yale University. #aireasoning #airesearch #scienceexplained