@paperpaper886: Last week, I discussed the current state and future of AI4Math with a friend from the math department. He said that current AI is already powerful enough as an auxiliary tool, but there is still a long way to go for AI to achieve independent discovery.
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Discussed the current state and future of AI in mathematics. Citing an example, ChatGPT 5.5 Pro autonomously solved the farthest pair problem in high-dimensional computational geometry, which had been stuck for years, demonstrating AI's potential in mathematical discovery.
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Last week, I discussed the current state and future of AI4Math with a friend from the math department. He said that as an assistive tool, today’s AI is already powerful enough, but if we want AI to make independent discoveries, there’s still a long way to go.
Phoenix Yin (@Phoenixyin13): AI autonomously solved an impossible task in high-dimensional computational geometry!
In a new paper released at the end of June, the abstract explicitly states that the proof was originally discovered by ChatGPT 5.5 Pro. Researchers only gave a minimal prompt, and the model autonomously cracked a mathematical no-man’s land that had stumped humans for years.
In high-dimensional space, given n points, find the two farthest apart — the farthest pair problem.
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@vista8: https://x.com/vista8/status/2072191315916538039
Starting with the story of Galois group theory, the article delves into the boundaries of AI's capabilities in mathematics, distinguishing between two types of progress: "connecting lightning" (cross-domain connections) and "building mountains" (creating new frameworks). It analyzes the limitations of the RLVR training method and introduces the concept of "grindability" to explain AI's rapid advancements in mathematics and coding.