while I agree with your general point, since you're asking, the table from Paul Bourke's marching cubes code comes to mind:

https://paulbourke.net/geometry/polygonise/

another one is the "fast hash" GLSL pseudo random number generator that everyone copies from Inigo Quilez:

    float rand(vec2 co){
        return fract(sin(dot(co, vec2(12.9898, 78.233))) * 43758.5453);
    }

> reduces antialiased vector paths into unique triangle patches and rasterizes them through a massively parallel pipeline with pixel local storage

this is typical type of LLM sentence that kinda runs under the radar, sounds clever, but if you actually look at it, none of it makes sense

- what are "antialiased vector paths"?

- why mention "unique" triangle patches? (surely it wouldn't render duplicate ones)

- a "massively parallel pipeline"? like a GPU you mean?

- "pixel local storage" sounds like an obnoxious marketing term if it's not defined in the article (which it isn't)

anyway I quickly skimmed the article after that but it was little substance

It literally couldn't have done it without tools, so your claim is not even relevant to this discussion.

They also pumped millions into searching for the lowest hanging fruit that would impress people like you, "hm I wonder how many millions they are pumping into solving actually useful problems like climate change or something".

Okay fine. I think we can agree to disagree on that.

And how is _that_ different from making the human memorize a billion weights and do matrix calculations in their head, in order to generate tokens?

How is _that_ different from a hive of bees trained to do the same?

Go ahead, argue these things are all the same ...

they talk about it like there's a "wanting" in there, that is distinct from both the original prompt, as the steering/warning prompt

if that's true, it would be very interesting, but if it's not, that would also be very interesting and even helpful

yeah, that's the dream. I do it whenever I get the opportunity to

You mean, something like the sandbox they weren't supposed to break out of?

TBH the more I read of these reports, the less I believe this.

These agents just weren't behaving in any way I've seen normal/publicly available agents do.

Sure I've heard (from other people, not seen myself) that they sometimes try to get around file system permissions or use `bash` to write when their `write` tool is disabled, or such.

But this is definitely another level, entirely.

There is this vague sense of desperation coming from many of these logs and I am sure they must have been motivated by something else, too.

We didn't see their system prompt or main prompt, right? We've only seen reports from what happened after deciding to break out.

OAI claims this was triggered by the task being literally impossible. That also doesn't quite add up, unless the other tasks that were possible, simply weren't hard enough? Otherwise wouldn't agents already start hacking when faced with a really hard task, too? Cause they wouldn't be able to differentiate. At least some of them would have started to somewhat poke their sandbox a bit?

Also I would have expected to see a few tens of other (perhaps less severe) public incidents from random people setting their models to YOLO, accidentally hacking stuff, this incident has been loud and messy enough, that if it happened to a few other people, we'd have heard about it.

Unless OAI's story is that it was specifically this batch of agents that crossed some threshold of going wild? (which would also raise some serious questions about how serious they take that danger ..).

Or maybe it is only dangerous if you have the compute resources to run 700 agents for weeks?

honest question, but almost literally everyone doing anything with web technology knows this is simply not true, right?

there's no such thing as "read only Internet" and restricting an agent to GET-requests only to accomplish that, is akin to using base64 for "encrypting" your password

People who don't know these "Meta glasses" exist (and they shouldn't need to), would have no idea that the thing is even capable of recording.

It's subterfuge and while you could argue that this subterfuge was "unintentional", but imho that's mincing words, and also given that it's Meta, not entirely in good faith.

Can I assume that you have good enough eye sight that you don't need to wear glasses if you choose to? Because as somebody who is absolutely dependent on glasses as a serious aid, it leaves a very bad taste they are literally hiding the recording device in a disability aid.

can you tell more about how you're using it? like, what harness? or also in the IDE?

I found Qwen3.6 35B/A3B to make slightly too many mistakes (already in its harness' tool use, hence my question), maybe it gets the job done, but it will also sometimes generate a bit of a mess (e.g. editing/creating files in the wrong folders) and fixing/solving its own mistakes takes time (or tokens) ..

someone has to protect Disney from these unjust opinions!

Are you saying that thinking and cognition requires language use? Cause I think not.

Or are you saying that language use is sufficient for cognition and thinking? Cause I'm also not convinced of that.

What I am convinced of, is that a machine capable of language use is capable of tricking people into believing there's a "there", there. In pretty much the same way as the famous supra-normal stimuli experiment made baby seagulls believe that a stick with a red dot was their parent. It's exploiting our instincts.

Or maybe my setup (128GB amd strix halo box) isn't configured right and it could be faster, I dunno. I've already spent a few days on that, but it might take a few more. It's way more complicated than I expected.

This week, I've had it look through and generate more complete documentation for Strudel (music live coding tool), cause a lot of functions/behavior in it are not in their official docs. It took about 2-3 days. I had expected it to be an overnight task.

I did find the "opencode" harness to be a bit more performant than the "pi" harness. But maybe I've not configured "pi" right, I tried very hard, but when I installed "opencode" it just performed much better right out of the box. Especially running subagents just seemed to confuse the model in "pi".

Either way, it made me realize that a large part of the "intelligence" and occasional "usefulness" of these tools are in the harness, not the weights.

I didn't know there were free models on OpenRouter. I'm not really into renting tools that I'll become dependent on, so I never looked. But, I dunno. You're still hooking it in to your terminal, and they could in theory literally inject any command and take over your machine when you're not looking ... it still seems a bit like a crazy thing to do :)

And it's not like I need LLMs to code or anything. To be completely honest I'm still waiting for when they get good, which everybody says is supposedly any day now.

I've also tried Qwen3.6-35B/A3B a couple of times. I'd say it's about 4x faster, which is quite significant. Unfortunately it's also quite obviously more stupid and often fumbles its tool use. For me this adds up to taking about the same amount of time, multiplied by more frustration.

I find it hard to give concrete tokens/sec numbers, because they seem to change a lot. When I give Qwen3.8-27B a test query in the browser chat interface (e.g. "explain fibonacci hash"), I currently can get it up to about 18 tok/s. The Qwen3.6-35B/A3B can get up to about 66 tok/s. But this is just what I use as an indication for when my settings are right, cause when I set it up in the coding harness, the numbers are wildly different (and generally slower).

I honestly don't trust these things to not accidentally mess something up, otherwise.

Now I think it's still technically possible to break out of that with some clever hacks? But the moment I see a model even vaguely considering that, I will never run it again.

(I don't use Claude but currently Qwen3.8 27B)

If you then put Wikipedia, LLM and Brain on a scale to how well they can be understood, you will see that one of them is not like the others.