• 8 Posts
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Joined 4 years ago
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Cake day: May 31st, 2020

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  • Bad code can certainly be part of it. The average skill level of those coding C/C++/Rust tends to be higher. And modern programs typically use hundreds of libraries, so even if your own code is immaculate, not all of your dependencies will be.

    But there’s other reasons, too:

    • Python, Java etc. execute their compiler/interpreter while the program is running.
    • CLIs are magnitudes slower, because these languages require a runtime to be launched before executing the CLI logic.
    • GUIs and simulations stutter around, because these languages use garbage collection for memory management.
    • And then just death by a thousand paper cuts. For example, when iterating over text, you can’t tell it to just give you a view/pointer into the existing memory of the text. Instead, it copies each snippet of text you want to process into new memory.
      And when working with multiple threads in Java, it is considered best practice to always clone memory of basically anything you touch. Like, that’s good code and its performance will be mediocre. Also, you better don’t think about using multiple threads in Python+JS. For those two, even parallelism was an afterthought.

    Well, and then all of the above feeds back into all the libraries not being performant. There’s no chance to use the languages for performance-critical stuff, so no one bothers optimizing the libraries.


  • Honestly, it’s still ridiculous to me how slow Python, Java, JS, Ruby etc. continue to feel, even after decades of hardware optimizations. You’d think their slowness would stop being relevant at some point, because processors and whatnot have become magnitudes faster, but you can still feel it quite well, when something was implemented in one of those.













  • I agree that (1) is particularly painful on openSUSE, because of (2), and I do agree that Fedora tends to be more similar to Debian/Ubuntu, but package names differing between distros is pretty universal for any non-derivative distros.

    For example, I tried to use nix-shell, which basically lets you set up a small, reproducible build environment using packages from NixOS. And it was working excellently, except I could not figure out for the life of me, what the names of the NixOS packages are that provide certain C libraries…


  • Tumbleweed does also feed into Leap. Leap uses SLE packages for most of the core libraries, but then user-facing applications see new versions integrated from what’s been packaged in Tumbleweed. Particularly, they also automate lots of the package testing in Tumbleweed, so that can be reused for Leap. Well, and also for SLE, which will also grab stuff from Tumbleweed when they do plan to upgrade their packages.

    As for minimal VM images, they do offer downloads for those.
    On this page, you can click on “Download”, then “Alternative Downloads”.
    These don’t seem to be available for Leap currently. Not sure, if it’s because Leap 15.6 has only been out for a few weeks. Could also be that I’m missing something here.

    As for Wicked, they only use it for server systems as the default, and they do make it easy to switch to NetworkManager, if you prefer.


  • I was amazed that we transitioned from one GPU heavy bubble (Crypto) to another (LLM/AI).

    From what I understand, that’s not a coincidence. We’ve had the technology for LLMs for a long time. We just didn’t make them Large, because the training would have taken an eternity.
    Then cryptocurrencies caused the GPU market to boom and then implode, which meant lots of cryptominers were selling their GPUs for dirt cheap. Perfect time to buy a bunch of GPUs, stick them in a server and try to do that eternity-long training.

    And yeah, as for local chatbots, I do also imagine they will continue to be a thing, even if they won’t get any better anymore when the big companies stop doing the training.
    But as you kind of also reasoned, I still don’t expect most of these companies to host their own chatbot…


  • Man, I’m so curious when and to what extent this whole hype bubble will implode.
    Like, we’re not talking blockchain, there is some legitimate use-cases for generative AI, which will continue to exist.

    However, there’s also many legitimate use-cases which will not continue to exist, because Microsoft et al are subsidizing GenAI to an insane degree.
    When the hype falls off, investors pull out their money and Microsoft cannot continue subsidizing, which will make prices shoot up for their customers and serve as a rough awakening to all the websites that integrated a crappy chatbot.

    And of course, there’s also the complete fucking bullshit use-cases, which will be gutted immediately when investors/management stop being hyped.