Posted by dbreunig 17 hours ago
First off, Opus 5.5 built working weights and code with only two prompts:
1. Read this article and any relevant source code: https://divagr.com/blog/qwenputer. Then explore if you could emulate the chip and ram in a Nintendo Entertainment System (as people do today with FPGAs in MISTRs) using this technique. If so, what size model would you have to build and if you could use smaller faster ones, could you get it to be at the standard clockspeed.
It returned charts well illustrating any model would be _slow_. But it's still fun, so the second prompt was:
2. I think we should build it! Just for fun. It's okay if it's not fast. We want to be able to have the weights, and a cli to run them that we can point at a ROM.
Now while this was an _epic_ run by Opus (5.5 is a crazy capable model), this is a surprisingly well-structured challenge.
There is a long-lived and incredible community of classic gaming emulation work online for it to reference. And that community has created…conformance tests! Opus found them and built against one, that has >3k golden instructions: https://github.com/christopherpow/nes-test-roms/blob/master/...
Also, there is the original Qwenputer repo that Opus used to drive the weight writing. That was essential.
But this is a great example of what these models can do with proper reference materials, great specs, conformance tests, and clear direction.
I'm doing something similar but not for an emulator, using tests other projects in a similar space use to validate things.
I also know a friend that feeds Claude Gherkin formatted test criteria, and apparently that yields insanely good Claude output.
Claude Gherkin
https://cucumber.io/docs/gherkin/
Very neat, seems quite appropriate for the way people currently work with LLMs.
I guess humans need their oracles too: teachers, encyclopaedias, degrees, phds.
Bravo, awesome project, really creative!
I suppose it doesn't need to necessarily be in the weights, a hybrid LLM + internal fixed function blocks that aren't encoded in the weights could be quite interesting.
Combine this with latent reasoning and it gets pretty wild.
A very useful fixed function region in my mind is a symbolic execution engine, capable of only following a well-defined grammar. Perhaps a lisp would be good too?
I wish they would let me use claude desktop, I really hate looking at the terminal and don’t know how to customize it to make it more readable
On a comment where you discuss a powerful tool for looking up information, you claim ignorance about a piece of information that same tool could explain to you! What the heck!
18 months ago: it can do some things but it’s generally not useful.
12 months ago: wow; this can write ok code that a human has to do a lot of review to make sure it’s ok.
6 months ago: holy fuck I’m shipping great stuff with only the occasional redo.
3 months ago: Jesus Christ this is actually pretty fucking great. I have to work entirely differently; becoming a manager of my single agent launching sub agents.
1 month ago: my god I am shipping more, faster, and more useful than ever.
Today: we have fleets of highly effectively domain expert agents working entirely autonomously and shifting between fleets depending on domain, available usage remaining, and we’re shipping 10x with 100% better reviews than before—expanding by the day and self-improving its own harness.
—-
Next week: the agents will prioritize code golf.
The week after that: everything is written in ASM.
We’ll come full circle in 3y
e: fyi; this is my personal progression with LLMs.
I have experienced directly what the evolution of cloud based software, and now AI based tooling, has done to team sizes on delivery projects.
Cannot understand how they don't get how all the performance improvements directly correlates to smaller team sizes, in shareholders driven economy.
So far I have been lucky, and just hope to have enough savings when time comes, as finding jobs after 50s wasn't already easy without having to add AI on top.
The org structure is optimised to reduce or even minimise individual agency, explicitly at the cost of efficiency.
Teams have fiefdoms, private repos that the rest of the org can't see. You are not granted permission to see what permissions you have. Byzantine department structures. Shipping "hello world" to production takes 3-6 months and nobody can imagine it working any other way.
There's actually no central directory of teams or processes. To get anything meaningful done, you need the co-operation of maybe 8 teams but there's no consistent way to engage them all. You have to negotiate with them all in different ways, they're like little warlords, sitting and guarding access to some vital resource you need. They have established a ticket-based interface with a 7 day SLA on top of a perfectly good vending API that could do what you need in seconds. Sometimes a blocking team has a 3 month backlog so your project will just have to wait.
Everything is always in the process of being restructured, so no end to end 6 month process happens the same way every time.
These organisations could use AI to run the end to end process in minutes. Heck, they could just put APIs on top of what they already have. But the way they WANT to use it is to keep doing what they're doing but with EVEN MORE form filling and paperwork.
You would think they would get outcompeted, but no. The "IT organisation" sits like a brain slug on top of an enterprise with substantial regulatory, capital and execution moats.
Big cuts of course do happen in these places, but it's often for optics (we need to signal that we care about efficiency, and AI is a great excuse). But you can't protect yourself by being efficient and good at your job, because the cuts were not about output.
I want to do MORE with the same amount of folks.
I'm not disputing productivity improvements can lead to smaller teams, particularly in a shareholder-driven org; that's a separate conversation, IMO. The fact I work at an employee-owned organization, currently, I suppose I'm simultaneously a worker and an influential shareholder.
I was trying to say, running counter to what is frequently mentioned on HN about FAANG Eng Leaders, that I don't equate engineering success with growing headcount. I've always preferred building small, highly effective teams that can accomplish more without needing to grow, just for the sake of growing headcount. My want to do more with the same number of people isn't an argument that headcount won't shrink. It's an argument that growing headcount was never my measure of success in the first place.
No that you asked, but, my measures of success are: are my engineers happy (being that many of them have worked with me at least one company before, and one at 4, I feel they are); are we playing with the latest technologies; and are we learning new things every day?
So do I, but I've been in two companies that had to let me go because the investors said they didn't want my role to exist any more. Plus two other roles where the company straight up ran out of money.
It's not always up to us.
First it was offshoring, then managed cloud environments and servless, followed by ready made SaaS products, low code/no code iPaaS cloud products, and now agentic runtimes.
The ones doing content translations, asset management were the first, followed by classical infrastructure people, then most backend roles, and so it goes.
Good! Costs going down is great
Why would we care about team size?
Doesn't the world have many more software engineers today than at the start of the evolution of cloud based software?
One day it is you that gets given the cubicle box and door walk out.
Not at all, given the layoff rounds for various reasons, which fail to find new jobs, because now corporations are doing more with less.
You don’t care if you’re understood?
Edit: My best interpretation is that you think the commenter believes the gains they’re saying are good, that they’re rooting for them, or some sort of other anti-human bend,
and normal readers just aren’t seeing that.
Also “1 month ago,” but s/ASM/Rust
This is an genuinely good minimalist good editor that is created in mostly assembly that was created with the help of AI[0]
I maintain a fork of it which basically adds scratchpad ability to it and is something that I use daily myself for what it's worth[1]
My fork was created with the help of GLM 5.3 (an open-weights model)
The future is already here in some sense. I could in theory add more features but I intentionally add not more features because asm is still slightly difficult for it to write but in some sense the tradeoff has been/could be worth it. It was more of an experiment really and I am really impressed by it.
in many ways, forcing AI to write asm does make you now think intentionally of features and ironically prevents feature creep and makes you think of stability of the product (atleast right now for me anyways)
[0]: https://rhun.app
I like these kinds of projects because it helps to show the massive compute requirement between LLMs and ordinary programs.
A while back I saw some people saying we would just have LMMs hallucinate an entire operating system every single frame. I guess technically it's now proven to be technically possible, but it would be thousands of times slower while requiring thousands of times more compute (a multi-million x difference from an ordinary OS!).
It’s a bit like when a human brain remembers facts, if you sat down and computed the hash values of the thing you were trying to remember, and traced out a DB lookup in your mind, it’d be a lot slower than just “oh yeah I remember that”.
To misquote a certain YouTuber: LLMs are just games, unlimited games, but no games.
Gosh. That would be a very silly use of an LLM.
Bad use of any AI, even image/video models which are certainly less wrong than this. Stuff like DLSS show we're getting stuff that could generate a game's graphics frame-by-frame, but even though it's possible to have an entire game environment (not just graphics, everything) done by an AI, such things demo better than they play due to temporal coherency.
That said, having an AI make the code for each thing as you need it, might work somewhat OK eventually. Wouldn't trust it today (security, data integrity, and a tendency to cheat on tests), but eventually it could happen.
A key point of DLSS (5) is that it is significantly guided by ground truth rasterization or raytracing info. It's not intended to replace graphics pipelines, it augments them to produce more detailed surfaces and interpolate frames more efficiently than calculating all of it traditionally is. But you have to calculate some of it to get these results, it can't be a purely AI solution without looking incoherent.
Doing it in a way that isn't described as "hilarious" is probably also possible in the time since that video came out. Doing it in a way which isn't described as "a security nightmare" or "liable to lose all your data", probably not yet. Not as vibe-coding, at least.
We have Jev to prove LLMs that output constrained decisions are useful. Why not make LLMs just output UI natively?
At a fast enough inference speed, you could just connect the network to it.
So an LLM would then just take the network, user input, and output a UI, with tool calls to deal with memory and other resources. In theory, you don't need an OS any more.
> hallucinate an entire operating system every single frame 1. I don't know that "hallucinate" is the right word here... any more than Windows 11 itself is a hallucination, for example 2. I don't personally think that this system is a million (thousands x thousands, from your attestation) times slower, but given Moore's Law, even that isn't the worst thing ever. this is the low water mark.
1) Have a single person vibe together a computationally inefficient solution in 1 month that runs transformers on some backend.
2) Hire a team to work for 2 years to design, perfect, optimize, plan, revise, and architect a solution.
The risk/reward for 1) is extremely better than 2). Given the turnover for entertainment in this day and age it doesn't make sense to do all this complex stuff.
are we not talking about the NES?
These are just machines for ripping off existing games/programs with mostly accurate simulations. You can't vibe together a transformer of something that doesn't exist with meaningful control over the results.
You're comparing apples to oranges there!
To hallucinate is arbitrary, you can use a 2B image param model, it will hallucinate an OS no problem* running real time!
What this post is about is completely different, which is actually emulating the complete system in an LLM - that is hundreds (or more) times slower.
*absulutely crappy quality tho, unusable OS in practice
Now is that a desirable product? Would it succeed on the merits in the marketplace? Maybe it would...
It's called a Nintendo emulator.
That's kind of the point here.
Code isn't going anywhere. It can be literally billions or trillions of times more efficient than an AI, and as AIs scale up that number just continues to grow and can completely plausibly hit quadrillions in our lifetime. What relationships humans have with code is a completely different question, but the idea itself isn't going anywhere. Anyone who thinks otherwise has failed to grasp just what producing a single token from an AI actually entails.
For example, Minecraft in Minecraft [0] is (while impressive) slow and inefficient too, but it doesn't tell us much about humans except that some of them are weirdly ambitious in their projects.
But at some point we’re hitting a wall here. If we want our software to undo 100,000x more processing powers, we need that llm software emulation layer.
This is amazing, love it! Qwenputer is very cool too
Reality says otherwise, especially from those who run LLMs in production at a large scale. Hacks such as baking in the weights with tiny experiments doesn't disprove anything.
The same LLM boosters also continue to repeat one of the biggest misconceptions: "sEt TeMperaTurE tO zERo tO aChiEvE fUlL dEterMinIsm."
This concept was hyped up (because DeepMind) for a while at the time and in reality it amounted to nothing. This is just the second reincarnation of a similar concept but with added extra saturated slop and hype on top.
Maybe the bots will appreciate it more, after all, it seems to be written for them.
https://www.reddit.com/media?url=https%3A%2F%2Fi.redd.it%2F5...
"Mario thanks you".
