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Google DeepMind· @GoogleDeepMind · X·· 2026-03-13
AI 导读

AlphaGo十周年之际,DeepMind科学家Thore Graepel与Pushmeet Kohli探讨了从游戏AI到科学发现工具的演进路径。对话回顾了Move 37与Move 78等标志性时刻的技术突破,阐述AlphaGo如何延伸至蛋白质折叠、矩阵乘法优化及算法发现领域。讨论还涉及AI生成发现的验证机制、数学家的协作角色,以及游戏智能对解决复杂科学问题的方法论变革。

正文 · 原文

What does it take to build AI for scientific discovery? 🧠

To celebrate 10 years of AlphaGo, @ThoreG and @Pushmeet joined @fryrsquared on our podcast to discuss how mastering games has paved the way for it to help solve more complex problems. ↓

00:00 The AlphaGo match
02:15 Why Go?
10:58 Lee Sedol vs AlphaGo
14:58 Move 37
20:55 Move 78
24:38 Reaction from the Go community
30:45 Never before seen footage
32:05 AlphaGo to protein folding
34:00 Matrix multiplication
38:00 AlphaGo and algorithmic discovery
41:40 How to verify new discoveries
47:38 Role of mathematicians
51:43 Would we be here without AlphaGo?

来源:Google DeepMind · x.com