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 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.