陶哲轩昨晚在 Caltech "Math 2.0" 演讲中表示,仅追求解题的盲目优化现在对数学的长期健康主动有害。他把开放问题比作灯塔,是探索周边数学景观的指引而非终点,尝试过程中的经验往往比最终解答更有价值;用自动化工具过早抵达灯塔会破坏未走路径的探索,不加区分地用 AI 解题还会损害向真实世界应用的迁移。
Terence Tao's slide from the lecture he gave yesterday evening at Caltech “Math 2.0”
AI can now crack open problems that were once out of reach, and he says that is the wrong thing to celebrate on its own.
Basically he says chasing problem-solving alone is hurting math.
“Further blind optimization of problem-solving alone is now actively harmful to the long-term health of mathematics.”
“Contrary to popular opinion (or some of our own marketing), mathematicians are not singularly focused on solving open problems.”
“Particularly in pure mathematics, open problems serve as “lighthouses”: not destinations to be reached in and of themselves, but as useful guides to explore the mathematical landscape around these problems.”
“The lessons learned while attempting to solve these problems — whether they succeed, fail, or achieve partial progress — are often more valuable than the final solution to the problem itself.”
“Reaching these lighthouses prematurely by automated tools can disrupt the exploration of the paths not taken, and sterilize the surrounding field.”
“Indiscriminate use of AI to solve problems in a non-renewable fashion damages the long-term health and progress of the field, as well as safe transfer to messier, real-world applications.”
来源:Rohan Paul · x.com