As a mathematician by trade I think they’re overblowing it. You can choose to use it or not. I choose not to because I enjoy the process. But I’m not doing formal research or getting paid to do it these days. I will note that the average corporate mathematical modelling is usually a fucking circus so adding AI might make it better.
silveraxe932026-06-03 20:10
ENGLISH (원문)
> However, the declaration argues math is more than a machine for producing correct answers. There might be more to maths than that, but that is definitely the most important part. I love science funding. But not because it's a jobs program for nerds.
fooker2026-06-03 20:15
ENGLISH (원문)
I'm curious about whether we will start discovering new maths in the next few years that provide insight into unsolved CS or Physics problems!
bloqs2026-06-03 20:21
ENGLISH (원문)
well put.
bandrami2026-06-03 20:21
ENGLISH (원문)
My vague prediction right now is that in five years LLMs will be heavily used by universities in grant-funded math research but nobody else will be able to afford it, much like supercomputer clusters 25 years ago.
ryan_n2026-06-03 20:22
ENGLISH (원문)
> You can choose to use it or not This is becoming less and less true unless you're specifically talking about usage of it outside of a work environment. Many work places are requiring people to use it and/or tracking usage. I don't know about in academic settings, but I'd imagine it's becoming heavily used there too?
19f191ty2026-06-03 20:22
ENGLISH (원문)
No, it's not the most important part. It can be argued that most important part is asking the right questions
Dilettante_2026-06-03 20:27
ENGLISH (원문)
>and the pursuit of knowledge for its own sake Except when someone hands you a magic button that just gives you knowledge?[at least in the framing of this "warning"] Then it's about peoples' livelihoods, about "culture", etc? "Computer" used to be a job. Did science on the whole lose or gain by making these clerks obsolete?
kakacik2026-06-03 20:27
ENGLISH (원문)
Sounds very good for regular joe software dev, almost too good to be true
TrackerFF2026-06-03 20:28
ENGLISH (원문)
I've said it before, but there's a massive risk that we simply stop educating researchers. So much of a Ph.D revolves around the person learning how to do research. They learn how to read papers and literature rigorously. They get low-hanging fruits to practice on, which can take months. Their funding doesn't come from thin air either. So what happens when the group leaders would rather spend money on compute, and get models to solve the low-hanging fruit? Which the models could very well do in mere hours, compared to months. Nor does it help that publishing is the number 1 measure in academia. Furthermore, the access to compute and capital could end up be the defining factor between researchers and research groups. It is basically the "junior problem", but even more severe.
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