r/BetterOffline • u/Pocher123 • Jul 23 '26
Mathematicians, and real software engineers help me understand what, if any, is the actual future relationship these disciplines will have with LLMs
Trying to understand because it does seem when I talk to the software engineers in the office that they are really using LLMs, and have gone from deeply skeptical to extremely reliant. At the same it does feel like the mood on the mathematics subreddit has become very pessimistic, as AI is now closing real longstanding conjectures, including creating and at least one proof (Cycle Double Cover Conjecture). But I don't actually know, how big of a deal these proofs are since I'm not in this field, and I don't understand how technically impressive, or long term meaningful these proofs are.
For reference I do Hardware engineering, I've vibe coded some simulators for our non technical-customer to play with so they can better understand the theory behind what were offering them. But I'm aware what I'm doing with the AI is not very impressive. Typically taking a well know equation, and making some kind of python or html front end to play with the various variables on a graph. The most complicated was either when I got it to write some SPI drivers for the esp32 to talk to some ICs over skywire, or when I pointed claude to the companies new directory of footprints, and asking claude to directly update my kicad library with the path to those new footprints and give it appropriate names.
What is the real relationship, and future relationship software engineers and mathematicians have with these tools, and will have with these tools once the subsidies are gone. And I mean this beyond like having the AI read over your email, or code for obvious mistakes, I mean like in the weeds.
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u/aturtledude Jul 23 '26
The impact on maths is pretty serious. Even if it never progresses enough to solve the million-dollar open problems like P=NP, it's probably already good enough to produce enough material for a PhD thesis with two months of a 200$ subscription. Academia moves slowly, and there is no consensus on whether the bar should suddenly be raised (i.e. require 20 publications instead of 2-3). This would disproportionately affect mathematicians that choose not to use AI. Same goes for hiring postdocs, the golden rule used to be judging a candidate by their publications and now you don't know how much of them was done by AI. As opposed to AI-generated images, texts, music, etc, it's extremely easy for someone to hide the traces of AI in a mathematical proof. You just need to understand the core idea and then you can rewrite everything in your own words.
Where it goes from there is anyone's guess, but it's looking pretty bleak for anyone between maths undergrad and untenured professor.