/AI7d ago

Analysis argues AI advancements accelerate human problem-solving, citing post-AlphaGo Go performance and combinatorics breakthroughs

Humans used AI-derived techniques to solve unit distance problems.

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anpaure@anpaure

@polynoamial not true according to a go player, skill rose because people just memorized lines further, starting from move 60 the move accuracy is similar to the past https://www.lesswrong.com/posts/nR3DkyivzF4ve97oM/how-go-players-disempower-themselves-to-ai

Noam Brown@polynoamial

After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.

2:48 AM · May 28, 2026 · 8.2K Views
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Lisan al Gaib@scaling01

True, but does it matter?

Will humans soon be permanently behind, like in Poker, Go and Chess?

It's worth pointing out that this is a bit different. Because language models can actually tell us how and why something works, so maybe the gap won't be as large as in these other domains.

But I still suspect there's a ceiling for what humans can understand. The main bottleneck is working memory. Oh, and the obvious example of that is of course biology. Generally speaking we have a pretty good idea how each individual part, for example in the human body, is working. But we can't really predict the downstream effects of one change. This is a big problem in drug discovery.

I suspect AI will be able to predict downstream effects of drugs much better than we do in a few months/years. Because to me it all seems too similar to what Mythos and GPT-5.5 just did with math and cyber. It's just a scaled up version of that with even more interactions and possible combinations, which AI can keep track of.

Noam Brown@polynoamial

After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.

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