I don't think it is dispositive, just that it likely didn't copy the proof we know was in the training set.

A) It is still possible a proof from someone else with a similar method was in the training set.

B) something similar to erdos's proof was in the training set for a different problem and had a similar alternate solution to chatgpt, and was also in the training set, which would be more impressive than A)

The model has multiple layers of mechanisms to prevent carbon copy output of the training data.

It's all up for debate, but personally I feel you're being too pessimistic there. The advances being made are faster than I had expected. The area is one where success will build upon and accelerate success, so I expect the rate of advance to increase and continue increasing.

This particular field seems ideal for AI, since verification enables identification of failure at all levels. If the definitions are wrong the theorems won't work and applications elsewhere won't work.

Regular WD40 should not be used as bearing lubricant!

I don't get your pessimism...

Nothing of it was even imaginable and yes the progress is crazy fast.

How can you be so dismissive?

I’m an engineer, not a mathematician, so I definitely appreciate applied math more than I do abstract math. That said, that’s my personal preference and one of the reasons that I became an engineer and not a mathematician. Working on nothing but theory would bore me to tears. But I appreciate that other people really love that and can approach pure math and see the beauty. And thank God that those people exist because they sometimes find amazing things that we engineers can use during the next turn of the technological crank. Instead of seeing pure math as useless, perhaps shift to seeing it as something wonderful for which we have not YET found a practical use.

Applications for pure mathematics can't necessarily be known until the underlying mathematics is solved.

Just because we can't imagine applications today doesn't mean there won't be applications in the future which depend on discoveries that are made today.

It's hard to know beforehand. Like with most foundational research.

My favorite example is number theory. Before cyptography came along it was pure math, an esoteric branch for just number nerds. defund Turns out, super applicable later on.

You’re confusing immediately useful with eventually useful. Pure maths has found very practical applications over the millennia - unless you don’t consider it pure anymore, at which point you’re just moving goalposts.

It's unclear to me what point you are making.

It's obviously not LLM-generated.

It's not.

Evidence shows otherwise: Despite the "20x" length, many people actually missed the point.

If the point was triggering a reply, the length and sarcasm certainly worked.

I agree brevity is always preferred. Making a good point while keeping it brief is much harder than rambling on.

But length is just a measure, quality determines if I keep reading. If a comment is too long, I won’t finish reading it. If I kept reading, it wasn’t too long.

To give them the benefit of the doubt, people who talk to AI too much probably start mimicking its style.

yea, i was suspicious by the second paragraph but was sure once i got to "that’s not engineering, it’s cosplay"

I’m confused by this. I still see this kind of phrasing in LLM generated content, even as recent as last week (using Gemini, if that matters). Are you saying that LLMs do not generate text like this, or that it’s now possible to get text that doesn’t contain the telltale “its not X, it’s Y”?

> But if it was there is currently no way for anyone to tell the difference.

This is false. There are many human-legible signs, and there do exist fairly reliable AI detection services (like Pangram).

> It wasn't AI generated.

You're lying: https://www.pangram.com/history/94678f26-4898-496f-9559-8c4c...

Not that I needed pangram to tell me that, it's obvious slop.

the poster is in fact being very sarcastic. arguing in favor of emergent reasoning does in fact make sense

It's a formal sarcasm piece.

I thought the mockery and sarcasm in my piece was rather obvious.

We need a name for the much more trivial version of the Turing test that replaces "human" with "weird dude with rambling ideas he clearly thinks are very deep"

I'm pretty sure it's like "can it run DOOM" and someone could make an LLM that passes this that runs on an pregnancy test

come out of the irony layer for a second -- what do you believe about LLMs?

I mean.. LLMs have hit a pretty hard wall a while ago, with the only solution being throwing monstrous compute at eking out the remaining few percent improvement (real world, not benchmarks). That's not to mention hallucinations / false paths being a foundational problem.

LLMs will continue to get slightly better in the next few years, but mainly a lot more efficient. Which will also mean better and better local models. And grounding might get better, but that just means less wrong answers, not better right answers.

So no need for doomerism. The people saying LLMs are a few years away from eating the world are either in on the con or unaware.

If all of it is going away and you should deny reality, what does everything else you wrote even mean?

Yes, it is simply impossible that anyone could look at things and do your own evaluations and come to a different, much more skeptical conclusion.

The only possible explanation is people say things they don't believe out of FUD. Literally the only one.