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Joined 2 years ago
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Cake day: April 4th, 2025

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  • Here a comment on this from usernomdeguerre on hacker news (ycombinator.com).

    “His” and “GKH” refers to Greg Kroah-Hartmann, who is maintainer of the stable kernel series and the speaker in the video.

    I’ve included a few slides into text that i thought were eye-opening to me:

    From his Kernel Recipes 2026 slide on Mythos

    
      Mythos's 79 vulnerabilities:
      24 - no detail at all "something crashed"
      14 - not a bug at all
      3 - totally made up data
      15 - already fixed in latest release
        - 11 by others
        - 4 by anthropic
      20 - fixes were needed
        - 7 "assume a malicious filesystem image"
        - 2 "assume you can inject a malicious network packet into the middle of the stack"
        - 2 "NOMMU"
        - 6 sctp networking issues for untrusted devices
        - 2 ipv6 minor network issues 
        - 1 gpu driver for local malicious user
    
    

    GHK called this “10 ‘real’ bugfixes”, which to me sounds like there’s a wild hype machine around these companies and uncritical parroting of every press release they make that falls apart when you engage the affected real experts.






  • Sometimes, I think the “AI” industry has an interest to keep the debate as polarized as possible. Because this keeps people from taking a sober look and examine rationally and objectively what they promise, vs. what they deliver.

    We have several public debates which followed a similar pattern, such as the debates around climate protection and clean energy. (And lo and behold! Now “AI” is the reason we can’t have climate protection!)

    Or the “AI arms race” argument, which honestly just reminds me in the enthusiasm, propaganda, and delusion that happened at the outbreak of WWI. Yes, modern weapons got “better”. But that made war just more lunatic. And now, you can kill a building full of school children with an “AI mistake”. Military people must be gleeful.


  • Keep in mind that this only relates to the state of the largest LLMs. You can train generative models on consumer graphics cards. Object recognition, classification, etc are all tiny compared to LLMs. These are also AI […]

    The linked Codeberg page refers to LLMs in their current, corporate-controlled shapIe. It is about using LLMs for coding.

    Your argument is rather leading away from that.











  • This is what I do. I use guix shell for local development environments, for example when I need current Rust + cargo or an LSP package in Emacs.

    Guix is typically very little behind of Arch (which I use as well, in a VM), and depending on what you do, it now has a pretty massive package selection (well, less npm stuff or NVidia hardware support).

    It is also quite good for packaging and distributing own software that way, offering for developers and power users a better solution to what flatpaks solve. Since it works across different distributions and across most popular languages, I expect it to become somewhat of a standard for bazaar-style open source contributions.