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The question then becomes do these concerns remain even for AI that cannot reproduce origional works? Does what does that mean for us? When we read things, or i

The question then becomes do these concerns remain even for AI that cannot reproduce origional works? Does what does that mean for us? When we read things, or interact with Amy information for that matter, it changes us and how we do things. If you consume art it will forever influence art you produce yourself. Are these copyright infringements also? I can see the problem where direct and faithful replication is possible but where it isn't is there still a problem? Or is the automatable aspect, the scale at which it can occur, that is the problem?

bayindirh 3y ago
The difference is what you mix, and the amounts of things you mix. As a human you mix many more inputs, plus your emotions, plus the things you consume to create it. Moreover, what you can consume and how perfectly you can consume is limited by our innate limits. An AI system consumes something perfectly, then ingrains it into its weights perfectly, and becomes capable of imitating the same thing perfectly. Plus, ther are no other internal or external factors which affect these "generation" over time. Hence, it mixes and reproduces based on what it consumed, solely. I might get inspired by people, and add my own values to it, iterate over it and diverge from what I'm inspired from ultimately to create my own style. AI doesn't work like that. Also, if I do the same amount of inspiration with the same precision and accuracy, I'll be neck deep in accusations and lawsuits (for the right reasons). As a result, just because we fail to ask the right questions to reproduce the training data verbatim or almost verbatim doesn't mean that the information is not there. At the end, a neural network is a compression algorithm which encodes data in terms of weights. Given the correct input, you can regenerate the training data as is. Unless you have special abilities, you can't read 500 books an hour, remember them perfectly, and generate derivative works by mashing all of them together. If I do and try to sell a novel, I'll be ridiculed no end. If I write a Ph.D. the same way and try to defend it, I'll be banned from academia for three lifetimes at least. For more elaboration on the subject, see [0]. [0]: https://news.ycombinator.com/item?id=39188463 https://news.ycombinator.com/item?id=39188463
- miki123211 3y ago
  The myth that AI models store all its training data in its weights verbatim is as widespread as it is false. In fact, if this were the case, deep neural networks would be considered far better compression algorithms than anything we have on the market right now, by literal orders of magnitude. If you divide Stable Diffusion's file size by the number of images used to train it, you get something like 1.2 bits per image, and it is physically impossible to get this kind of a compression ratio. The actual problem with AI is that it sometimes plagiarizes random fragments of the work it is trained on, even if it is not the user's intend, and we currently don't really know how to fully prevent this.
  - bayindirh 3y ago
    It still doesn't change the fact that the inclusion of commercial works is copyright infringement though. Same for code generating models trained on Open Source and Free Software. Tons of licenses violated, from strong copyleft to source available models and reproduced (almost) verbatim with comments intact. Some researcher's codebase is almost completely reproducible without any licensing information just by hinting the function names. Maybe for the image compression it's borderline impossible for now due to network size, but for text and code, generation of training data almost verbatim is very possible and straightforward. Also in image generation models, style transfer is the bigger problem, because it completely eliminates the artist who uses/created the style in the first place. "You pioneered this, and we fine tuned this model with your images, and we can do your work for free, without you, have a nice day". However, the artist's life expenses doesn't disappear when they're transferred to an image generation model. This is also unethical.
    - miki123211 3y ago
      Style transfer is perfectly legal AFAIK, asking artists to do a drawing of X in the style of Y was already a thing. Style is not copyrightable.
      - bayindirh 3y ago
__loam 3y ago
The "humans do it too" argument is totally irrelevant to this because humans have special and specific privileges under the law that computers don't. The problem is that a lot of data was copied into training sets and used for commercial purposes without permission.
ribosometronome 3y ago
Whether or not I'm influenced by media isn't super relevant to whether or not I pirated that media. Before even arriving at the question of whether or not the resulting models are infringing, it's clear the training data is.

bayindirh 3y ago

The difference is what you mix, and the amounts of things you mix. As a human you mix many more inputs, plus your emotions, plus the things you consume to create it. Moreover, what you can consume and how perfectly you can consume is limited by our innate limits. An AI system consumes something perfectly, then ingrains it into its weights perfectly, and becomes capable of imitating the same thing perfectly. Plus, ther are no other internal or external factors which affect these "generation" over time. Hence, it mixes and reproduces based on what it consumed, solely. I might get inspired by people, and add my own values to it, iterate over it and diverge from what I'm inspired from ultimately to create my own style. AI doesn't work like that. Also, if I do the same amount of inspiration with the same precision and accuracy, I'll be neck deep in accusations and lawsuits (for the right reasons). As a result, just because we fail to ask the right questions to reproduce the training data verbatim or almost verbatim doesn't mean that the information is not there. At the end, a neural network is a compression algorithm which encodes data in terms of weights. Given the correct input, you can regenerate the training data as is. Unless you have special abilities, you can't read 500 books an hour, remember them perfectly, and generate derivative works by mashing all of them together. If I do and try to sell a novel, I'll be ridiculed no end. If I write a Ph.D. the same way and try to defend it, I'll be banned from academia for three lifetimes at least. For more elaboration on the subject, see [0]. [0]: https://news.ycombinator.com/item?id=39188463 https://news.ycombinator.com/item?id=39188463

miki123211 3y ago
The myth that AI models store all its training data in its weights verbatim is as widespread as it is false. In fact, if this were the case, deep neural networks would be considered far better compression algorithms than anything we have on the market right now, by literal orders of magnitude. If you divide Stable Diffusion's file size by the number of images used to train it, you get something like 1.2 bits per image, and it is physically impossible to get this kind of a compression ratio. The actual problem with AI is that it sometimes plagiarizes random fragments of the work it is trained on, even if it is not the user's intend, and we currently don't really know how to fully prevent this.
- bayindirh 3y ago
  It still doesn't change the fact that the inclusion of commercial works is copyright infringement though. Same for code generating models trained on Open Source and Free Software. Tons of licenses violated, from strong copyleft to source available models and reproduced (almost) verbatim with comments intact. Some researcher's codebase is almost completely reproducible without any licensing information just by hinting the function names. Maybe for the image compression it's borderline impossible for now due to network size, but for text and code, generation of training data almost verbatim is very possible and straightforward. Also in image generation models, style transfer is the bigger problem, because it completely eliminates the artist who uses/created the style in the first place. "You pioneered this, and we fine tuned this model with your images, and we can do your work for free, without you, have a nice day". However, the artist's life expenses doesn't disappear when they're transferred to an image generation model. This is also unethical.
  - miki123211 3y ago
    Style transfer is perfectly legal AFAIK, asking artists to do a drawing of X in the style of Y was already a thing. Style is not copyrightable.
    - bayindirh 3y ago

__loam 3y ago

The "humans do it too" argument is totally irrelevant to this because humans have special and specific privileges under the law that computers don't. The problem is that a lot of data was copied into training sets and used for commercial purposes without permission.

ribosometronome 3y ago

Whether or not I'm influenced by media isn't super relevant to whether or not I pirated that media. Before even arriving at the question of whether or not the resulting models are infringing, it's clear the training data is.