The first surprise of this afternoon was finally finding an informed and sensible discussion of the implications of AI agents for hep-th research, in the form of a twitter thread by stringking42069.
The second was learning from the twitter thread about Xi Yin’s ongoing project to have GPT 5.5 write a QFT textbook under his supervision. The past week there had been rumors that he was hired by OpenAI. If he’s now on their payroll, what he’s getting paid to do presumably is this textbook, which is a very active ongoing project.
The current state of the textbook is at this github repository. I don’t see a pdf anywhere there, but you can get the tex files by cloning the repository with
git clone https://github.com/xiyin137/QFT
and then tex’ing
monograph/tex/main.tex
He’s working on this right now, with latest changes 6 minutes ago. What I downloaded produced a 3527 page pdf document.
I’ve just skimmed through the thing, and it’s quite fascinating, raising a host of questions. This is clearly a work in progress, on its way to a document with tens of thousands of pages (or more…). Also, it’s undoubtedly the first of many such projects to come. I know from experience that writing a textbook is a huge effort, and AI agents very plausibly could take over a lot of the work. So, one set of questions is about what the future of textbooks, specifically QFT textbooks, will be.
The first obvious comment is that this document is useless as a “textbook”, in the sense of something one could use to learn the subject from. No one is going to learn QFT in any useful sense by trying to read these thousands of pages. Sections of it might be useful to experts in the same way that a badly-written research monograph is.
When I wrote a QM (and some elementary QFT) textbook, a big part of the experience was the following process. Starting from a certain conception in my mind of what the right way to think about a topic was, I’d start writing, and then after a while realize that there was a better, clearer way to think about the topic, so lots of material had to be thrown out or completely rewritten. Sometimes I came to this realization because things were getting too complicated and it became clear there was a simpler way. Sometimes the new insight came from getting stuck on a calculation: at one point, days spent chasing signs that wouldn’t match led to understanding that I was thinking about the dual of the vector space I should have been thinking about.
For an AI agent to be able to write a good textbook, I think it will need to somehow embody that kind of process: realizing when a line of exposition needs to be abandoned because there is a better way to describe what is really going on.
For a QFT textbook, a big set of issues is the unsolved problem of what the best way to think about QFT really is. Just going out to the current literature, grabbing what is there and then trying to rework it as a textbook/monograph, results in a huge, undigested mass of various inconsistent ways of thinking. This may be useful for making clearer to us what’s wrong with the current state of the field, but not useful for anyone who wants to better understand what is really going on.
In any case, I’m curious to see how this project evolves, as well as others like it that surely will come. Initially their role will likely be just to provide examples of what doesn’t work: AI agents fed millions of pages of crud will just produce more crud. Can they develop real insight about fundamental issues in theoretical physics, or can human beings with real insight turn them into useful tools for progress? I’ve no idea how that will play out in the long term. In the short term, I think what we’ll see is just more crud, often dressed up and sold to the public as innovation by the PR departments of our new tech oligarchies.
