As a child, I was very passionate about Go, almost to the point of fanaticism. I didn't play games; I only used one app on my phone called Go Encyclopedia, watching professional players' games day and night. Whenever I had a little free time, I would play online Go, and at night I would sit on my bed, setting up the board and playing against myself. In the morning, I would find myself resting my head on the pieces — at that time, I firmly believed that Go was the crown jewel of all intellectual sports. The moment my faith collapsed was ten years ago when AlphaGo defeated my favorite player, Lee Sedol. All the romance vanished, and Go no longer seemed elegant; it became as uninteresting as chess, Rubik's cubes, and poker. In high school, I became obsessed with physics. A moment that remains vivid in my memory is solving a problem: what does the universe look like when you are traveling at 0.5 times the speed of light? The answer is that under the effects of relativistic light aberration and the Doppler effect, you would see a blue body with a red edge, like a goldfish bowl — I thought nothing in the world could be more beautiful than this. Later, I discovered that outdated mathematical tools greatly limited physicists. Even those much smarter than me might spend their entire lives without finding a unified theory, so I gave up. But the feeling of that white moonlight in physics still lingers; every time I return home, I chat with classmates who studied physics with me back then, indulging in intellectual nostalgia. A few days ago, a PhD student working on high-energy physics at Peking University told me: there is a longitudinal project developing an agent based on Claude Code to reproduce papers, and he has nearly reproduced articles in his own field. Perhaps physics is also about to迎来 its own AlphaGo moment... It's not that AI can master the best methods of scientific research; there's no need to pursue optimization; it just needs to be stronger than humans. The training dataset for AlphaGo included many human players' games. After AlphaGo, its development team, DeepMind, created a much more powerful Go model called AlphaZero — which was developed without using a single drop of human game records, purely derived from first principles. What’s even more frustrating is that DeepMind did not continue to develop a stronger model but instead announced that the Go problem has been completely solved. To destroy you, what does it matter to you?