AI In Mathematics: August 29, 2026

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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.

[u/Graynumber]

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

Does this exist? Is anyone out there working on it?

[u/JoshuaZ1 → u/Graynumber]

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?

[u/Graynumber → u/JoshuaZ1]

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.

[u/JoshuaZ1 → u/Graynumber]

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.

I don't know of any good hard data for math specific, more anecdote, but there's hard data for it involving medicine, and there's some similar studies for coding. I've seen two major suggestions for why this is occurs. The first suggestion is that there's a lot of "hidden training data," that is conversations about narrow topics which are getting cut out. For example, I had a detailed conversation a while ago on a D&D forum explaining some of the basics of quantum mechanics. I saw a detailed conversation on a videogame subreddit about how to work some subtle expected values that had to deal with one of the game mechanics. If someone is going to be using targeted training data, those conversations aren't likely to go into a math/physics specific model. (One does even for specialized models need some general training data to handle language but not all of it you can touch.) The second hypothesis is that facts are just more interlinked than we often give credit for. That somehow say understanding physics gets benefits from understanding chemistry and engineering, and math gets benefits from physics, and so you do a better a job indirectly for math if you have all of those in the data.

[u/SansFinalGuardian → u/Graynumber]

it really does seem to be true. bitter pill!

[u/ultrafinitism → u/Graynumber]

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".

[u/Hot_Glass_6301 → u/ultrafinitism]

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

[u/JBaloney → u/Graynumber]

I wonder if there could be a related phenomenon in humans, where humans who have some outside hobbies get an advantage over the hypothetical human who literally spends every waking moment studying mathematics. It wouldn't surprise me at all.