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GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

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Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#461

Earlier quoted context omitted.

The 2 most notable/interesting solutions have come from Open AI directly, but most of the 'LLM solves open problem' category didn't and has come from 3rd parties doing their own thing with publicly available models. I don't see why one would assume they're running models on hundreds of problems. Most likely they have a few problems they especially care about that they run on.

What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Remember back in the day when Deep Mind made AlphaGo? That made huge waves for two reasons: one, it was very well understood by AI researchers that beating expert humans at Go was very hard; and, two, that Go is a game of great cultural significance to literall…

>What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those.

Erdős problems vary enormously in difficulty and significance. The fact that a problem is obscure to non-mathematicians does not make its solution unimportant. There are also many major open problems in computer science that most laypeople have never heard of.

>That they started with Erdős problems? I'd have gone for a Millennium Prize problem, first. P vs NP, Riemann, Navier Stokes, those are heavy-weight results that would establish AI as the de facto approach to mathematics for the foreseeable future.

Solving the biggest, most famous open problems would "establish AI as the de facto approach to mathematics for the foreseeable future"? It would do a lot more than that.

>That's exactly how research works in general, both in academia and in industry.

Then what exactly is the objection? Research normally produces many failures and incremental results before a major success. Do you apply this survivorship-bias criticism to every published mathematical result, or only when a machine contributed to it?

>Actually, that's a good point but it's in support of my contention.

If they're running as many problems as constantly as you imagine then they did not miss all that. So either they're just not sharing it us which contends with your "desperate to demonstrate mathematical competence" or they have their eyes on a more curated set.

>Or, to abuse Fermi's question, where is everybody?

If we had as many verified alien encounters as LLM contributions to open problems, nobody would be invoking the Fermi Paradox. Where is everyone? Right here.

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#462

Earlier quoted context omitted.

What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Remember back in the day when Deep Mind made AlphaGo? That made huge waves for two reasons: one, it was very well understood by AI researchers that beating expert humans at Go was very hard; and, two, that Go is a game of great cultural significance to literall…

>What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Erdős problems vary enormously in difficulty and significance. The fact that a problem is obscure to non-mathematicians does not make its solution unimportant. There are also many major open problems in computer science that most laypeople have never heard of.…

>> Then what exactly is the objection? Research normally produces many failures and incremental results before a major success. Do you apply this survivorship-bias criticism to every published mathematical result, or only when a machine contributed to it?

Yes I do. Not mathematical results specifically but generally research results. I might even have articulated that criticism on HN. I don't know if I could search for it easily though.

>> If they're running as many problems as constantly as you imagine then they did not miss all that. So either they're just not sharing it us which contends with your "desperate to demonstrate mathematical competence" or they have their eyes on a more curated set.

The people desperate to demonstrate mathematical competence are the AI companies. The people discussed in the part of my comment you quote are "random people" by which I meant the "3d parties" in your original comment.

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#463

Earlier quoted context omitted.

>What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Erdős problems vary enormously in difficulty and significance. The fact that a problem is obscure to non-mathematicians does not make its solution unimportant. There are also many major open problems in computer science that most laypeople have never heard of.…

>> Then what exactly is the objection? Research normally produces many failures and incremental results before a major success. Do you apply this survivorship-bias criticism to every published mathematical result, or only when a machine contributed to it? Yes I do. Not mathematical results specifically but generally research results. I might even have articulated that criticism on HN. I don't know if I could search f…

>Yes I do. Not mathematical results specifically but generally research results. I might even have articulated that criticism on HN. I don't know if I could search for it easily though.

Okay Fair, but then this is a general research issue and not really a Open AI issue.

>The people desperate to demonstrate mathematical competence are the AI companies. The people discussed in the part of my comment you quote are "random people" by which I meant the "3d parties" in your original comment.

I'm not sure you got the point i was making. The point there was that if Open AI were running as many problems as frequently as you imagine they are then those 3rd party results should have been achieved by them, and if they're really so desperate to tell us how good the model is for math then why didn't they tell us ? Why have they only announced 2 results when they could have announced near a dozen by now ? Sure these 2 are in a class of their own, but some of the others are genuinely impressive in their own right and would certainly help that narrative you're talking about.

Either they're just not telling us and aren't as desperate as you imagine, or they're simply only interested/running models in a relatively few set of problems.

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#464
post #380
post #307

Earlier quoted context omitted.

I was baffled enough by this comment to take my copy and look. The Nullstellensatz is an exercise late in the book long after Noetherian rings are introduced and they don't even do the Rabinowitz trick in the hints as they have enough theory to hit it the hard way. Determinants are nowhere to be found.

It's been a few years (~ 15) since I read it. The determinant trick I'm referring to is used in prop 2.4 (in the Version I found via Google). They use the determinant of the adjugate matrix if I remember correctly... But they just hit the reader with this without any motivation or even naming it.

For Nakayama lemma (but they give a cleaner proof later). Note that the book was from the 1960's and from lectures at Oxford: matrix manipulations like that were a lot more commonplace.

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#465

Earlier quoted context omitted.

The 2 most notable/interesting solutions have come from Open AI directly, but most of the 'LLM solves open problem' category didn't and has come from 3rd parties doing their own thing with publicly available models. I don't see why one would assume they're running models on hundreds of problems. Most likely they have a few problems they especially care about that they run on.

What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Remember back in the day when Deep Mind made AlphaGo? That made huge waves for two reasons: one, it was very well understood by AI researchers that beating expert humans at Go was very hard; and, two, that Go is a game of great cultural significance to literall…

One's at https://www.starfleetmath.com/

https://news.ycombinator.com/item?id=48914646

Here's another: https://x.com/edgardobriban/status/2077082912021786660

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#466

Earlier quoted context omitted.

>> Then what exactly is the objection? Research normally produces many failures and incremental results before a major success. Do you apply this survivorship-bias criticism to every published mathematical result, or only when a machine contributed to it? Yes I do. Not mathematical results specifically but generally research results. I might even have articulated that criticism on HN. I don't know if I could search f…

>Yes I do. Not mathematical results specifically but generally research results. I might even have articulated that criticism on HN. I don't know if I could search for it easily though. Okay Fair, but then this is a general research issue and not really a Open AI issue. >The people desperate to demonstrate mathematical competence are the AI companies. The people discussed in the part of my comment you quote are "rand…

Or they're not solving as many problems as they'd like, despite trying.

Re: GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]

#467
post #26

Unlike the unit distance problem, the impressive thing here is that it is a proof rather than a counter-example. However, it seems the proof is extremely concise so it seems that it is exploiting a clever trick that somehow all the experts missed. So not to dunk on this amazing result (or move the goal post), but it seems now the only achievement that AI hasn't managed in mathematics is presenting an autonomous "theo…

the unit distance problem's paper was human-summarised and condensed significantly from the initial LLM output, so it seems the model did do some theory-building there (possibly providing motivation for the clever trick as a natural deduction, at least in its eyes) before humans cut off all the chaff; I imagine the development was similar here.
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