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Comment by causalmodels | Hacker News Reader

What do we do about the problems that don't require many millions of dollars in resources?

Last weekend I spun up a small agent swarm and pointed it at a field of math I have some affinity towards. Within four hours I had settled three conjectures, one of which is rather famous (for the field, not in general). It cost me about four hundred dollars.

I am at a loss about what to do with these results. On one hand I feel like the mathematicians working on these should know about them, but on the other I feel a bit like a barbarian who suddenly finds themselves sacking Rome.

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I'm not a mathematician but it seems to me that if all it took to solve the problem was an enthusiast level understanding of the domain and a few hundred dollars of tokens then the result probably isn't that valuable. Even assuming you are the first person in the world to solve it, these kinds of LLM-friendly problems that are now easy to solve and easy to verify will almost certainly be picked off by one person or another in the near future.

It's also possible that the result is already known and you just weren't aware of it. It's easy for someone outside of a field, or even one steeped in it, to not be aware of certain solutions.

sounds a bit like cope. Crouzeix's conjecture was solved exactly under these circumstances and I wouldn't describe it as "not that valuable". In any case, AI capabilities will increase dramatically over the next few years while human math capability will not. That means that there's a fixed target regarding whatever is currently considered a "serious math problem" and its difficulty level. Soon the average problem solved with a few hundred dollars of compute will be at that bar.

> while human math capability will not.

I actually partially disagree with this. What happened to all the excitement about Intelligence Augmentation (IA)? Now it's AI instead of IA. I think there's so much untapped potential for augmenting our intellect with the likes of https://dynamicland.org and https://folk.computer, as well as the work that's been going on in college math education, things like Lean, etc. I think the only reason human math capabilities haven't expanded that much is a failure of our imagination, not our potential.

I couldn't agree more. The way everyone thunders towards "replace" instead of "improve" is depressing.

> I am at a loss about what to do with these results.

I would recommend publishing them to Palomar (https://palomar-registry.org/) - I have no affiliation, this is an online registry of Lean-verified proofs created by Terrence Tao.

I have submitted a proof there that's also minorly important in an extremely niche field.

Anyway, I feel like it's a good place to dump AI slop lean proofs because the main point of the registry is that it verifies that: 1) your Lean challenge statement is the same as what you informally state you're trying to prove; 2) your Lean proof actually compiles.

This could be useful to future AI slop researchers who want to know if a given result has already been formalized, and they may be able to mine some lemmas from your work. Also, it's good to know for the field in general what has been proven.

I'm fairly certain you can set your publishing name to be whatever you want, so you could set it to be just the word "Anonymous", or the name of the model you used.

It is interesting isn't it.

You asked for a painting. A robot made the painting. You looked at it and said, "well, I guess it's good. Should I put it online or something? Dunno. Hey Fred, what do you think of this?"

Meanwhile, your next door neighbor spends their entire life developing their understanding of life through art. They "understand" (maybe not in a way they can articulate) art. You go next door, you look at their painting and say, "well I guess it's good." But you also understand that your neighbor is just like you, and maybe you are a painter in another way.

I find it strange that, people can't see that, we don't need to solve hunger and poverty and work balance, and etc, by a round-about make-super-intelligent-AI. We could just solve it. It's pretty obvious how to, as well.

We can all be painters, if we put restrictions on the psychopaths.

what about cancer?

If we're all painters, where does the food come from?

Robot farms.

https://www.swarmfarm.com/

OP specifically said "we don't need to solve hunger and poverty and work balance, and etc, by a round-about make-super-intelligent-AI" though. And I don't know how you get robot farms without that.

But the post I was replying to said "If we're all painters, where does the food come from?"

And robot farms are being made now, without AI. Just plain and simple normal robotics.

I mean, let's say you spun up a swarm of agents to rewrite a large component of a well used open source library to be memory safe. You could dump it in a big PR and walk away (we all know how that would go), or you could try engaging, see if they're interested, write something up and see where it goes.

The biggest problem is, IMO, drivebys uninterested in actual results, just getting a check mark, and the equivalent of dropping a 200k line PR on people and expecting them to be interested and do the work for you. These are things many on HN are familiar with and know how to do better :)

> and the equivalent of dropping a 200k line PR on people

I can understand why the community is pissed. So now, lean proofs can be churned out at scale, and the community is left to decipher all of that slop into human understanding. There are bad actors with misaligned incentives coming in with drive-by proofs upending what the community holds dear which is to practice and propagate the art. I applaud them for this declaration.

To re-align incentives the following could happen. AI slop lean proofs are dumped unceremoniously into a lean dumpster, and what gets rewarded are results that could digested into human understanding - via the already followed human review process. Prizes are not given to lean proofs since anyone with sufficient compute can churn them out.

How do you know the proofs are correct?

The numerical results are trivial to check. I wrote the analytical results in Lean by hand before asking a former professor to confirm after asking him to keep this private.

They're valid.

It's really tough to come to terms with it but making academic contributions in general from the outside (with or without AI tbh) is not often welcome and the whole process feels very gate-kept.

If that's the case, that makes me much less sympathetic, even though I can understand how it's very disturbing to see the field suddenly changing like this.

(academic.) Unfortunately the overwhelming majority of outsiders are missing core knowledge (or are cranks), so the optimal prior from a time management perspective is to ignore them. AI just makes engaging more costly because there’s more volume and it’s harder to get signal on whether they know what they are talking about.

Post them here and laugh about people trying to cite them: https://en.wikipedia.org/wiki/Superpermutation

It depends.

If you are trying to understand better the field, then do a good write up of the proofs so that people can learn from it.

If you want to earn the respect of people because you found interesting proofs. Then do a good write up of the proofs so thst people can learn from it.

If you want to plant flags and pollute peoples minds. Then please publish it anonimously, no one wants to correct LLM slop for you.

Probably we should build a repository of AI slop proofs that are only allowed to be publish anonimously. That way people may be more inclined to work on it because they would feel like they are cleaning your house for free.

Maybe I'll end up doing the write ups pseudonymously. I have taken care to make sure the results can meaningfully contribute to field but I don't want to plant flags or really receive credit of any kind. I just think they are interesting.

I like my current life and don't want to get dragged into the current fracas surrounding the use of AI in math.

If you have taken care, then share it with the community. People will be thankful and happy.

The problem is with people that may do it without contributing to the community.

If this was limited to just three results, I would agree with you. But those three are just the ones I've managed to verify myself. The list of unverified results is quite a bit larger.

The field I've been investigating is not large. Even if I were to take the time and care to beat the interesting results into something meaningful, I'm afraid the pace at which I'm able to produce these results would not be well received.

This all comes down to what we think mathematics is. There are two options here:

Mathematics is just the formal system: in that case we will never be able to beat the AI as humans. The goal is then to cover as much of the formal landscape with AI generated proofs to proof as much statements as possible. Success metrics are lines of lean and numbers of proven statements.

The formal system is just a limited representation of what mathematics is: in that case probably some parts of the formal mathematical landscape are more important than others. Not all statements are born equal. And 90% of AI generated proofs will be just noise. Our job as mathematitians is to steer the AI to high mathematical value regions and turn formal proofs into mathematical proofs and insights.

From my point of view we have know since Godel that we are living in the reality of point 2.

Each of the two points implies a very different way of doing mathematics. So pick the one that you think is true and act accordingly.

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