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PaperclipPerfector  3d ago (text post)   11422 thread views

Culture War Roundup for the week of October 5, 2026

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I'm quite sure they have. These math results are likely almost an afterthought; I wouldn't be surprised if they've already put 10x of the compute they used for these math results into researching ML.

10x? More like 100-10,000x I'd wager. See the piddling $4 million estimate above. It makes little difference even if it cost them $40 million instead. >>$100m is the ballpark of where it might make sense for them to not try, because the reputational aura and PR is worth it.

What did people think RSI meant? Vibes? Papers?

"sub-incremental counterexamples to previous conjectures with no practical applications"?

No doubt. I'm sure you could describe the majority of human-derived mathematical findings in the exact same words. I'm sure figuring out optimal square-packing has made billions of dollars for someone.

Nobody is making any money on a 1-10^xx exponent on integer multiplication's big O -- the fact that you think this shows that you are relying on an unreliable interlocuter to form your opinions.

I don't dispute that some of the other results may have some useful application, but the ones of this form are only interesting in the sense that humans tend to expect round numbers, and have been mostly correct in this assumption to date. (I do share this expectation and personally think it's more likely that there's some kind of mistake in these proofs -- but if I'm wrong, that's interesting!)

Your bot can probably explain this to you if you ask, but briefly: Big-O notation typically disregards the portion of algorithmic complexity that's constant doesn't and depend on the size of the dataset; ie. whether a loop takes a millisecond or a minute to execute once is not considered. Something that takes a minute per cycle but is O(1) may be better than something that does it in a millisecond but is O(n^2) -- it depends on how many "n" you are interested in though.

TBH I haven't looked into the actual algorithms involved here, but given the length of the proof I'd expect the constant term (call it overhead) to be quite high compared to existing methods -- considering the tiny difference in the exponents, you would need n to be literally approaching infinity for the proposed algo to make any difference at all. In the case of the integer math, this would mean that multiplying integers of ~infinite length could be somewhat faster -- but we can't even test it, because computers don't have infinite memory.

Nobody is making any money on a 1-10^xx exponent on integer multiplication's big O -- the fact that you think this shows that you are relying on an unreliable interlocuter to form your opinions.

Do I think this? Nobody told me. It's not true. I've never said it, I've never thought it, and you can go look.

I'd prefer you stick to what I've actually said. Or if that's what you thought I implied, I ask that you at least acknowledge when I clarify otherwise.

I also know how Big O works, for the record. I took CS courses in my free time once. I am a nerd.

You just said it though! (well, maybe your LLM did)

I also know how Big O works, for the record.

It doesn't really seem like you do; an optimal square packing algorithm that is better only in the case of infinite squares is not making anybody any money either.

You have missed clear sarcasm. Now you know better.

I don't think I've agreed with a word out of @BurdensomeCount 's mouth in my life -- but you truly are a curious case.

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