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What should we tell our students?

127 points • by sajid • today at 2:27 AM • 165 comments • view on HN

Comments

0xEnsp1re • today at 11:58 AM

that is kinda true, AI (LLM) can't think right now but maybe soon enough it is gonna change

unknownian • today at 7:36 AM

You tell them to cancel their Astra subscriptions and get to work. Hundreds of mathematicians, including Peter Scholze, have already agreed to not use AI at all. There’s absolutely no reason to help train an AI that will just make your own life more miserable.

https://www.ahmath.org/members

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hintymad • today at 6:32 AM

> On the other hand, none of the proofs so far seem to contain “alien ideas,” a move-37, or completely novel arguments or new concepts that were not present in the literature in some form or another.

I have the same optimism as Prof Tao. That said, I can understand why so many mathematicians have been so upset or stressed out. It turned out much of the mathematical work is about clever combination of existing methods - this already requires enormous amount human ingenuity and years of dedicated learning. Unfortunately, or maybe fortunately, AI can be very good at knowledge transfer and finding combination of existing ideas to solve seemingly impossible problems. Even though mathematicians are extremely smart and capable, only a small number of them are capable of truly inventing "alien ideas", discovering new ground-breaking mathematical structures, or coming up with new problem-solving techniques. That is, AI can eat many mathematicians' cake. That said, I'm still hopeful. Mathematicians still understand mathematics deeply. If someone can prompt AI to solve an important problem, that person is more likely a good mathematician than an average joe like me. So, I think mathematicians do have a bright future: leverage AI, and make more and bigger math discoveries. It's still the same north star: we must know, and we shall know. It's just that with AI, we will know sooner and more.

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reasonableklout • today at 3:15 AM

This post in the blog comments is quite compelling. Some observations that publishing of research is drying up because results can be easily retrieved at any time. Over the long-term, I wonder whether this will result in accumulation of knowledge grinding to a halt:

> With the latest ChatGPT models, these problems are more equivalent to homework questions: the answer is `in the back of the book.’ I am not discovering new solutions. Instead, I am working on problems whose answer exists and is simply waiting to be retrieved by a user of the model. In fact, I mentioned a problem that I was interested in working on to my advisor and he informed me that he and a collaborator had completely resolved it using ChatGPT – they have no plans to write up the result, so it will sit there until another `researcher’ pulls the proof slot machine.

There is another good point that the most tenured researchers have a sense of what problems are most worth exploring and therefore are more likely to feel excitement than younger researchers:

> I have also heard the contention that math research has `gotten more exciting,’ mainly from established researchers. They have decades of open problems that they care deeply about and want to see resolved. I have no such problems.

mikestylz • today at 2:52 AM

Just about anyone who has played a sport has heard that they have to target where the ball is moving to, not where the ball is right now. In this regard I am consistently disappointed with the commentary that mathematicians have been producing lately.

As a student, I am actively making decisions which will shape my career for the next forty or so years. At a minimum a discussion like this should acknowledge the possibility that the current rate of AI progress continues apace. I understand the desire to be encouraging, but the best preparation for students involves the consideration of possibilities that current mathematicians negligently paper over.

Of course it will get better at exposition than humans. And it will prompt itself in due time.

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huitzitziltzin • today at 2:54 AM

Nice piece. I think the fundamental message that there is still demand for mathematicians and mathematics done by humans is fundamentally correct.

I expect it will remain true into the future (10+ years). I have moderately high confidence (75% or higher) in this prediction.

I use frontier AI models in my work all the time. I think they accelerate my work by helping me understand faster and prompt better.

The models are most useful and most productivity-enhancing in the hands of experts and in the area of their expertise.

I don’t expect a jobs apocalypse, not even in math.

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Eridrus • today at 3:04 AM

There's going to be a massive reshaping of how mathematics is done. If you do not like where math is going (using computers to explore fully new ideas), and you have not committed to this path, it seems totally correct to opt out of it. There probably isn't going to be a technical field that isn't reshaped by this in the immediate future though, so there is unlikely to be anything that slots in cleanly as a replacement. Maybe the philosophy department.

bmenrigh • today at 8:58 AM

The “convex hull of ideas” is a very interesting framing.

My own suspicion/guess is that AI can break out of the bounds of the convex hull in math, and that’s going to become apparent soon.

soltanov • today at 3:39 AM

Treat the model as a compiler, not an oracle. You still must know how to specify the problem correctly, or you will only generate garbage faster.

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kian • today at 3:01 AM

Learning mathematics is about understanding the world, not proving things.

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analog31 • today at 3:38 AM

I'm not a mathematician. I was a college math major, got a PhD in physics, and still enjoy math.

It's not like "should I get a PhD" is a new question. It's not unheard of for unpredictable events to drastically affect the career prospects of PhDs in my field. During my lifetime:

1. Mandatory retirement of professors was ruled illegal. While good for civil rights, it created a 10+ year gap in faculty retirements.

2. End of the cold war.

3. Transition of college teaching from tenured professors to gig workers, aka "adjuncts."

The one constant during this time was the perpetual optimism of the faculty for the employment prospects of PhDs. "There will always be a need for physicists." My dad, also a PhD, confirmed that this goes back as early as the 1950s.

I would add one question to the student's letter: What are the ethics of AI and its owners?

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carlosjobim • today at 11:36 AM

The solution is obviously to make Mathematician a hereditary title and then have the European Union implement global regulations which forces AI companies to pay royalties to licensed mathematicians for any mathematical research their models perform. Care has to be taken so that initial titles are distributed in an equal and fair way between diverse groups of people based on ethnicity, sexual orientation, and other identity factors.

keithluu • today at 9:34 AM

Reading all the AI progress on math I wonder if current SOTA LLMs could have come up with the Incompleteness theorems.

pontus • today at 3:27 AM

Isn't there an analogy here to what's happening in software engineering? People keep saying things like "software engineering is so much more than programming". Couldn't one say that "mathematics is so much more than writing proofs"?

At least for now someone still has to decide what to prove and why. Like why are you trying to prove that thing to begin with? Presumably it's a step along some journey, right? Maybe the journey is where you need to start deriving your satisfaction from, then.

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dyauspitr • today at 7:17 AM

I don’t think anything is going to change for actual mathematicians. The only jobs they were getting were in universities and schools as teachers and professors anyways and you’re always going to need those.

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ButlerianJihad • today at 10:39 AM

Late in life I sought to complete community college. The RHEL degree path included a Calculus requirement that I could not evade. I had progressed somewhat beyond Calc in the first and second iterations, somehow.

So this Calculus class was 100% online. I discovered only at finals week that the instructor was firmly based at a distant satellite campus.

The class was brutal to me, and I needed a lot of time in the tutoring hall just to barely grasp concepts as they paraded past us. I used my calculator in good faith.

I discovered that there were websites that would solve integrals and complex equations, but I recognized that as outright cheating, so I resisted those tools.

However, the online LMS was set up with frequent quizzes with unlimited attempts. Not being penalized for attempts meant that I could brute-force every answer for every quiz throughout the course and get perfect scores. Though I felt kinda evil, I did just that.

When the final exam came around, our phantom remote instructor suddenly expected everyone to show up on her campus in-person. This was absurd to someone who was (1) on FAFSA funds and (2) riding the bus, and when I protested, the solution was a proctored session in the Disability office, all alone.

I solved every last question on that thing with paper and pencil and I required every single minute of the extended 3-hour limit they granted to me. I got an A- or whatever final grade.

Perhaps I didn’t deserve it, because all those learings drained out of my skull within 3 months, but it was a textbook example of gaming the system without strictly cheating, and since I was not aspiring to a math career, who cares?

The department deleted the Calculus requirement shortly after I finished that semester.

Hacktrick • today at 3:39 AM

why invoke move 37 as evidence against AI creativity? Move 37 was made by an AI. Is it so insane to think that the same selfplay training regimen that AlphaGo underwent to make that move couldn't be applied to LLMs trying to solve math problems?

mjewkes • today at 3:49 AM

> However, a proof of the Riemann hypothesis, say, may need new ideas that are strictly outside of the convex hull of current mathematical ideas

[...]

> After I finished writing this blog post, and had already sent it to Terry, OpenAI released a huge treasure trove of results in mathematics [including] the resolution of the so-called quasi Riemann Hypothesis

We ought to all be careful about underestimating the speed and magnitude of the change that is coming.

> if you are a student who is passionate to learn what is new and what is left to do, then a PhD is definitely the right path for you

This is an awful lot of confidence to put behind career advice in a wildly changing world. Markets are real and tradeoffs bite. We're not in gay communist space utopia yet.

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inSumErgoCogito • today at 9:33 AM

That not all humans are born equal. Equal inquisitive, equally providing of original thought and inspiration. The new, the step back and above is where AI still has weak spots and needs help.

This is a great moment to be a hassadeur, a madmen, somebody who wants to jump of the cliff with just a rope on his feet.

If you are that- great times- otherwise- good luck.

If you are one of those who try to drag down people oustanding, congrats on the team effort. Now try that with a machine..

intended • today at 8:03 AM

Just reading the letter from the student is depressing, and then you think of all the students who are not in a first world nation and how much worse their chances are.

God, the absolute decimation that is going to come for middle income countries.

Hell, right now the people quitting frontier labs are rediscovering trust and safety isues, like language parity problems, except all the work being done is in the first world and exported back to the rest.

Invictus0 • today at 3:28 AM

The difference between math and all the other professions AI has been obsoleting is that math is actually not a useful pursuit. The tired old line about math someday discovering something that will be useful in an entirely unrelated field is mostly baloney, and the problems that mathematicians spend their years broadly have no real world applications at all. A modern day mathematician is much closer to a monk than a productive worker.

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fragmede • today at 2:52 AM

> This is a guest post by Álvaro Lozano-Robledo.

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nadermx • today at 3:44 AM

"Solve the Riemann hypothesis, make no mistakes"

What actual industries where you could get a phd in, died?

If I was to ever suggest one, it would be Philosphers.

Yet they have found ways to get tenure and/or other jobs for as long as the field exists.

jdw64 • today at 3:18 AM

It reminds me of The Hitchhiker’s Guide to the Galaxy. The mice asked for the answer to everything in the universe, and it produced the answer:

“42.”

But no one could understand what the answer even meant. So they designed a computer to build the question itself again, and that was Earth. Then the story begins with Earth being destroyed because of a cosmic highway problem (I won’t write more since that would be a spoiler). In the opening background of this work, I found it interesting that after calculating for 7.5 million years, they didn’t even know what they had originally been asking. The story now feels similar to that story from back then.

livepairai • today at 3:19 AM

just work hard as much as they can

rvz • today at 7:46 AM

You should tell them that they were lied to as most of the “advice” no longer applied (or never did) and were completely setup to be displaced.

You should also tell them “better luck next time” as they have to create and find their own luck unfortunately.

This game was meant to be unfair because the ones who have “won” want to keep it unfair for others, and cannot stand losing due to complete greed.

The truth is they (students) have to find a way to outsmart the incumbents. The best advice is to find your own strategy and listen to no-one.

hyperbole • today at 9:29 AM

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aaron695 • today at 3:33 AM

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