Main issue is drivers. One of the best places to take advantage of rust’s memory safety is in hardware drivers, and those would be hard to share between separate kernels.

That entire talk, and the complaint that Ts’o responded to was that to continue with rust, there needs to be some responsibility from the guys working on the underlying C bindings to not break downstream dependencies if they refactor code.

The answer from some of the Kernel developers, and vocally by Ts’o was: lol no fuck you and your toy language.

You can use nix alongside guix, it’ll just double-up the dependencies on disk:

services (append (list (service nix-service-type))
                    %base-services)))

Services are, in guix terms, any configuration change to a computer, so creating your own service 99% of the time is just extending etc-service-type and creating a variable interface to fill in the config file text yourself

Creating a service as in a daemon of some kind uses shepherd and involves extending shepherd-service-type or home-shepherd-service-type with your service description, depending on whether the service runs in root or user space.

Shepherd service configurations aren’t actually part of the guix spec(https://www.gnu.org/software/shepherd/manual/shepherd.html#Defining-Services), but still use Guile, so you can interoperate them super easily.

It’s important in guix to understand lisp pretty thoroughly, and knowing how to program lisp is still a very useful skill to have so I’d recommend learning it even if you never touch guix.

I use guix because, while it has a small community, the packaging language is one of the easiest I’ve ever used.

Every distro I’ve tried I’ve always run into having to wait on packages or support from someone else. The package transformation scheme like what nixos has is great but Nixlang sucks ass. Being able to do all that in lisp is much preferred.

Plus I like shepherd much more than any of the other process 0’s

One of the few practical things AI might be good at:

https://github.com/CorentinJ/Real-Time-Voice-Cloning

I hope shepherd gets a mention in this series eventually

Facebook is trying to burn the forest around OpenAI and other closed models by removing the market for “models” by themselves, by releasing their own freely to the community. A lot of money is already pivoting away towards companies trying to find products that use the AI instead of the AI itself. Unless OpenAI pivots to something more substantial than just providing multimodal prompt completion they’re gonna find themselves without a lot of runway left.

NewPipe can do peertube as well

https://github.com/hykilpikonna/hyfetch

I like hyfetch because it has the largest os compatibility.

It feels like the spiritual successor to neofetch tbh.

I’d say mostly energy savings and CPU usage efficiency

KDE separated out into Plasma and the utilities and apps separately at KDE 5. Previously it was all one package, so there is a bit of a confusing distinction.

Figured a link would help: https://gitlab.com/nonguix/nonguix

Ignore the weird wording about not promoting it on the page, it’s just a warning to keep people from complaining about the nonguix packages to the guix devs, but there’s lots of crossover

KDE is not, Plasma is:

https://guix.gnu.org/en/manual/devel/en/guix.html#Desktop-Services

I use guix cause having an entire OS centered around Scheme is cool and based.

Wearing out the parentheses keys on my keyboard

Ah, no not the template files for the individual containers, but the project descriptors are just compose files.

They’re 1-1 compose files.

The app just saves them as compose files and then runs docker compose in the backend.

it is EXTREMELY barebones

There’s also Yacht.

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I would recommend instead to use the AI Horde: https://stablehorde.net/ It’s a collection of people hosting stable diffusion/text generation models

There’s also openrouter which can connect to ChatGPT with a token-based system. (They check your prompts for hornyposting though)

It helps differentiate between GNU/Linux users and the five people who use GNU/Hurd

Yes of course, there’s nothing gestalt about model training, fixed inputs result in fixed outputs