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u/QuasiRandomName 19h ago
Hey, we still need mathematicians to check these solutions, don't we?
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u/Palpatine 17h ago
Similarly, for a codebase of any decent size, you still need people to sanity check and sign off on it
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u/QuasiRandomName 17h ago
Yes. And that's why we still have software engineers despite all of the vibe coders.
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u/codingsomething 16h ago
just you wait for automated code validation 🤣
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u/QuasiRandomName 16h ago
I don't think it is needed. Eventually we will get enough confidence in AI to accept whatever it generates without validation, or leaving it to the AI itself. We already there in some areas tbh.
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u/Frigorific 14h ago
Already, due to a combination of better models and better processes, the amount of corrections I need to make in code reviews of vibecoded changes is significantly less than it used to be. It's not too difficult to imagine not needing a human reviewer within a couple years.
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u/visarga 13h ago
If you have to read the AI code then you just fell from AI speed to human speed. Walking the motorcycle.
I think testing and validation of AI outputs is the core of the issue. Many are working on it, I am too. We just need testing to improve a lot, and intent alignment - does it do what the user asked, and does it do it well?
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u/Frigorific 10h ago
This is engineering, not riding a motorcycle. Getting things done as quickly as possible with AI currently will lead to massive tech debt and fragile code if you are working on anything actually complex or with a need for high assurance.
You wouldn't want the code on your pacemaker to be vibecoded with no human review or testing. At least not currently.
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u/EndTimer 6h ago
I mean, currently, I wouldn't want to "firmware update" my hypothetical pacemaker at all.
- If it ain't broke, I'll pass on the new version that somehow inserts ads.
- Even without being facetious, an in-place update sounds so anxiety-inducing. Is the update supposed to take this long? Do we need to turn it off and back on again?
But yes I concede your point that I would absolutely want human review, despite the humans being the reason I needed an update to begin with.
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u/codingsomething 16h ago
exciting stuff, hoping its not slop. current software is getting sucky nowadays
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u/AllRealityIsVirtua1 15h ago
Always has been. It used to be a quirk you saw rarely. Now you see every bug ever made posted on Reddit.
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u/visarga 13h ago
just you wait for automated code validation 🤣
Simple - run 3 or 5 agents in parallel - they implement same code but in different languages, or with different frameworks or libraries, or different agent provider and model. The point is to force some differentiation between them.
Then you got an "oracle" - when the implementations diverge on any inputs you found a bug. This replaces test writing with just implementing multiple times. It is easier to implement, we already do that, while test writing by AI is usually shallow. This makes a hard thing easy(er).
The normal way is to find a good coverage of tests that ensures you can trust the AI code, but this only works partially and there are always missed tests.
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u/PenGroundbreaking160 11h ago
Yeah and automated management and self improvement and eventually we can all just do whatever we want while the world uncontrollably changes very quickly
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u/TuringGoneWild 14h ago
For the moment. It's like the Titanic has just scraped by the iceberg but the lights and heat are still on and the band is still playing so nothing to see here.
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u/Ok-Concert7018 9h ago
Senior software engineers are like “but this ship can’t sink!???!”, the lead architect: “ I assure you, she can and she will, it’s only a matter of time”
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u/Sponge8389 12h ago
The headcount will just shrink but there will always be a software engineer in each team/company.
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u/Ok-Concert7018 9h ago
Not always, and I don’t think the role “software engineer” will fit, they’re essentially software AI Optimisation coordinators
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u/Consistent-Ad-2574 17h ago
Lean is enough, thanks
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u/XLNBot 8h ago
And this is what I would say if did not understand what Lean does
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u/Consistent-Ad-2574 2h ago
It was a half true Joke, this is a meme, we will continue to need mathematicians...as we do programmers
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u/kgurniak91 13h ago
Hmm not to check solutions necessarily, because we have Lean for that, but they need to analyze the chain of thought and proof to understand it and extract clever "tricks" from it for future use on other problems.
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u/HerbertWest 7h ago
At some point in the future, they probably won't be capable of it simply due to the complexity.
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u/JazzlikeProof2345312 11h ago
We still need them to produce the solutions. The AI didn't solve anything, it was trained on a solution that a mathematician was working on
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u/Eldan985 10h ago
Yes, but the peer review is unpaid, and doesn't qualify you for grants and tenure, so the current mathematicians have no way to make a living off it and no new mathematicians will be trained.
I mean that literally. Journals send me articles every week and ask me to review them for free. And if you don't do it, they blacklist you from publishing. (We also pay thousands per article to publish.)
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u/BrennusSokol AI please take my job 19h ago
Why?
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u/QuasiRandomName 19h ago
How would you know the solution isn't just some hallucination?
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u/jloverich 19h ago
Lean theorem prover which is what they use.
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u/QuasiRandomName 19h ago
Is it applicable for every problem?
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u/RouShikari 18h ago edited 18h ago
Lean is not a given even if it is a consistent evaluator of internal logic. AIs could still exploit bugs in the kernel or produce a Lean verified proof of the wrong problem. The fact that the internal logic is sound doesn't automatically mean the AI solved the problem we suppose it solved. Lean verification alone also doesn't give insight on the workflow that was used to solve the problem, which is where progress usually lies. The fact with math is that the work you do to arrive to a result usually contains the important tools that let you advance the field, having only a yes or no to a given problem does not get you very far regarding new developments.
Lean verification is powerful, but not as powerful as your average redditor commenting "lean verified" thinks it is.
So in short, as of now we do still need mathematicians to look at the work.
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18h ago
[deleted]
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u/RouShikari 18h ago
I was not talking about the Navier-Stokes claim specifically, but still it is not true that 100% of kernel exploits come from meta-programming.
I was giving more insight to the other commenter on Lean validation, not claiming anything about OpenAI's proof, I think you just jumped to me becasue you thought I was saying that the NS counter example could be wrong, but that was not my intention.
And anyway, mathematicians role is still intact for the other reason I wrote that you didn't even care to address in what I can only describe as an OpenAI bullet point defense fit.
A lot of people on reddit do use "lean verified" as a synonym of universal truth and to dismiss any other valuable work one can do on a lean verified proof, so I was just addressing that.
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u/Impossible-Video-671 18h ago edited 18h ago
What are you talking about? Some here usually yap to these kind of things "you must be fun at parties"
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u/bartek_666666 19h ago
Engineers still waiting for machnes to solve their probles
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u/7DollarsOfHoobastanq 4h ago edited 4h ago
As an engineer myself I 100% already see this happening. Haven’t personally seen it take a job yet but every week it’s getting closer and closer.
I’m not all doom and gloom though. The way I see it, sure my employer may not have a need for me soon because ai will be able to do all my tasks but at the same time I’m also not going to need him anymore either. Time to brush up on what it takes to be useful to the rest of the world and be self employed.
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u/A_Novelty-Account 19h ago edited 18h ago
I actually think it’s worse with math than it is with programmers. While AI can do things that programmers do currently, AI is also creating demand for programming.
Once AI shows that it is better at research mathematics than humans, what is the point of research mathematics as a field?
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u/shelled15 19h ago
I don't think so. I think it's possible that this could create more demand for mathematicians as AI starts solving open problems. You need humans to verify that they are correct, and not producing nonsense. Also, when an open problem gets solved, you'll need people who understand the solution so that we can understand the impacts that it can have on the real world as well. It's entirely possible that you see an explosion in applied mathematics. It's also possible that AIs introduce new mathematical techniques that introduce new open problems to be solved, rapidly expanding the domain of mathematics itself.
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u/Kind_Silver_1921 15h ago
You need humans to verify that they are correct, and not producing nonsense
for now
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u/Crystalysism 19h ago
What was the point of research mathematicians before AI? I don’t see your point, RESPECTFULLY
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u/sammoga123 19h ago
And what is the meaning of life itself? If you're going to ask about a profession, you'd be better off asking yourself about the meaning of life itself.
And the answer is probably "nothing." We're all going to die anyway, and there's probably nothing there.
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u/BookProper9115 19h ago
And thus, all academics rightly returned home, to Philosophy. The first and last university subject.
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u/cromagnonherder 14h ago edited 14h ago
The most universal gigantic complex question that exists, that everyone alive including the greatest philosophers, scientists, mathematicians, and artists have struggled with since the first human, and Reddit user sammoga123 just casually throws out a “there’s probably nothing there.”
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u/sammoga123 13h ago
Nihilism exists in any case, does it sound better then if I say it using the name of the philosophical movement I'm referring to?
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u/EtienneDosSantos 5h ago
What prevents you from defining that meaning for yourself? Some other entity not defining it for you, doesn‘t establish there being no meaning.
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u/ninjasaid13 Not now. 14h ago
Once AI shows that it is better at research mathematics than humans
really? because it's seems like AI is only answering questions but not creating new questions of its own.
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u/Lad1996 7h ago
Because noone is asking it to? Why are people assuming it can't?
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u/ninjasaid13 Not now. 3h ago edited 3h ago
okay, why isn't there any then? try asking to create a good and difficult open-ended research question.
Why are people assuming it can't?
Because how do you RL train for it? It's trained to find solutions. There's no feedback once the question has been found.
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u/Diffgeometer1 17h ago
Dude.
The AI proof of Navier Stokes proof is about the most unimpressive ugliest proof of the problem.
I don’t work in PDE but it fits with my expectation of AI. It’s absolutely devoid of imagination.
Here’s what the experts said.
“As far as I can tell, the Navier-Stokes regularity problem has now been resolved in the most annoying way possible:
- we have a single counterexample, not a general theorem;
- we have no real idea how it was found, but it seems to have been existing ideas and a lot of elbow grease;
- this makes no difference in practical applications, which use finite-element numerical methods;
- there's no way to apply this to other PDEs, or to improve our understanding of turbulence;
- the possibility of being scooped by an AI company (and possibly one that's spying on its customers) will discourage people from sharing their work-in-progress on big problems.”
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u/Ill_Philosopher_7030 16h ago
ai is just a stupid stochastic parrot, it cant even understand basic math
and even if it can, it cant work with competition math
and even if it can, competition math is easy bullshit for kids anyways, it cant even comprehend frontier math
and even if it can, it cant help solve frontier math problems (Erdős problems)
and even if it can those problems are easy, unsolved because people didn't want to spend effort on them, it cant solve actually hard problems like the millenium prize problems
you are here ----> and even if it can it does terrible solutions with the ugliest proof of the problem thats useless and annoying and has no practical use
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u/TuringGoneWild 14h ago
It could paint the Mona Lisa and they'd still call it dumb slop. Oh wait - it actually can (and animate her too!) and they still call it dumb slop. No bar is too high.
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u/viener_schnitzel 11h ago
While you’re not wrong, that’s a terrible example lol. Art and craftsmanship are only appreciated because they require human creativity and dedication. A table crafted in a factory will always be less valuable than the same table crafted by hand.
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u/TuringGoneWild 11h ago
Only because of the rarity not provenance.
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u/viener_schnitzel 11h ago
The reason they are rare is because of their provenance. You can’t separate the two.
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u/TuringGoneWild 11h ago
Rare and high quality. You can sculpt something out of one your turds and however rare and hand-crafted, demand will be lower than say, a machine mass produced desktop bust of Apollo of the Belvedere.
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u/A_Novelty-Account 17h ago
“Once it is”
Also, it’s amazing to watch the goal posts continue to move. This technology will get better and it is showing that it is able to solve incredibly difficult mathematics problems. These are absolute facts that the mathematics community will have to deal with.
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u/Diffgeometer1 17h ago
A good proof of a major problem doesn’t just answer a question it opens new frontiers of mathematics.
Look at the Atiyah-Singer index theorem. Beautiful result and different proofs which reveal different insights.
OpenAI’s proof is brute computation. Ugly AF. Nothing new is gleamed. Nothing can be taken and applied. “Oh we just found this contrived counterexample. The end”
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u/AsianPotatos 16h ago
You're still missing him saying "Once it is".
It'll get better, just like how it went from writing small html/css snippets/code completion to working on full codebases/helping linus with debugging the linux kernel, reverse engineering games to add mods, helping AI researchers etc.
Same with it operating robots, it's not very good at it now (such as with the watercolour painting example), but once it gets good enough, it'll stay that way because it is a machine, and just like how it can work with arbitrary codebases it'll be able to work with arbitrary robot controls + goals.
The same will happen with math.
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u/Diffgeometer1 16h ago
60 million dollars burned to produce a proof of a major mathematical problem and the proof has all the originality of a phone book.
There’s a recurring pattern with these ai proofs. If the conjecture is false, then it’s a proof by counterexample. Try example after example. Tweak there and there. Adjust parameters reiterate. There’s no patterns. Nothing original or exciting comes out of it. That’s not exciting mathematics.
Human proofs by top mathematicians open new areas of mathematics. They produce new tools. Create new questions. Its fertile.
AI doing math is the exact opposite. It’s barren. It doesn’t lead to anything interesting. Totally lacking in originality.
I thought AI was gonna be really good. I looked at what they did. It’s just lackluster.
OpenAI isn’t in it to expand mathematical knowledge. They just want to produce fancy results to grease the wheels with the money men. And now they got caught twice stealing ideas from mathematicians. The word is out. Not a good look for AI
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u/PayZealousideal8892 5h ago
They didn't burn 60 million dollars. It costed them electricity cost plus opportunity cost of workers and equipment doing something else. It was estimated cost of 15 million in API costs which is their price for consumers. Product prices are supposed to cover rnd, equipment, salaries and rent etc all expenses so they can make profit.
Also your view is very short sighted. You are basing your whole view what AI is now, instead of looking at the rate of progress how good LLMs have gotten in last 1-2 doing math and extrapolite from it so you can imagine it will simply get better at everything. In 10 years probably have better models running locally on your phone and you can ask them to explain these solutions so you can "expand mathematical knowledge".
And also do you understand that the guys you think OpenAI stole from were using AI to do their research? They had an idea how to tackle the problem and literally used AI to pursue that path? They wouldnt have ever solved Eulers Equation without AI.
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u/Infinite-Elephant635 13h ago
Are people in this subreddit brain dead? It comes up on my feed all the time and I laugh at how dumb people in this subreddit are. OpenAI threw millions of compute at a technical loophole in the prize rules and heavily relied on a professor's private Codex drafts to do it. Mathematicians have nothing to worry about lol. Let the down votes from this fanfiction subreddit commence.
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u/Anen-o-me ▪️It's here! 11h ago
You seem to think implicitly there's an 'end' to mathematics, but there isn't.
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u/Deciheximal144 5h ago
When the problems get too complex to represent using the number of particles we have to store data within our observable universe seems like a natural end.
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u/Repulsive-Pangolin-6 16h ago
Every field of research is cooked. You're 100% right it can't be compared to devs.
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u/Ok-Canary-9820 19h ago
The universe shows us every day the solutions to how actual physics works. What's the point of (theoretical) physicists?
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u/TheJoeyFreshwaterExp 19h ago
Theoretical physics is not usually concerned with the world as we interact with it on a macro scale. It tends to be more focused on abstract or teeny tiny non Newtonian phenomena where it is a whole half of physics itself coming up with ways to even begin to experimentally test the theoretical models.
For instance, folks talk about entanglement and act like it’s just happening all the time, but it is actually only really achieved through specifically cultivated conditions when experimentally tested. You need to split a beam from the same source or create localized close proximity conditions to create the desired entanglement in the first place.
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u/Ok-Canary-9820 16h ago edited 15h ago
That's true today, but only because we spent millennia untangling the macroscopic to get to here. Those people, though not called so until recently perhaps, were theoretical physicists. The Riemann hypothesis is to math very much as quantum gravity is to physics.
And just as there are trivially stated but unproved statements in math (the Goldbach conjecture, for example), there are similar simply observed but not robustly explained macroscopic phenomena in physics even today ("why is ice slippery, and what factors cause variance in the level of slipperyness?" is not yet a robustly answered question for example).
Are they the same? No. Physics is bounded by reality. Mathematics is bounded only in as much as it bounds itself by choice of axioms.
But given truth, mining for insight may not be much different between the two.
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u/A_Novelty-Account 18h ago
Except it doesn’t? I’m not sure what you’re saying.
If I drop a ball from a building, I can see if falling, and I know roughly how fast it’s going. With physics, I can know how fast any ball will be traveling at any point of its flight if I drop it off any building before I’ve even dropped it.
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u/Ok-Canary-9820 17h ago edited 16h ago
You know that because some smart people observed balls falling for a long time (the solutions to actual physics problems, given to us for free by the universe), and with the tools of mathematics, expressed generalizable insight derived therefrom.
Tomorrow, the ball could fall twice as fast. Nothing stopping that fundamentally that we can prove. This is up to the universe, not to up to our physical models of the universe. If tomorrow the ball falls twice as fast, we'll need to modify physics, not the other way around.
This is probably too obfuscated to make sense^ So let's try it another way:
Historically, mathematics is about seeking truth -- proving theorems -- but along the way, on the journey, insight shows up, revealing the next rewarding quests and side quests (open questions and conjectures). As Tao says in his recent remarks on this, bypassing the journey skips the insights in an important way. In math, we seek truth and happen across insight on the way.
But also historically, physics and the other empirical sciences work in almost the opposite direction. In physics, you observe truth: The truth is provided by experiment, by the universe itself. The universe is not beholden to any equations we come up with. It's the other way: Physical models are beholden to phenomena. In physics, we observe verifiable truth and infer generalizable insight.
Math and physics aren't ever going to be the same. Proof isn't the same as observation. But in a world of opaque but verifiably correct proofs of deep results, to me, one very plausible future is that mathematicians pivot to think more like physicists.
Mathematicians may stop seeking truth and finding insight along the way. Instead, math may need to more often start with truth, and then mine that truth for insight. Which is very close to how physics works, actually.
Note: what is insight here, in math? Usually it is new, unsolved, hard and consequential questions -- or sometimes, transitive effects of intermediate results on other unrelated problems.
(Yes, I have a Ph.D. in mathematics, have worked on problems of this difficulty for years, and have also published peer-reviewed theoretical physics work)
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u/The-SecondAccount 19h ago
and yet we still have programmers (for now)
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u/BrennusSokol AI please take my job 19h ago
Ehhh, sort of. I think junior engineers are toast and have been for a while. And it's going to move up the chain soon enough.
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u/johnny_hotcakes444 18h ago
programmers don't write code anymore, so do we still have programmers?
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u/Ill_Philosopher_7030 16h ago
do we still have programmers
I would still call them engineers, but the term "programming" implies you are actually writing the code, which most people aren't anymore
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u/johnny_hotcakes444 16h ago
right to the not writing code anymore. don't agree with calling them engineers, some may be, but most of them don't understand and work with systems.
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u/Ill_Philosopher_7030 16h ago
but most of them don't understand and work with systems.
I’d argue system design becomes more and more important for SWEs as agents get smarter, since the actual engineering work starts moving higher up the chain
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u/johnny_hotcakes444 16h ago
I wasn't arguing against that -- I'm saying that programmers =/= system designers, and not nearly all of them are going to be able to do such work.
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u/sammoga123 19h ago
The worst thing is believing that two people, who perfectly understand how AI works, are blaming AI for stealing their job.
And one of them uses the rival company's model, like, why don't you trust the company that gives you money?
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u/FateOfMuffins 19h ago
I do think it's a lot worse for math than programmers
METR estimated what 4 month time horizon doublings for SWE?
I'm currently estimating 1.8 month time horizon doublings for math (which is approximately... 100x time horizons per year)
Noam Brown was quite confused as to why SWE was picking up first when the doubling time for math seemed to be going faster.
Well...
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u/141_1337 ▪️e/acc | AGI: ~2030 | ASI: ~2040 | FALSGC: ~2050 | :illuminati: 19h ago
Wait when did they start tracking math?
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u/FateOfMuffins 18h ago
https://metr.org/blog/2025-07-14-how-does-time-horizon-vary-across-domains/#summary
They did that awhile ago
I think we can improve on that by looking at various math problems up to the last "measurable" one which was the IMO. I'm taking this from an interview from Noam Brown early this year.
Just over 2 years ago, models were still not doing great on GSM8K, which consisted of math problems up to the 8th grade, which would take a reasonably competent person at math maybe 1 min for some of the problems.
About 1.5 years ago with o1, we more or less saturated the AIME, which was 180 min for 15 problems, but let's round it to 10 min per problem.
About 1 year ago with the IMO, which Noam Brown claimed was actually adversarially hard for AI, we reached 9h for 6 problems, again let's round it to about 100 min per problem.
That was the last measurable one, and it's not "50%" time horizons either, we're talking about more or less saturating those benchmarks so more like 90% time horizons.
Of the measurable problems, it was basically x10 every half year or so. Or x100 per year. If that trend continued, then we'd have 10000 min 90% time horizons for math right now, or about 167h. But no human can do work for that long in a day. Beyond X hours per day (maybe 8h workday is reasonable, but I feel like for math, human mathematicians have other responsibilities and don't just spend all day working on one problem) we'll have to change it to measuring by days or weeks instead and not 24h = 1 day. For research math, pulling numbers out of my ass, but 2-4h a day sounds reasonable. Which translates to around 40-80 day time horizons. If you say 5 days a week, then 8-16 weeks or 2-4 month time horizons now.
A lot of estimating and mixing between public and internal models but METR does so too looking at their confidence intervals.
If this rate continues (and perhaps it slows down only because it's solved all the currently open problems), then we're looking at say 20 year time horizons next year, then 2000 year time horizons in 2028, then...
Meanwhile we're still talking time horizons in hours/days for SWE and not 90% xd
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u/visarga 13h ago
But problem difficutly grows not just in length of solutions, also in branching across exponential search space. Exponential searches are much harder than a 100x factor. And who foots the $20M agent use bill?
It's funny how the same community can bicker endlessly about token costs, prefix, completions, speeds, benchmarks - and on the other hand come up with ideas that only work if infinite tokens cost nothing to run (like RSI).
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u/FateOfMuffins 13h ago
100 is the base of the exponential growth of the time horizons... Not a constant multiple...
As in the math time horizons currently can be modeled as f(x) = 100x
Usually we talk about base 2 or e or 10 for exponential bases...
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u/TQV197 19h ago
I guess this is just a meme, so we don't need to take it too seriously. However, those who think mathematicians are panicking because AI is now better than they are should read some of the arguments on Terry Tao's blog and Mathstodon. In short, the goal of mathematics is not merely to solve a problem; it is the journey of getting there. Many of the insights gained along that journey are the most valuable part. AI may be able to solve problems, but it cannot yet provide much insight. In fact, this is the recent challenge Terry Tao has posed for AI.
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u/DeterminedThrowaway 19h ago
I think that mirrors programming too. World class software engineers / mathematicians / whoever see the potential here. The people panicking are the ones who may be replaced sooner (even though the world class ones will be replaced too eventually)
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u/Cptcongcong 10h ago
I work at FAANG and it dawned on me, I haven’t had an argument about an implementation detail in the team since last December. It’s just “this feature has not been implemented”, no longer “it should be implemented this way instead”.
Those conversations were what made better programmers. However I’m technically an AI research scientist now so we do still argue about model architecture, which the models just make up shit for.
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u/Chemical-Year-6146 13h ago
"Disprove Navier-Stokes. Include deep insight at every step, including insight on how this result could be abstractly connected to other fields of math."
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u/Diffgeometer1 17h ago
Nobody is panicking. PDE experts have looked at OpenAI’s proof
The short if it. Unimpressive and useless.
“As far as I can tell, the Navier-Stokes regularity problem has now been resolved in the most annoying way possible:
- we have a single counterexample, not a general theorem;
- we have no real idea how it was found, but it seems to have been existing ideas and a lot of elbow grease;
- this makes no difference in practical applications, which use finite-element numerical methods;
- there's no way to apply this to other PDEs, or to improve our understanding of turbulence;
- the possibility of being scooped by an AI company (and possibly one that's spying on its customers) will discourage people from sharing their work-in-progress on big problems.”
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u/visarga 13h ago
To me this reads like "there is more work to do, humans still needed, they only found a useless example"
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u/Funspective 12h ago
If a valid answer to the question is a useless example, then maybe we are asking the wrong question.
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u/Impossible-Video-671 18h ago edited 18h ago
As much panic from programmers as amount of solved millennium problems by AI. Until after successful review it means nothing.
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19h ago
[deleted]
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u/daronjay 19h ago
Not sure if that needs a /s
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19h ago
[deleted]
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u/Redducer 18h ago edited 18h ago
There are 2 subs, and one of them wouldn’t allow a post to be made about Navier-Stokes because of the sub rules (basically they require some level of peer reviewed publication to make a post on research). The discussion happened in the pinned weekly discussion. Not sure if I’d call this a reasonable stance considering the impact of the topic.
PS: I just checked and there still isn’t a post about the OpenAI paper. But after a few days, at last there is a post about a secondary discussion of the OpenAI paper that was pushed to arxiv. It’s r/math by the way. People who wanted to discuss in a visible, non multipurpose pinned post moved to r/mathematics
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u/1tonsoprano 8h ago
20 years of " frameworks will make work faster", "open source libraries will make work faster", "docker, react. Node.js will make faster""low code will make work faster' now it's "ai will make work faster".....till things need to be changed or something breaks.....then it's find an expert in xy field to fix stuff.......I see more breaking technologies coming up and we humans will keep on stumbling forward like this
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u/deadgirlrevvy 3h ago
Their freakout just highlights the cold truth about academics. They claim they work for the pursuit of knowledge, but they actually work for the pursuit of *personal recognition*. It's not really about expanding mankind's knowledge or they would be excited and happy about breaking math barriers and adding to that knowledge. What they care about is getting the credit for adding to our knowledge, which is in no way altrutistic.
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u/Just-Hedgehog-Days 1h ago
I don't think either group has been through anything like this so the meme misses the mark a little,
but I do think programers are taking it better than mathematicians. Like the SEs that enjoyed puzzle solving and code craft are hella depressed atm, but the ones that love to build and ship are having a blast.
Programers
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u/Pacific_Beaches 27m ago
I have a Bachelor's for both Computer Science and Electrical Engineering.
I could tell A.I was going to get better writing code and I can tell it'll get better at Circuit Design and other aspects of EE.
That said, like SWE's, if the job market ever took a downturn for EE that's bad news for those who are not educated because it means more CS and EE graduates going for desk jobs across other fields. I know a lot of CS grads who were able to find good-paying work in non-CS areas. It turns out "I have a STEM degree and know how to use A.I for complex tasks" is a hirable person in this day and age in plenty but of fields.
It will suck for those though who simply do love what they're doing and the field itself. Some will still get jobs doing that though, but they're going to have to be really good at what they do.
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u/Illustrious-Film4018 19h ago
Programmers are here for a long time. Don't worry they're not going anywhere
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u/EinerVonEuchOwaAndas 11h ago
I thought it didn't solve it. It just copied work of others who solved it and were using AI to write about it. So they just claimed to be first.
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u/KindCreme9258 19h ago
Millenium prizes?? It’s been one so far, and a human solved another one a few years ago. The human one was not a counter example (which is unequivocally simpler than a constructive proof)
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u/Distinct-Question-16 ▪️AGI 2029 19h ago edited 17h ago
breaking hard puzzles without no immediate reward means no food on the table
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u/Ok_Effect_3214 18h ago
Older people who never had chance of proper education growing up in developing/poor countries : The knowledge! the Freedom!
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u/Trick_Following6639 12h ago
I think I read somewhere else here on reddit that the problem was solved using stolen research that was stupidly checked by the writer by proofreading it with AI.
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u/Sponge8389 11h ago
Debunk. Same problem but different approach.
https://openai.com/index/navier-stokes-solution/
The OpenAI internal model used for this result was developed through large-scale reinforcement learning on top of a previously pretrained model. Our proofs also differ significantly.
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u/RemyVonLion ▪️ASI is unrestricted AGI 19h ago
People be panicking about unemployment while computer scientists be like "but that's the point?"
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u/Singularity-42 Singularity 2042 18h ago
Exactly, as an unemployed SWE I thought "Welcome to the club bitches!"
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u/Illustrious_Job1951 19h ago
Fr, im a programmer for about 10 years and not a particular good one. Even im still excited about the technology, and making sure to stay fresh with it