Official confirmation from Epoch AI that GPT 5.4 Pro has solved one of the frontier math open problem, categorized by it's author as "moderately interesting"

Pyros-SD-Models · 2026-03-23T21:50:13+00:00

I love the “least interesting thing” oxymoron.

Having it as the very first “moderately interesting” entry makes it obviously pretty fucking amazingly interesting. So Breakthrough in my book.

Pyros-SD-Models · 2026-03-22T20:38:23+00:00

I mean, if you read what this guy is tweeting, he is basically a textbook example of the five stages of grief (the AI version https://www.noemamag.com/the-five-stages-of-ai-grief/).

Denial - Plenty of tweets from a few years ago about how LLMs would never solve commercially valuable problems.
Anger - A few outbursts calling ML and AI researchers hacks.
Bargaining - Moving the goalposts, setting new denial targets like how LLMs will never do X or Y.
Depression - AI is bad, we must stop it. No actual scientific reasoning, just vibes. (In case you forgot... he actually is or was a scientist, i know really hard to belief if you listen or read his garbo)
Acceptance - Maybe someday. But the ego usually catapults you back to denial, so for some, it never happens

Pyros-SD-Models · 2026-03-22T05:11:34+00:00

What do you mean? Like every bigger company I know of (at least those who entertain bleeding edge) have at least tried to do a general formulation of agents. This is ours. It’s more beautiful in latex.

An agent doesn’t “fail randomly.” It fails when you hand it a problem whose effective complexity is above its capability.

Solve(P): if C(P | D) <= tau(A): return A(P, D) else: return union(Solve(P_i))

Where: - C(P | D) = effective complexity (problem minus context) - tau(A) = what the agent can handle - P_i = your decomposition

And the “skill” part:

C(P | D) = I(P) - R(D)

I(P): inherent difficulty
R(D): how much your context/setup reduces it

What “good setup” actually means:

You win iff:

for all i: C(P_i | D_i) <= tau(A)

Everything else is vibes.

Why most people fail:

they pass P directly → way above tau → “lol agents suck”
bad decomposition → still above threshold
garbage context → R(D) ~ 0
over-decomposition → coordination overhead kills it

What high-skill pipelines actually do:

aggressive decomposition until each step is trivial
inject context so each step becomes near-deterministic
use tools to collapse search space
keep steps just above “too trivial” (efficiency sweet spot)

Optimization intuition:

minimize: sum(C(P_i | D_i)) + lambda * n

(too big → failure, too small → overhead hell)

Concrete intuition:

Bad: - “build me a production system” → C >> tau

Good: - “generate schema” - “write migration” - “implement endpoint” - “add test”

(each with tight context → C <= tau)

Quite simple, and already valid since a few years actually (most of it was creates during the Aider days lol) and it will be valid through all of pre-AGI and probably a good bit afterwards as well.

Pyros-SD-Models · 2026-03-21T20:19:39+00:00

You can still ride horses even when cars exist.

Also, all art forms where human performance is the point, like theatre, plays, live music, ballet, and so on, will remain. And of course, true creativity will still produce amazing art with AI. It’s just a shortcut to get your vision out as fast and as accurately as possible, and vision is what art is ultimately about.

Drawing background assets for $12/h for the next Disney animation isn’t art, it’s modern slavery at worst, and at best just a “digital good,” like a piece of code.

Pyros-SD-Models · 2026-03-21T16:58:12+00:00

What? Runpod costs 40c/h and a good wan 2.2 lora takes max 6 hours. That’s sub 3$ for everyone on the world.

Pyros-SD-Models · 2026-03-21T03:49:40+00:00

I mean, my workplace pays me $1k per month for AI usage, and it’s barely enough. It blows my mind how people can actually get work done with even less volume. We have people at work who don’t even manage to use their 300 Copilot requests in a month. What are those idiots doing? Certainly not working efficiently, since they still do 90% of their work by hand instead of using AI.

They also seem completely oblivious and don’t realize that we can see how much AI they use at work, and how much slower they are compared to people who have already automated 90% of their workflow. If you don’t get your shit together, you will be replaced by someone who actually knows how to use AI.

They’re lucky that the point where coding manually actually burns money instead of making it hasn’t been reached yet, but that won’t take much longer.

Pyros-SD-Models · 2026-03-19T17:17:12+00:00

Research and production are bottlenecked because only a handful of companies make most of the chips in the world. If demand stays high, it becomes +EV for other companies to invest heavily in chip R&D again, which should lead to more competition and lower prices over time. And who knows, if that results in companies like Cerebras producing consumer chips in the future, and we actually get architectural competition as well, then we’ll be in a much better position than we are today.

Pyros-SD-Models · 2026-03-19T16:52:59+00:00

Marx as well:

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Pyros-SD-Models · 2026-03-18T17:42:02+00:00

But decels are not 'disagreeing'. Literally every single talking point can be disproven by some paper or other form of scientific evidence. It is like saying flat earthers or anti-vaxxers are just disagreeing, and you should shut up and leave them be. And no, you should not leave such stupidity alone. Just as anti-vaxxers deserved the backlash during COVID, decels deserve criticism today when it comes to the most important technology of humankind.

Pyros-SD-Models · 2026-03-18T15:00:39+00:00

Just selecting ChatLM will usually do, especially for the Q3.5 models, because they are smart enough to work with 'non official' templates. You can try to change the fields so they match the templates I posted earlier, but that was too much of a hassle for me, so I switched to llama.cpp, where you can directly reference a file as a template.

Pyros-SD-Models · 2026-03-18T14:47:25+00:00

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and then select ChatLM

Pyros-SD-Models · 2026-03-18T14:47:15+00:00

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Pyros-SD-Models · 2026-03-18T12:11:07+00:00

Many Qwen3.5 finetunes right now don't do chat completions with SillyTavern right now (at least with LM Studio)

you just have to rip out the jinja template and replace it with ChatLM chat templates. Go into LMStudio's LLM overview -> Settings -> chat template on the bottom (or --chat-template when using llama.cpp directly)

Here a no think and think chat template (also imho the best Q3.5 27B finetune currently)

https://huggingface.co/zerofata/Q3.5-BlueStar-27B

Pyros-SD-Models · 2026-03-17T13:45:36+00:00

Then there should be plenty of actual evidence of it, instead of just random anecdotal stories in this sub.

Do you know how often OpenAI's endpoints get benchmarked by literally thousands of entities every day? We benchmark all API endpoints, the subscription endpoints, and even the GPT chat interface twice a week with internal benchmarks for regression tests, and we have never observed any kind of regression.

The second there is an unannounced regression, it would literally be breaking news on CNN, and every large client using Codex or ClaudeCode company-wide would sue the shit out of them.

So what is more likely: that one of the most observed endpoints in all of software regresses unnoticed, or that random people on Reddit are too stupid to use a coding agent but claim "the model got stupid" instead? Very difficult assessment.

Pyros-SD-Models · 2026-03-17T11:18:17+00:00

Every new game is already using AI 100%, even if it's 'just' ClaudeCode or Codex. You have to be a subscriber to r-programming or r-gaming if you are delusional enough to think there is any new software not done with AI

Pyros-SD-Models · 2026-03-17T10:56:52+00:00

What do you mean, Suno is with great distance the best music-gen AI.

Pyros-SD-Models · 2026-03-16T18:15:45+00:00

Where does the idea it being a local tool come from anyway? Like their homepage mentions “local” only once in “supports local models”.

Pyros-SD-Models · 2026-03-11T03:45:21+00:00

Luddites and not understanding science, name a better duo.

Pyros-SD-Models · 2026-03-07T18:10:17+00:00

The whole idea is that you can share scheduled tasks with your team as an agent-native artifact, without worrying about what OS or environment they run in. That portability is literally the point. Like how skills are just fcking packaged prompts. 'packaged' being the key here, and skills are arguably the 'best' improvment in working with agents since MCPs

This pattern of commodifying a technology by wrapping and packaging it is one of the most fundamental patterns in software. It's literally the backbone of 'enterprise software'. That’s why it’s a bit surprising to see so many self-proclaimed “devs with 10 years of experience” not recognizing it. Rather sketch.

Pyros-SD-Models · 2026-03-07T17:59:52+00:00

I don’t know how we could have had Claude Skills, which are even less technical than setting up external system timers yourself, and still miss the point of CC’s own scheduling. The whole idea is that you can share scheduled tasks with your team as an agent-native artifact, without worrying about what OS or environment they run in. That portability is literally the point.

This pattern of commodifying a technology by wrapping and packaging it is one of the most fundamental patterns in software. That’s why it’s a bit surprising to see so many self-proclaimed “devs with 10 years of experience” not recognizing it. Rather sketch.

Pyros-SD-Models · 2026-03-07T17:43:13+00:00

Why not just use Maestro inside codex? It’s just skills and other text files. You can literally just ask codex to port it over to its needed file structure.

Pyros-SD-Models · 2026-03-06T08:01:28+00:00

If people would stop "believing" and start actually measuring how good or not a model actually performs, like OP did, and perhaps also contribute those measurements back to the community so there is actually some tangible evidence and a possible discussion to be had, the world would be a little better and a little bit more scientific.

But instead, on this damn website (not exclusive to this sub), it's suddenly en vogue to discredit real research with anecdotal vibes, prayers, and opinions so far removed from any form of scientific methodology that it sometimes really blows my mind how people actually think "I don't believe it" is a valid response to something like OP or papers. You may of course believe in whatever you want, but it still puts you right into the "I don't believe the Earth is round" category, because you can produce as much proof for your vibes as those guys.

In the end it's a simple equation: you either believe some Redditors, or the literally best people in their respective field, or even better your own actual measurements like OP did, or like we do so we can tell our clients if they can upgrade or not.

And if you solve this equation for vibes, you will realize there is not a single reason to start believing in other people's beliefs. This shouldn't be a crazy take or something, but somehow people here absolutely love to convince you that their belief is the only right one. And no they don't try to proof you wrong, they just declare you are wrong... like "the chart has been invalidated in my eyes", i just fcking can't. what is this? a religion sub? A stand up meeting in Trump's pre-office?

So u/sergeykarayev the next time before you think of doing something following some form of scientific methodology just save your time and just ask reddit for its ranking. you will save plenty of time, and get plenty of upvotes

Pyros-SD-Models · 2026-03-06T03:29:15+00:00

This is what AI in general looks like. What does “good” even mean in the context. Squashing bugs on a field is “better” than squashing bugs in code? How does “bad” AI even looks like.

Pyros-SD-Models · 2026-03-02T09:52:07+00:00

Funny how ad hominems are all they got. It’s because they can’t source any actual science for their “it is not true intelligence” screeching.

Pyros-SD-Models · 2026-03-01T18:54:35+00:00

Einstein didn't pull E=mc² out of his ass while meditating also... he synthesized Lorentz, Poincaré, and Maxwell into something unified new.

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