Many academics around me have a paid plan of LLM of some sort, most are on $100 plan some are on $200, all of them are getting reimbursed for their plan.

Most of them uses it to optimize code, generate visualization, or formalize pen and paper proof.

I hated it, and don't use much of it myself. But it seems too useful for these people and it is hard to stop them. As an example, formalizing a pen and paper proof can take an expert weeks, if not month of work, whereas it only takes codex a week.

But I do feel this success is tied to the nature and value of academia, and might not transfer to other fields or industrial projects:

• we usually have tiny codebases: it is not uncommon to have a 10-line algorithm with a 70-page paper explaining its correctness
• 90%, if not more, of the codes are proof of concepts, without the expectation for long term maintainance.
• the work is highly specialized, everyone is running out of time, and there is high expectation of the outcome of the work: in our recent work, we do have an expert in formalization, but he doesn't have enough time, so the grad student formalized the project using codex. The overall architecture is probably much much worse than what would have been done by the expert. One interesting outcome is that codex is able to prove a more general result than the expert intended: not because it found a better proof, but because it is much better at bruteforcing a solution than human.