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Joined 9 months ago
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Cake day: October 14th, 2025

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  • I think you’re missing the trees for the forest. Yes, all those downsides make the current crop of LLM implementations pretty shitty for humanity, on balance, but none of them are intrinsic to LLMs, they are intrinsic to the current business practices that are attempting to profit from LLMs. LLMs are just math. Often computationally expensive math, sure, though they needn’t be. But I don’t think it helps anyone to say “LLMs are intrinsically bad and no one should use them” any more than it makes sense to say that blockchains are intrinsically bad and no one should use them (a common sentiment about a decade ago). I think a more realistic approach is to find out what real benefit can be had by using LLMs, and see if that benefit can be realized without all the downsides you mentioned.

    To take the case at hand, I think open source code review is probably a pretty good candidate domain for exploration, because there’s a large corpus of available text that could be obtained ethically, if LLM trainers bothered to put in the work. It seems like Torvalds isn’t concerned with that, and it looks like sashiko only supports LLMs that are known to have been trained on stolen data, which is shitty and I think Torvalds and the Linux maintainers should be taken to task for that. I think LLM makers should get permission from project maintainers before training on their codebases, just as natural-language rightsholders should be asked for permission before using their works for training. I think LLMs trained on ethically sourced data should be permissively licensed and, if they collect revenue, should be expected to kick some of that revenue upstream to the projects they benefit from. I also think such projects could be powered ethically: I have some plans for my own small solar powered server that will run batch jobs when production is higher than my storage capacity. Right now I’m mostly targeting Folding at Home, but I might well run my own LLM trainer if I get enough capacity, and I could see a similar distributed processing network for high-cost jobs from trusted open source LLM projects.

    I don’t think you’re wrong about the scope of the downsides, but I also don’t think it makes sense to take them all as a singular block and judge all possible LLM tools by all possible downsides. I think they are problems that can be engineered around with technical and social guidelines for use. And I think it will be down to the open source community to set those guidelines, because I don’t know of any other group that has the expertise and the motivation to do so.


  • I think asbestos is a good analogy, but I think your claims that the inherent downsides of LLMs outweigh any possible upsides are as-yet unfounded. I also think it’s kind of strange that you assume anyone who thinks otherwise is being disingenuous.

    Maybe they are too dangerous for broad use, and we need to regulate them like asbestos, or uranium. Maybe they shouldn’t be used outside of a laboratory setting or by anyone who doesn’t have extensive training with how to interact with them safely. It seems pretty clear that Torvalds has decided they’re worth the downside, and while I don’t know if that’s a good call, I don’t think he’s operating in bad faith to the detriment of the kernel project. That doesn’t sound like something he would do.

    I feel confident that I don’t have the expertise to say for certain one way or the other, though the experience I do have with software tools makes me think there’s probably an application for them where the downsides can be mitigated to the point where they become worthwhile. I think there’s probably some single-purpose or tailored application of LLMs related to textual analysis that don’t require the theft of the whole internet, and don’t require insane amounts of energy to run. I don’t think we have discovered them yet (at least I haven’t), but saying “this kind of software is only bad and can have no ethical uses, ever” seems premature.


  • I think if we, as a community, really put our heads together, we could figure out how to define and make useful user-respecting tools that incorporate LLMs. There are a lot of hard problems, like the massive power consumption, and the ethical use of data, that I don’t really know how to solve.

    I think a start would be to focus on making smaller, lower-complexity models that are built for purpose, rather than trying to make a jillion-parameter jack-of-all-trades trades model. I think it would also make sense to focus initially on areas where there are already large corpuses of freely available text, like all the writings in the public domain. But I don’t really have a good idea of what these tools would be used for, exactly, which is where I’m stuck.


  • The solution is to make sure those LLM tools help maintainers instead of just causing them pain. There’s no question on that side.
    We’re not forcing anybody to use it, but I will very loudly ignore people who try to argue against other people from using it.
    And no, AI isn’t perfect. But Christ, anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time.
    Because it’s not like natural intelligence is always all that great either.
    The kernel project has been and will continue to be about the technology.
    Sure, the social angle of working on open source is important and often a very motivating part of the project, but in the end that’s a side benefit, not the point of the project.
    This is NOT some kind of “social warrior” project, never has been, and never will be.
    In the kernel community we do open source because it results in better technology, not because of religious reasons.
    And so we make decisions primarily based on technical merit. Not fear of new tools.

    IMO it’s a pretty clear eyed take. LLMs are tools and, like all tools, are more fit for some purposes than others. And, like many tools, they’re hard to understand, easy to misuse, and dangerous when they are misused (intentionally or otherwise). And, like any tool, they can be used for evil if the user has a mind to do so. Just because they are currently being used to do great harm doesn’t mean they can’t also be put to good use.

    I think the FOSS community, in particular the Fediverse community, does itself a disservice by refusing to engage with them at all. They aren’t evil in and of themselves, they’re just new and selfish people will try to find an angle with them, same as it’s always been. I think it’s up to us to understand them and try to find a way to use them ethically. Show the world that it’s not that we invented scary Artificial Intelligence, it’s just that we created a cool, if wonky, search interface for text. Wonky in what way? Well, I think it’d be nice if there were robust FOSS tools and documentation I could use and/or contribute to, and learn about them with a community of my peers working for the common good, instead of having to either take the megacorps at their word or just renounce anything “AI branded” altogether, which doesn’t feel like a good long term strategy.