Starting to look like AGI will be written in markdown

i put my laptop next to the window and it was spot on wtf

what got me the most is opening chrome dev tools and seeing nothing there

Amazing now I need to fire up my other agent so that it can go in my other laptop, and use the dummy github I use for throwaway agent because this thing is asking to act on my behalf on my github and I don't understand wtf that even means... can it sell my account to another bot, can it add all my data to another drastic leak no one cares about...

And then I can finally use this thing.

The problem with AI ethics, safety and to a smaller extent, privacy groups is that the priority of the work/message is not placed on the practicality of solving the problem, or i.e. calculating improving affordability of food/housing, but is placed,as evident on this article too, on the lack of "governance structures".

In other words the priority of the work is to get these types of people into positions where they don't do any work.

At least with privacy groups you do get here and there some practical advice on using ublock origin or more rarely on how to install a blocklist from https://someonewhocares.org/hosts/, but with AI ethics & safety orgs... well lets put it this way.

I have yet to meet a single AI safety person that knows how to rename a file in linux.

God forbid we have a rogue AI-worm shutting down all servers & BGP routers while these types of people were in charge of safety, they'll be in the way of anyone even fixing it. They can't even get a simple safety benchmark working on lm_eval-harness. They're great at lecturing you why they shouldn't need that.

And this is the key issue with AI Ethics. It's the refusal to work at the problem constructively, and get the most skilled people possible to actually make the damn benchmarks to work, to rank models on the understanding of human rights, to list every current violation and abuse of humans in every single country without exception and to make practical plans on what to do when systems go rogue. Even if they're not technical they could be making the dataset in a csv in excel for that and making it public domain accessible.

Instead we get the most depressed, leechy-office-worker types complaining about how it's all over.

Now back to work, move it.

If you want to have an opinion on it,

just install lmstudio and run the q8_0 version of it i.e. here https://huggingface.co/bartowski/Qwen_Qwen3-4B-Instruct-2507....

you can even run it on a 4gb raspberry pi Qwen_Qwen3-4B-Instruct-2507-Q4_K_L.gguf https://lmstudio.ai/

Keep in mind if you run it at the full 262144 tokens of context youll need ~65gb of ram.

Anyway if you're on mac you can search for "qwen3 4b 2507 mlx 4bit" and run the mlx version which is often faster on m chips. Crazy impressive what you get from a 2gb file in my opinion.

It's pretty good for summaries etc, can even make simple index.html sites if you're teaching students but it can't really vibecode in my opinion. However for local automation tasks like summarizing your emails, or home automation or whatever it is excellent.

It's crazy that we're at this point now.

From the article:

"Why are there no laws requiring device manufacturers to open source all software and hardware for consumer devices no longer sold?"

I think it's because people (us here included) love to yap and argue about problems instead of just implementing them and iterating on solutions in an organized manned. A good way these days to go about it would be to forego the facade of civility and use your public name to publicly tell your politician to just fuck it, do it it bad, and have plan to UNfuck after you fuck it up, until the fucking problem is fucking solved.

Same goes for UBI and other semi-infuriating issues that seem to (and probably do) have obvious solutions that we just don't try.

"Full 131k" context , actually the full context is double that at 262144 context and with 8x yarn mutiplier it can go up to 2million. It looks like even full chip scale Cerebras has trouble with context length, well, this is a limitation of the transformer architechture itself where memory requirements scale ~linearly and compute requirements roughly quadratically with the increase in kv cache.

Anyway, YOU'RE NOT SERVING FULL CONTEXT CEREBRAS, YOU'RE SERVING HALF. Also what quantization exactly is this, can the customers know?

I've been using it all day, it rips. Had to bump up toolcalling limit in cline to 100 and it just went through the app no issues, got the mobile app built, fixed throug hthe linter errors... wasn't even hosting it with the toolcall template on with the vllm nightly, just stock vllm it understood the toolcall instructions just fine