Actually setting up rootless Docker is pretty manual and kludgy. With Podman, rootless is pretty much effortless.
Wow. It seems really clunky indeed: https://docs.docker.com/engine/security/rootless/
Readit Newshaolez commented on Using Podman, Compose and BuildKit emersion.fr/blog/2025/usi... · Posted by u/LaSombra
haolez commented on Using Podman, Compose and BuildKit emersion.fr/blog/2025/usi... · Posted by u/LaSombra
But Docker can run rootless these days, right? Can anyone chime in with how well does this work?
haolez commented on Closer to the Metal: Leaving Playwright for CDP browser-use.com/posts/pla... · Posted by u/gregpr07
Ah, yes, the classic "Playwright isn't fast enough so we're reinventing Puppeteer" trope. I'd be lying if I haven't seen this done a few times already.
Now that I got my snarky remark out of the way:
Puppeteer uses CDP under the hood. Just use Puppeteer.
I've seen a team implement Go workers that would download the HTML from a target, then download some of the referenced JavaScript files, then run these JavaScript files in an embedded JavaScript engine so that they could consume less resources to get the specific things that they needed without using a full browser. It's like a browser homunculus! Of course, each new site would require custom code. This was for quant stuff. Quite cool!
haolez commented on Mangle – a language for deductive database programming github.com/google/mangle... · Posted by u/simonpure
I haven’t worked closely with Datalog, but whenever I come across tools that use it, they always seem to extend vanilla Datalog (like this one).
Are there any notable implementations of plain Datalog? If not, what’s the reason? Does vanilla Datalog have major limitations? Just curious.
haolez commented on Show HN: Draw a fish and watch it swim with the others drawafish.com... · Posted by u/hallak
No obscene fishes observed. Well done! :)
haolez commented on Show HN: I built an AI that turns any book into a text adventure game kathaaverse.com/... · Posted by u/rcrKnight
How do tools like this avoid what I see in many of these types of narrative chat bots: the user becomes the only one steering the narrative, and the AI ends up just an obedient responder? Whenever I try these things it ends up very predictable, shallow, and repetitive, especially as time goes on. And if I have to prompt the AI to be creative or act differently... is that really acting different?
Anecdote on my side, but Grok 4 was the first model that didn't feel like that to me. Maybe my conversations were just not long enough for it to fallback to sycophantic behavior.
I believe an important reason for why there are no LLM breakthroughs is that humans make progress in their thinking through experimentation, i.e. collecting targeted data, which requires exerting agency on the real world. This isn't just observation, it's the creation of data not already in the training set.
Maybe also the fact that they can't learn small pieces of new information without "formatting" its whole brain again, from scratch. And fine tuning is like having a stroke, where you get specialization by losing cognitive capabilities.
haolez commented on The AI lifestyle subsidy is going to end digitalseams.com/blog/the... · Posted by u/bobbiechen
I am bewildered to hear the sense of "local," in which I and engineers in my experience have for thirty years referred to things which are not remotely hosted, referred to as an "overload."
My definition of local is the same as yours. It's just that my mind got focused on the open models part and I forgot that you specifically mentioned a "local" setup. My bad
haolez commented on The AI lifestyle subsidy is going to end digitalseams.com/blog/the... · Posted by u/bobbiechen
This has been coming for a long time and it is why I use local models only. I'm willing to give up capabilities in exchange for being able to trust that whatever biases may exist in the models I do use remain static and predictable.
How do you do it? Do you host on your hardware or do you use cloud-based providers for open models?
I wonder if these extremely terse languages might see a rise in popularity with LLMs, since they save a lot of tokens. The hard part would be training on them, since training data is not as comprehensive as JavaScript, for example.
Fun times! :)