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how is that any different from new human artist that study other artists work to learn a style or technique. In fact it used to be that the preferred way for painters to learn was to repeatedly copy paintings of masters.
What you and many other in the thread seem to be oblivious about is that algorithms are not people. Yes, it may come as a shock to autistic engineers, but the fact that a machine can do something to what a person does does not warant it equal protection under the law. Copyright, and laws in general, exists to protect the human members of society not some abstract representation of them.
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You can't rip something and compress it badly enough to not violate copyright when you sell it. The point of compression is to throw away information about the original in ascending order of importance.
>You can't rip something and compress it badly enough to not violate copyright when you sell it. While I doubt that specific case has been tested in court, arguably you could. If you created glitch art ( https://en.wikipedia.org/wiki/Glitch_art ) via compression artifacts, and your work was sufficiently distinct from the original work, I think you would have a reasonable case for transformative use ( https://en.wikip…
“Stable Diffusion contains unauthorized copies of millions—and possibly billions—of copyrighted images.” That’s going to be hard to argue. Where are the copies? “Having copied the five billion images—without the consent of the original artists—Stable Diffusion relies on a mathematical process called diffusion to store compressed copies of these training images, which in turn are recombine…
You seem to be under the impression that SD can only generate original art. However, it will literally recreate existing paintings for you if you just prompt it with the title. Identical composition and everything.
But it's virtually impossible for these models to make an exact replica – a photocopy - of an existing painting, because that would make it break some laws of information theory probably. It's not a lossless compression engine. Paintings like, "Girl With the Pearl Earring" appear so frequently in the datasets that the models tend to overfit on them – which is actually not something you want when designing a model. It tends to create issues for you. But that's why a painting like that can be simulated somewhat accurately. But even then – it's never going to be 100%.
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> storing it in the training data means the AI can recreate it. No it doesn't, it means that abstract facts related to this image might be stored.
This just sounds like really fancy, really lossy compression to me. Compression that returns something different from the original most of the time, but still could return the original.
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No, it means there is a 512 bit number you can combine with the training data to reproduce a reasonable though not exact likeness (attempts to use SD and others as compression algorithms show they're pretty bad at it, because while they can get "similar" they'll outright confabulate details in a plausible looking way - i.e. redrawing the streets of San Francisco in images of the golden gate bridge). Which of course t…
> It's equivalent to trying to sue a compression codec because a specific archive contains a copyrighted image. That's plainly untrue, as Stable Diffusion is not just the algorithm, but the trained model—trained on millions of copyrighted images.
It's like the compression that occurs when I say "Mona Lisa" and you read it, and can know many aspects of that painting.
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Don't think stable Diffusion can reproduce any single image its trained on, not matter what prompts you use. It does have Mona lisa because of over fitting. But that's because there is too much Mona lisa on internet. These artist taking part in suit won't be able to recreat any of their work.
Does SD have to recreate the entire image for it to violate copyright? As a thought experiment, imagine a variant of something like SD was used for music generation rather than images. It was trained on all music on spotify and it is marketed as a paid tool for producers and artists. If the model reproduces specific sounds from certain songs, e.g. the specific beat from a song, hook, or melody, it would seem pretty s…
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What you and many other in the thread seem to be oblivious about is that algorithms are not people. Yes, it may come as a shock to autistic engineers, but the fact that a machine can do something to what a person does does not warant it equal protection under the law. Copyright, and laws in general, exists to protect the human members of society not some abstract representation of them.
It seems like you're using "autistic" as an insult here. If that's not your intention you might want to edit this comment to use different verbage.
Legislation is driven by people who are, on aggregate, not autistic. So it's entirely appropriate to presume that a person not understanding how that process works is indeed autistic, especially if they suggest machines are subjects of law by analogy with human beings.
It's not that autists are bad people, they are just outliers in the political spectrum, as you can see from the complete disconnect of up-voted AI-related comments on Hacker News, where autistic engineers are clearly over-represented, versus just about any venue where other professionals, such as painters or musicians, congregate. Just try to suggest to them that a corporation has the right to use their work for free and profit from it while leaving them unemployed, because the algorithm the corporation uses to exploit them is in some abstract sense similar to how their brain works. That position is so for out on the spectrum that presuming a personality peculiarity of the emitter is the absolutely most charitable interpretation.
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In that vein, surely MD5 hashes should also be copyrighted, as they are derived from a work.
Not really, since one of the major characteristics is being able to recover the copyrighted work from the encoded version. Since md5 hashes don't share this property, they're not "in that vein".
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This argument's pedantic and problematic for artists; take away a human's "dataset" and processes and they are also unable to produce a single original "pixel".
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