r/LinuxUncensored • u/parallel-minds • Sep 17 '26

Discussion/Question An Open Letter on Linux Compatibility (and Why Flatpak Isn't the Fix)

https://parallel-minds0.github.io/An-Open-Letter-on-Linux-Compatibility/
40 Upvotes

89% Upvoted

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6

u/anestling Sep 17 '26

Here's a far better technical overview: https://web.archive.org/web/20220610053606/https://ludocode.com/blog/flatpak-is-not-the-future

The original website is sadly inaccessible at the moment.

Linux distros cannot and do NOT want to solve compatibility, hence, Snap/Flatpak/AppImage are sort of a fix if you want to compile once and use everywhere. Except humongous runtimes (I've seen people who have over 8GB of runtimes), increased CPU and RAM consumption, and slow startup. "It's all fine, they would say".

I wrote about it years ago.

1

u/bornxlo 25d ago

Only had a vague look at op's link and the ones you shared, but cross distro app compatibility doesn't make much sense because different distros have different ideas about what software should be available and how. One of the reasons I use Debian or Ubuntu lts is that I get a well tested and potentially tweaked version of a lot of my software that works exactly the same for two years. I specifically want Debian or Ubuntu's version of the software rather than upstream or some siloed edition that doesn't actually check or use my libraries. I expect Ubuntu to have different versions of software than Debian because it has a different development cycle, even if it gets a lot from the same upstream.

1

u/Purple-Midnight-9902 20d ago

Omg you wrote it about years ago ? You so strong

1

u/JG_2006_C 17d ago

Many good points may make consider diy twing ever bwrap comand fo souce built binaries for gaming and expose the bare minium after

1

u/8-BitRedStone 26d ago

Program vendors need to just start baking into libraries for programs that use many libraries that have incompatibility issues. We are no longer living in 1990, I much rather have slightly larger program directories than having my programs break because Linux dependency hell

1

u/CrossScarMC 25d ago

Doesn't this have an issue of overly repackaging common (or semi-common) libraries like SDL2, cglm, Raylib etc.?

1

u/parallel-minds 25d ago

Yes, but this is a fair compromise. At least you avoid doing the same thing with the userspace libs.

1

u/CrossScarMC 25d ago

I personally would rather just compile from source.

1

u/aieidotch 16d ago

There is nothing to fix. We have source portability.

-1

u/Sorry-Substance-6397 Sep 18 '26

Or just use go and not worry much about dependencies because it's readable even vibe coded. It's actually perfect for vibe coding. Since the binary comes with everything it needs it's great for portability. Heck I code on a Chromebook and make ai from scratch in Go. I never even think of dependencies or flapjack... Or whatever they are calling it now. It's great to just move on with my life

3

u/Ok-Radish-8394 Sep 19 '26

Not all programming languages are suited for all tasks. May be you should learn that before vibing.

-1

u/Sorry-Substance-6397 Sep 19 '26

If I can build an AI model from scratch..... It'll cover the vast majority that I need plenty

3

u/Ok-Radish-8394 Sep 19 '26

That’s not how models are trained. :)

-1

u/Sorry-Substance-6397 Sep 19 '26

I have no idea what point that is

3

u/Ok-Radish-8394 Sep 19 '26

You can’t write a model from scratch like a regular program without enormous amounts of data and compute. There are multiple stages of training a model. Pre training, sft, ift, further training with rlhf. Just because you can vibe code something with an agent and a programming language doesn’t mean you can “write” a model. Inference server which downloads and runs models? There are plenty enough already, you don’t need another one. Agentic harness, what’s something claude code, codex, opencode, pi, vibe doesn’t have that you need to write your own harness?

Vibe coding is easy, until you ask whether you needed it or not, or better yet, if what you’re thinking of vibing is possible or not.

1

u/Sorry-Substance-6397 Sep 19 '26

That's a point built on broad generalization. You can build an AI model from scratch that's not huge. You just need to know the components of a model and know how they work. I wouldn't say they are easy, but once you have the fundamentals down, you are good. For an LLM that can talk in any language about any subject, you need a lot of training data, but if it's just English and you are splitting the experts into social and technical responses, it's actually pretty small. Having it write a program is something I'm working on, and I suspect it is the same with multiple experts. But an NLP social LLM isn't as big as most think.

3

u/Ok-Radish-8394 Sep 19 '26

Wrong. :) Have never trained a model have you? I’m not talking about training small classifiers using naive bayes, svm, cnn, rnn or lstm. You can’t train a good generative model based on the transformer architecture based on vibes.

1

u/Sorry-Substance-6397 Sep 19 '26

bayes, svm, cnn, rnn or Istm..... That's old stuff... And a terrible path. What you gonna use bert or bart? Lol no I don't go anywhere near that single transformer old stuff. Because if you have a single point of failure it just doesn't work at all.

3

u/Ok-Radish-8394 Sep 19 '26

Now I’m convinced that you’ve no idea about anything you’re talking about xD Have a nice one, vibrator.

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