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mellosouls 5 hours ago

Not to denigrate the moment (AI ingress into theory which this is a part of) or the result here, but these headlines are perhaps overstating the importance - some of the theories and conjectures are available for AI-assisted exploration because they are quite niche and not very important.

Maxwell's name being invoked here for instance implies a hundred year old foundational problem like Fermat, but it's just a recent conjecture that was inspired by reflections from the great man on his work.

ashleyn 5 hours ago | parent | next [-]

They might be low-hanging fruit but two things immediately come to mind:

* As more of the small stuff is just proven for free, the more they can be used as a basis for other proofs. If you know something is true or false for certain, that can be a significant tailwind for the much harder, much more important problems. Fermat's last theorem looks deceptively simple and invited many failed amateur attempts at solving it, but Wiles' proof drew on a diversity of seemingly-distant subfields within mathematics that were better understood.

* What are aspiring math Phd's supposed to do, now that the bar is much higher these days? The net effect of this appears to be that we'll see far fewer, but far more elite math Phd's, potentially discouraging many young people from the field.

ndriscoll 3 hours ago | parent | next [-]

The bar for math PhDs already ruled out like 99.9% of the population, so I don't see it having much effect on discouraging people. The gap between even a bright student who takes AP calculus or whatever and someone studying e.g. spectral sequences is already incomprehensibly large. Like you literally could not even convey to a smart young person how far away they are from the boundary of today's understanding. I don't think I even have a reasonable sense with a math bachelor's!

People who get into math do it because they can't not do it.

ian-g 2 hours ago | parent [-]

I think it'll become increasingly important to have folks thinking about how to explain new math in a way that makes sense to your math bachelors students. And to your bright AP Calc students.

If we can point ChatGPT at these problems and get eventual answers, that's awesome, but it'll still be important to figure out how to tell people why this matters in ways they understand.

throwaway0123_5 5 hours ago | parent | prev | next [-]

> The net effect of this appears to be that we'll see far fewer, but far more elite math Phd's, potentially discouraging many young people from the field.

It seems plausible that the value of education will go down for the vast majority of fields and as a result less people will be getting degrees of all types.

Not a good outcome I think for humanity to be less educated, even if people are provided for when they can't get jobs... things like mathematical and scientific literacy, as well as history knowledge (which even STEM majors often receive via undergraduate degree breadth requirements), etc. I would expect strongly result in more informed and harder to deceive citizens.

CWuestefeld 2 hours ago | parent [-]

A large proportion of degrees awarded today are not useful for any practical application.

But having a degree of some kind still serves as a signaling mechanism, demonstrating lots of things including the ability to "play the game". to follow instructions, and so forth.

hgoel 4 hours ago | parent | prev | next [-]

I don't believe this is raising the bar for minting fresh PhDs.

We need to maintain perspective here, a PhD is essentially work done by a researcher at the least experienced, least skilled point of their career. Their primary goal is to demonstrate that they are capable of contributing to research.

They are not competing against AI to publish a counterexample to a known conjecture.

chermi 4 hours ago | parent | prev | next [-]

Maybe masters will become more popular. I have no problem with bars being raised on PhDs, but it's crazy history that math may be the first one to have it raised (or brought back to old levels).

StableAlkyne 2 hours ago | parent [-]

IMO, I don't think this will raise the bar for PhDs.

In every field of science, PhD student research is largely incremental. Very rarely is a thesis groundbreaking. The point of it is all is to function as an apprenticeship for that PhD student to become a scientist.

Sometimes a particularly gifted or lucky one hits an important result, but that's rare and isn't the purpose.

julianeon 4 hours ago | parent | prev | next [-]

Is the bar really higher? Those math PhD's can use GPT too; they benefit equally from AI assistance.

fn-mote 2 hours ago | parent [-]

This approach totally changes the game, in ways we are still discussing.

The current consensus is that domain experts get the most out of using AI on problems. How will domain expertise develop when AI is doing the work?

I’m not saying that there won’t be another approach that builds on the strengths of AI, but we have to look for that and develop it.

There’s a lot to talk about.

jauntywundrkind 3 hours ago | parent | prev [-]

Notably we have had very few conjectures proven true, so it doesn't feel like there is that widening base of established map to draw yet more proofs upon.

moomin 5 hours ago | parent | prev | next [-]

Yeah, the Jacobian conjecture counter-example was big news. In particular, it would have been news even if an AI hadn't done it. That's where the bar is now. Settling Erdős conjecture 7529 or whatever no longer qualifies as AI news.

tsunamifury 5 hours ago | parent [-]

Real talk.

AI solving these makes me feel like mathematicians put far more importance on their work than was actually there. Many solutions seems to be tautological games, and games of logic where conjecture puzzles that few work on or care can be solved by AI which doesn’t care what it works on.

It seems to always be some form of this:

Mathematician: “Propose conjecture a and conjecture b can’t be true simultaneously”

AI: “they can”

Everyone: “ok…”

I know this might be unfair or out of ignorance but it genuinely is how this field feels today. Games of games with self importance added in.

Edit: the point I should have made is, should we be using AI to figure out what proofs MATTER now vs games of proofs?

efficax 5 hours ago | parent | next [-]

"tautological games".

All proofs are a form of tautology, you have to end up back at the point your theorem proposed. Math is games of logic. That's what it is.

wongarsu 4 hours ago | parent | prev | next [-]

Academic math is a bit like basic research. You come up with funny ways to look at numbers or prove weird statements about this thing you came up with and call a "group", and a couple years or decades or centuries later it turns out that this solves real problems in electrical engineering or biology

Or it ends up never becoming useful. But you can't know that in advance

tsunamifury 4 hours ago | parent [-]

Disagree, basic research, no matter how dull, is an observation of a measured reality. Math Theory are patterns of abstraction that may never be useful at all or representative of reality.

lioeters 28 minutes ago | parent | next [-]

> may never be useful at all

Nobody is qualified to judge the usefulness of mathematical, scientific, artistic, or any other kind of research that people choose to dedicate their time doing. And the world is better for it.

> or representative of reality

This so-called "reality" you speak of is some arbitrary representation in your head. It's your theory and patterns of abstraction, as you call it. Who knows how far or close you are to "objective" reality, whose existence we can only know through representations and abstractions. Mathematics and logic are some of the best tools we have of getting closer to that truth and understanding. All the sciences and even some of the arts are based on it.

fn-mote 2 hours ago | parent | prev | next [-]

Parent seems to conflate “abstract” with “useless”. This comment addresses the “abstract” part only.

> Math Theory are patterns of abstraction that may never be useful at all or representative of reality.

This is a complete misunderstanding of (good) mathematical research.

The results look abstract, but they are based on concepts that are real and have truth or falsehood.

One example that comes to mind (sorry, technical): is it possible that all maps from a high dimensional sphere to a three dimensional sphere (S^2) might form a group that is not even finitely generated?

This is not just “abstract nonsense”, but understanding any of this takes effort.

lyu07282 3 hours ago | parent | prev [-]

“May never be useful“? You make it sound as if there aren't countless examples of those "abstractions" of theory/pure math turning out to be useful in all kinds of fields in the past. This feels like the more general anti-science argument of 90% of science is useless and never produces practical applications, the point people never understand is that nobody knows which 10% it's going to be so you have to do the 100% to get to the 10%.

dwaltrip 5 hours ago | parent | prev | next [-]

Look up how pure mathematics connects back to reality in countless unexpected and useful ways, time and time again.

throw-the-towel 4 hours ago | parent | prev | next [-]

To borrow a common wisdom about marketing, half of all mathematics is a waste of time, but you can't know which half.

jstanley 4 hours ago | parent | prev | next [-]

We call a proof that is not tautological "wrong".

chermi 4 hours ago | parent | prev | next [-]

Very useful games, self-importance or no.

See pattern, conjecture generalization, test generalization. It's almost like empirical math. I like it and I also like mathematicians doing it the old way.

deeznuttynutz 4 hours ago | parent | prev [-]

Don't do that...

astro1234 4 hours ago | parent | prev | next [-]

I find them useful bellweathers of genuinely out of domain performance and capability, regardless of their theoretical importance. What I see is that performance trends are remarkably stable both upstream (miraculous scaling laws of pretraining on validation loss) and downstream performance (epoch capability index). We get the equivalent of a GPT4->GPT5 performance leap every ~16-18 months, and we are not hitting ceilings nor do we see any deceleration.

Today we can solve nontrivial open problems. What will we be able to do next year or the year after? 18months ago no one was using a coding agent seriously. Now for a large segment of the population you cannot do your job without them.

gjm11 3 hours ago | parent | prev | next [-]

I'm not sure that's right. The conjecture is (claimed to be, by the people who explicitly made it) simply a reformulation of a claim made by Maxwell in his "Treatise on Electricity and Magnetism" of 1873.

spullara 2 hours ago | parent | prev | next [-]

It is much harder to prove these conjectures true than false. On some of these people had spent years of their life trying to prove them true. By showing they are definitely false that can be avoided.

paulpauper 2 hours ago | parent | prev | next [-]

some of the theories and conjectures are available for AI-assisted exploration because they are quite niche and not very important.

The fact this has gone viral, shows otherwise. It is important to apparently enough people that the story went viral.

5 hours ago | parent | prev [-]
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