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Joined 2 years ago
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Cake day: July 27th, 2024

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  • I have been meaning to answer for days now. I don’t have time for a longer answer right now so I’ll keep it short.

    Linux AV is basically useless if you sandbox stuff and only use trusted sources like your package manager. Keep away from user generated repositories, read the news of your distribution. You can scan your system from time to time with ClamAV if you’re paranoid, but no need to enable the background agent/daemon. Funnily enough I sometimes found viruses on my systems with this, but it’s always Windows viruses 😹

    The recent attacks on Linux always focused on AUR, COPR and similar user repositories first.

    Do updates frequently and timely. Maybe read security bulletins like from heise.de or theregister.com, but focus on tailoring their feeds to the stuff you actually use. Maybe enable auto updates if you’re on a stable distribution like Debian or an immutable one like Bazzite.

    Oh and don’t use Linux Mint as they hold back security updates or Manjaro as their quality control keeps lacking.









  • Yes, something like that. If you use a model which is specifically trained on C(++), Assembly and Rust, as well as scientific articles about Linux and the Linux Kernel, has the whole Linux Kernel already baked in, you can probably get faster and more accurate results than if you add the whole Wikipedia in 20 languages.

    My LLM doesn’t need to answer all the questions, it’s enough if it answers the ones I want to ask. AI and the (mathematical) algorithms used for it are very old in terms of computer timeframes (think the 70s to 90s). The new part with LLMs is actually in the first “L”: large datasets. I think we have gone too large.

    And, with Linux, you have an issue with authorship if you train on copyrighted data. Reproducing code 1:1 from a non-Free textbook might be problematic, so special LLMs trained on Open/Libre texts will be safer in terms of compliance as well.