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Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." (arstechnica.com)
submitted 1 month ago by [M] to c/news@lemmy.linuxuserspace.show
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[–] 4 points 1 month ago (2 children)

This comparison is invalid. Training a neural network algorithm is not equivalent to human learning. We are talking about data stored in machine learning models owned and controlled by multi-billion dollar corporations.

It has already been demonstrated multiple times that original training data can be reproduced completely from models, so yes, they are data storage systems. When they reproduce code which they have previously stored, even only in part, that is a derivative work. Adding extra steps to the transcribing process doesn't make it any less a copy of the original.

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  • [–] 2 points 1 month ago* (last edited 1 month ago)

    Only when the data in question is so obscure to the point that the original source is the only place in which the data exists; which is neither common, nor useful to regurgitate, in practice.

    It's like if someone asked an artist to draw Trump, and then they did. It's not that they studied what he looks like, but they're familiar with that walking pusbag and there's only the one, so it's going to be a recognizable drawing.

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  • [–] 0 points 1 month ago (1 child)

    Training a neural network algorithm is not equivalent to human learning

    That's a stretch, since we don't know exactly how human learning works. Yes we have more than just that one mechanism at work obviously, but that's not to say we're not using the same or similar method as part of our learning process.

    original training data can be reproduced completely from models

    So can a few savants, more if you take into account those with special training, etc. The ability to do so is obviously latent to our brain.

    When they reproduce code which they have previously stored, even only in part, that is a derivative work.

    I don't know about you, but I for one have not produced anything 'original' my entire coding career by that metric. I feel confident in saying the vast majority of programmers have not either.

    Don't mistake me, I'm well aware LLMs are not intelligent. But I disagree with the idea that their method of learning and their actions is inherently different from what the average person does.

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  • [–] 3 points 1 month ago* (last edited 1 month ago) (1 child)

    That's a stretch, since we don't know exactly how human learning works.

    It is not a stretch. We may not know exactly how human learning works, but we do know exactly how machine learning works, and we know that it is not like how human learning works. It is absolutely possible to differentiate things even without complete knowledge.

    For instance, I am not a biologist. I do not have complete knowledge of the workings of a horse or a snake. However, I do know that a horse and a snake are different.

    I don't know about you, but I for one have not produced anything 'original' my entire coding career by that metric. I feel confident in saying the vast majority of programmers have not either.

    This is a bad argument. The output of a generative model is a copy-and-paste function from a library of ingested code samples with a fairly competent keyword search attached to it. Code writing bots are just script kiddie crutches.

    If all you did was copy and paste from GNU GPL code, then your output would also be bound by the same license.

    But I disagree with the idea that their method of learning and their actions is inherently different from what the average person does.

    Then you don't understand even the basics of the mathematics that makes them actually work. It's a purely algorithmic process. It's an outgrowth of multidimensional analysis and optimization, that's all.

    Here is a better explanation than I could give, by someone who knows better than me:

    Large Language Models explained briefly by 3Blue1Brown

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  • [–] 0 points 1 month ago

    Yes we have more than just that one mechanism at work obviously, but that's not to say we're not using the same or similar method as part of our learning process.

    You seem to have entirely ignored the gist of my first point. We may be using a more well rounded method which utilises the same technique LLMs use as a part of our overall learning ability.

    If all you did was copy and paste from GNU GPL code, then your output would also be bound by the same license.

    We're back to the same argument that's been around since the start of the current AI boom, about whether or not people produce art and everything else the same way. At this point it's very obviously a philosophical argument in general, and from your other comments in this post you've offered nothing but semantics as to how they're different. We're going to have to agree to disagree there.

    Then you don't understand even the basics of the mathematics that makes them actually work.

    I understand how LLMs work. We DON'T understand how humans work, and unless you've got a human theory of mind in your back pocket, insisting that they're inherently different instead of possibly being part of our mental toolkit is premature.

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