[refulgentis]

Frankly, this reads as a lot of words that amount to an excuse for using only LMArena, and the rationale is quite clear: it’s for an unrelated argument that isn’t going to ring true to people, especially an audience of programmers who just spent the last year watching the AI go from being able to make coherent file edits to multi hour work.

LMArena is, de facto, a sycophancy and Markdown usage detector.

Two others you can trust, off the top of my head, are LiveBench.ai and Artifical Analysis. Or even Humanity’s Last Exam results. (Though, frankly, I’m a bit suspicious of them. Can’t put my finger on why. Just was a rather rapid hill climb for a private benchmark over the last year.)

FWIW GPT 5.2 unofficial marketing includes the Erdos thing you say isn’t happening.

[zamadatix]

I've always found LiveBench a bit confusing to try to compare over time as the dataset isn't meant to be compared over time. It also currently claims GPT-5 Mini High from last summer is within ~15% of Claude 4.5 Opus Thinking High Effort in the average, but I'll wait with bated breath for the millions of amazing apps which couldn't be coded before to start showing up (or, more likely, be told in 6 months how these 2 benchmarks weren't the ones that should matter either). Artificial Analysis at least has the same at 20% from the top, so maybe that's the one we all agree to use for now since it implies faster growth.

> FWIW GPT 5.2 unofficial marketing includes the Erdos thing you say isn’t happening.

Certainly not, unless you're about to tell me I can pop into ChatGPT and pop out Erdos proofs regularly since #728 was massaged out with multiple prompts and external tooling a few weeks ago - which is what I was writing about. It was great, it was exciting, but it's exactly the slow growth I'm talking about.

I like using LLMs, I use them regularly, and I'm hoping they continue to get better for a long time... but this is in no way the GPT 3 -> 3.5 -> 4 era of mind boggling growth of frontier models anymore. At best, people are finding out how to attach various tooling to the models to eek more out as the models themselves very slowly improve.

[nl]

> I'll wait with bated breath for the millions of amazing apps which couldn't be coded before to start showing up

Appstore releases were roughly linear until July 25 and are up 60% since then:

https://www.coatue.com/c/takes/chart-of-the-day-2026-01-22

[zamadatix]

I never claimed people don't make apps with AI. Of course it does - I can do that in a few clicks and some time with most any provider. You've been able to do that for a few years now, and that (linear) trend line starts over a year ago.

I can guarantee if you restricted yourself to just that 60% you wouldn't be responding to me doubting AI apps are already amazing things people are actually supposed to be so excited about using though.

[refulgentis]

One of the best surgically executed nukes on HN in my 16 years here.

[refulgentis]

See peer reply re: yes, your self-chosen benchmark has been reached.

Generally, I've learned to warn myself off of a take when I start writing emotionally charged stuff like [1]. Without any prompting (who mentioned apps? and why would you without checking?), also, when reading minds, and assigning weak arguments, now and in my imagination of the future. [2]

At the very least, [2] is a signal to let the keyboard have a rest, and ideally my mind.

Bailey: > "If [there were] new LLMs...consistently solving Erdos problems at rapidly increasing rates then they'd be showing...that"

Motte: > "I can['t] pop into ChatGPT and pop out Erdos proofs regularly"

No less than Terence Tao, a month ago, pointing out your bailey was newly happening with the latest generation: https://mathstodon.xyz/@tao/115788262274999408. Not sure how you only saw one Erdos problem.

[1] "I'll wait with bated breath for the millions of amazing apps which couldn't be coded before to start showing up"

[2] "...or, more likely, be told in 6 months how these 2 benchmarks weren't the ones that should matter either"

[zamadatix]

I'm going to stick to the stuff around Tao, as even well tempered discussion about the rest would be against the guidelines anyways.

I had a very different read of Tao's post last month. To me, he opens that there have been many claims of novel solutions which turn out to be known solutions from publications buried for years, but nothing about rapid increase in the rates or even claims mathematicians using LLMs are having most of the work done by them yet.

He speculates, and I also assume correctly as well, that that contaminations are not the only reason. Indeed, we've seen at least 1 novel solution which couldn't have come from a low interest publication being in the training data alone. How many of the 3 examples at the top end up actually falling that way is not really something anyone can know, but I agree it should be safe to assume the answer will not be 0, or even if it was it would seem unreasonable to think it stayed that way. These solutions are coming out of systems of which the LLM is a part, and very often a mathematician still actually orchestrating.

None of these are just popping in a prompt and hoping for the answer, nor will you get an unknown solution to an LLM by going to ChatGPT 5.2 Pro and asking it without the rest of the story (and even then, you still will not get such a solution regularly, consistently, or at a massively higher rate than several months ago). They are multishot from experts with tools. Tao makes a very balanced note of this in reply to his main message:

> The nature of these contributions is rather nuanced; individually and collectively, they do not meet the hyped up goal of AI autonomously solving major mathematical open problems, but they also cannot all be dismissed as inconsequential trickery.

It's exciting, and helpful, but it's slow and he doesn't even think we're truly actually at "AI solves some Erdos problems" yet, let alone "AI solves Erdos problems regularly and at a rapidly increasing rate".

[refulgentis]

"...as even well tempered discussion about the rest would be against the guidelines anyways."

Didn't bother reading after that. I deeply respect you have the self-awareness to notice and spare us, that's rare. But it also means we all have to have conversations purely on your terms, and because its async, the rules constantly change post-hoc.

And that's on top of the post-hoc motte / bailey instances, of which we have multiple. I was stunned (stunned!!) by the attempted retcon of the app claim once there were numbers.

Anyways, all your bete noirs aside, all your Red Team vs. Blue Team signalling aside, using LMArena alone as a benchmark is a bad idea.

[zamadatix]

The conversation is certainly not on "my terms" as I didn't write the guidelines (nor do they benefit me more than anyone else). If you are genuinely concerned with the conversation, please flag it and/or email [e-mail] and they will (genuinely) handle it appropriately. Otherwise there is not much else which can be said around this here.

If not, continuing to have a conversation can only happen if we want to discuss the recent growth rate of AI and take the time to read what each other write. Similarly, async conversation can be as clear and consistent as we want it to be - we just have to take the time to ask for clarification before writing a response on something we feel could be a movable understanding. Nothing is meant to be unclear as a "gotcha" and I'll always be glad to clarify before moving on.

I also agree nobody should rely solely on LM Arena for benchmarks, which is not what starting a conversation by using it in an example was meant to imply we need to do. I'd love to continue chatting more about other benchmarks and how you see Tao's comments, as you seem to have walked away from reading them with a very different understanding than I did.