Fedora is not enterprise grade. That would be RHEL. And entreprise grade mostly just mean stable (some would say stale) packages anyway if you don’t pay for support.

Installing nvidia drivers on fedora workstation is as easy as enabling rpm-fusion non-free and then installing a few packages. The issue here comes from OP running an OSI-based immutable system, which makes layering stuff on top a bit more difficult.

OP’s already running something fedora based, might as well stay where they feel comfortable and just add a few drivers and gaming tweaks on top.

Nothing against opensuse though. I’m currently running aeon because their approach of immutability is more modulable than fedora’s one.

If you find yourself wanting to game on your distro again, layering nvidia drivers ontop of immutable fedora is do-able. If you want a more hands off approach you can use bazzite (https://bazzite.gg/), which has an nvidia compatible version and is just a kinoite-based OSI image with gaming oriented tweaks and extra apps.

You can even just rebase to it if you’re already using kinoite (and rebase back to kinoite if you don’t like it), no need to reinstall your system. The download page has a one-command exemple on how to do that.

I’ll confess that I only tried gpt 3.5 (and the mistral one but it was actually consistantly worse) given that there’s no way in the world I’m actually giving openAI any money.

Having said that I don’t think it fundamently changes the way it works. Basically I think it’s fine as some sort of interactive man/stackoverflow parser. It can reduce frictions of having to read the man yourself, but I do think it could do things a lot better for new user onboarding, as you seem to suggest in the comments that it’s one of the useful aspect.

Basically it should drop the whole “intelligent expert” thing and just tell you straight away where it got the info from (and actually link the bloody man pages. At the end of the day the goal is still for you te be able to maintain your own effing system). I should also learn to tell you when it actually doesn’t know instead of inventing some plausible answer out of nowhere (but I guess that’s a consequence of how those models work, being optimized for plausibility rather than correctness).

As for the quality of the answer, usually it’s kind of good to save you from googling how to do simple one liners. For script it actually shat the bed every single time I tried it. In some instances it gave me 3 ways to do slightly different things all in the same loop. In other straight up conflicting code blocks. Maybe that part is better in GPT 4 I don’t know.

It also gives you outdated answers without specifying the version of the packages it targets. Which can be really problematic.

Basically where I’m going with this is that if you’re coding, or maintaining any server at all, you really should learn how to track the state of your infra (including package versions) and read man pages anyway. If you’re just a user, nowadays you don’t really have to get your hands in the terminal.

At the end of the day, it can be useful as some sort of interactive meta search engine that you have to double check.

I’m really not getting into the whole “automated garbage that’s filling up the internet, including bug reports and pull request” debate. I do think that all things considered, those models are a net negative for the web.

It’s the long term support version of OpenSUSE that is binary compatible with the entreprise version provided by SUSE (SLES). Kind of the same relation between RHEL and CentOS (before the stream controversy).

In laymans terms it’s a stable desktop and server linux disribution. But it’s in a weird spot right now as OpenSUSE has stated that this will be the last major version following this release format. The next main OpenSUSE distro will be something based on modular imutable images.

Edit: Apparently there will also be a non-immutable version of Leap 16

This is one of the worst case of tech dude tries to solve social sciences with math I’ve ever read. The paper is not just bad as a whole, it deliberately disregard 200 years of research in at least 3 different academic fields and instead quotes Borat.
And then goes on to gleefully describe how the authors made a giant machine to reproduce their own (dangerous) biases about the universality of emotion-voicing with just chat-GPT and a zero-shot classifier, would you look at that? Yay science I guess?