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Um, the entire intent of these "AI" systems is explicitly to reproduce copyrighted work with mechanical changes to make it not appear to be a verbatim copy. Th

by olliej 2y ago

Um, the entire intent of these "AI" systems is explicitly to reproduce copyrighted work with mechanical changes to make it not appear to be a verbatim copy. That is the whole purpose and mechanism by which they operate. Also the intent does not matter under law - not intending to break the law is not a defense if you break the law. Not intending to take someone's property doesn't mean it becomes your property. You might get less penalties and/or charges, due to intent (the obvious examples being murder vs manslaughter, etc). But here we have an entire ecosystem where the model is "scan copyrighted material" followed by "regurgitate that material with mechanical changes to fit the surrounding context and to appear to be 'new' content". Moreover given that this 'new' code is just a regurgitation of existing code with mutations to make it appear to fit the context and not directly identical to the existing code, then that 'new' code cannot be subject to copyright (you can't claim copyright to something you did not create, copyright does not protect output of mechanical or automatic transformations of other copyrighted content, and copyright does not protect the result of "natural processes", e.g 'I asked a statistical model to give me a statically plausible sequence of tokens and it did'). So in the best case scenario - the one where the copyright laundering as a service tool is not treated as just that, any code it produces is not protectable by copyright, and anyone can just copy "your work" without the license and (because you've said if you weren't intending to violate copyright it's ok) they can say they could not distinguish the non-copyright-protected work from the protected work and assumed that therefore none of it was subject to copyright. To be super sure though they weren't violating any of your copyrights, they then ran an "AI tool" to make the names better and better suit your style. I am so sick of these arguments where people spout nonsense about "AI" systems magically "understanding" or "knowing" anything - they are very expensive statistical models, the produce statistically plausible strings of text, by a combination of copying the text of others wholesale, and filling the remaining space with bullshit that for basic tasks is often correct enough, and for anything else is wrong - because again they're just producing plausible sequences of tokens and have no understanding of anything beyond that. To be very very very clear: if an AI system "understood" anything it was doing, it would not need to ingest essentially all the text that anyone has ever written, just to produce content that is at best only locally coherent, and that is frequently incorrect in more or less every domain to which it is applied. Take code completion (as in this case): Developers can write code without essentially reading all the code that has ever existed just so that they can write basic code, because developers understand code. Developers don't intermingle random unrelated and non-present variables or functions in their code as they write, because they understand what variables are and therefore they can't use non existent ones. "AI" on the other hand required more power than many countries to "learn" by reading as much as possible all code ever written, and then produce nonsense output for anything complex because they're still just generating a string of tokens that is plausible according to their statistical model - the result of these AIs is essentially binary: it has been in effect asked to produce code that does something that was in its training corpus and can be copied essentially verbatim, with a transformation path to make it fit, or it's not in the training corpus and you get random and generally incorrect code - hopefully wrong enough it fails to build, because they're also good at generating code that looks plausible but only fails at runtime because plausible sequence of tokens often overlaps with 'things a compiler will accept'.

shkkmo 2y ago
> Also the intent does not matter under law - not intending to break the law is not a defense if you break the law Intent frequently matters a great deal when applying laws. In the specific area of copyright law, it doesn't itself make the use non infringing, but it can absolutely impact the damages or a fair use argument.
- freejazz 2y ago
  Great point, I wonder how the court will look at OpenAI's internal discussions around utilizing copyrighted materials.
Kim_Bruning 2y ago
I actually once tracked this claim down in the case of stable diffusion. I concluded that it was just completely impossible for a properly trained stable diffusion model to reproduce the works it was trained on. The SD model easily fits on a typical USB stick, and comfortably in the memory of a modern consumer GPU. The training corpus for SD is a pretty large chunk of image data on the internet. That absolutely does not fit in GPU memory - by several orders of magnitude. No form of compression known to man would be able to get it that small. People smarter than me say it's mathematically not even possible. Now for closed models, you might be able to argue something else is going on and they're sneakily not training neural nets or something. But the open models we can inspect? Definitely not. Modern ML/AI models are doing Something Else. We can argue what that Something Else is, but it's not (normally) holding copies of all the things used to train them.
- pclmulqdq 2y ago
  I think this argument starts to break down for the (gigantic) GPTs where the model size is a lot closer to the size of the training corpus. Thinking in terms of compression, the compression in generative AI models is lossy. The mathematical bounds on compression only apply to lossless compression. Keeping in mind that a small fraction of the training corpus is presented to the training algorithm multiple times, it's not absurd to suggest that these works exist inside the algorithm in a recallable form. Hence the NYT's lawyers being able to write prompts that recall large chunks of NYT articles verbatim.

by olliej 2y ago

shkkmo 2y ago

> Also the intent does not matter under law - not intending to break the law is not a defense if you break the law Intent frequently matters a great deal when applying laws. In the specific area of copyright law, it doesn't itself make the use non infringing, but it can absolutely impact the damages or a fair use argument.

freejazz 2y ago
Great point, I wonder how the court will look at OpenAI's internal discussions around utilizing copyrighted materials.

Kim_Bruning 2y ago

I actually once tracked this claim down in the case of stable diffusion. I concluded that it was just completely impossible for a properly trained stable diffusion model to reproduce the works it was trained on. The SD model easily fits on a typical USB stick, and comfortably in the memory of a modern consumer GPU. The training corpus for SD is a pretty large chunk of image data on the internet. That absolutely does not fit in GPU memory - by several orders of magnitude. No form of compression known to man would be able to get it that small. People smarter than me say it's mathematically not even possible. Now for closed models, you might be able to argue something else is going on and they're sneakily not training neural nets or something. But the open models we can inspect? Definitely not. Modern ML/AI models are doing Something Else. We can argue what that Something Else is, but it's not (normally) holding copies of all the things used to train them.

pclmulqdq 2y ago
I think this argument starts to break down for the (gigantic) GPTs where the model size is a lot closer to the size of the training corpus. Thinking in terms of compression, the compression in generative AI models is lossy. The mathematical bounds on compression only apply to lossless compression. Keeping in mind that a small fraction of the training corpus is presented to the training algorithm multiple times, it's not absurd to suggest that these works exist inside the algorithm in a recallable form. Hence the NYT's lawyers being able to write prompts that recall large chunks of NYT articles verbatim.