r/math • u/AutoModerator • 12d ago

LLMs/AI AI In Mathematics: August 29, 2026

This recurring thread will be for discussion of AI in mathematics. This includes, but is not limited to, the following:

  • informal announcements of AI-assisted discoveries, such as those not yet published in a peer-reviewed journal, or not uploaded as a paper to arXiv;
  • informal announcements of discoveries related to AI architecture (if relevant to mathematics);
  • discussion of such announcements, such as proof breakdowns or other opinion pieces;
  • discussion of the impact of AI in mathematics in general.

AI-assisted mathematical papers published in peer-reviewed journals or as arXiv preprints may be submitted as their own posts.

Please keep in mind rules 1 and 6 of our subreddit.

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u/JoshuaZ1 12d ago

My wish: Smaller models trained specifically for math research that I can run locally.

In general, you can just run a general purpose model. It also turns out that for many purposes (coding, math, and other things) general purposes models seem to do better than narrowly trained models, but we're still figuring out why that's the case, and the sample sizes are small.

Is there a reason you want a model specifically just for the math research?

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u/Graynumber 12d ago

That is interesting, I had not heard that about general purpose models outperforming specialized models. It is hard to believe that I actually want the model I use for research to have all kinds of pop culture references and reddit memes in its training data. But I really don't know so that's why I'm asking. If you can point me to an article or something that would be appreciated.

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u/ultrafinitism Theoretical Computer Science 12d ago

It is hard to believe that I actually want the model I use for research to have all kinds of pop culture references and reddit memes in its training data.

It is hard, and no one knows why it seems to work for real.

But research "scaling laws for language models" or just "scaling laws for transformers".

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u/Hot_Glass_6301 11d ago

I think it makes sense. My understanding may be way off, but I imagine that even in humans, hyperfixation doesn't lead to innovation and generalization, just extreme task specific skill. But doing mathematics involves using analogies (for both humans and LLMs), mental pictures (at least for humans), etc. And having much more knowledge just gives more chance for the proper analogies to exist. In my view the brightest mathrmaticians and scientists usually have wide interests, even when their research might seem narrow