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“Stable Diffusion contains unauthorized copies of millions—and possibly billions—of copyrighted images.” That’s going to be hard to argue. Where are

“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 recombined to derive other images. It is, in short, a 21st-century collage tool.“ “Diffusion is a way for an AI program to figure out how to reconstruct a copy of the training data through denoising. Because this is so, in copyright terms it’s no different from an MP3 or JPEG—a way of storing a compressed copy of certain digital data.” The examples of training diffusion (eg, reconstructing a picture out of noise) will be core to their argument in court. Certainly during training the goal is to reconstruct original images out of noise. But, do they exist in SD as copies? Idk

codeflo 4y ago
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.
- Filligree 4y ago
  I’m curious. Can you give an example of that happening for a painting that’s still in copyright?
- Aerroon 4y ago
  Photoshop can also recreate existing paintings if you just "prompt it with the correct input", no?
  - codeflo 4y ago
    So you're saying "if I put the made-up straw man argument that I intend to knock down in quotation marks, it's less obvious that it's not actually what the other person wrote"?
    - Aerroon 4y ago
      I'm pointing out that the model has a piece missing - the input from the user. You can't just flippantly dismiss it, because input from the user is a crucial part of recreating the works the model is supposedly copying. It's an important factor to consider, because any digital painting program will let you recreate any art work with the correct user input. It's not sufficient to just consider whether it can reproduce an image, but also how much user input was required to do so.
- gdubs 4y ago
  Models like MidJourney and StableDiffusion can generate very close renditions of some very well known paintings – and if it has enough of a conceptual understanding of even a less known painting, it can do a pretty impressive rendition of that as well. 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%.
akjetma 4y ago
I don't think you have to reproduce an entire original work to demonstrate copyright violation. Think about sampling in hip hop for example. A 2 second sample, distorted, re-pitched, etc. can be grounds for a copyright violation.
- Salgat 4y ago
  The difference here is that the images aren't stored, but rather an extremely abstract description of the image was used to very slightly adjust a network of millions of nodes in a tiny direction. No semblance of the original image even remotely exists in the model.
  - akjetma 4y ago
    there are some artists with very strong, recognizable styles. if you provide one of these artists' name in your prompt and get a result back that employs their strong, recognizable style, i think that demonstrates that the network has a latent representation of the artists work stored inside of it.
    - andybak 4y ago
      I was with you right up until the final sentence. How did "style" become "work"?
      - limitedsupply 4y ago
        That’s the key question of the lawsuit IMO!
      - WA 4y ago
        Because in some cases, adding a style prompt gives almost the original image: https://www.reddit.com/r/StableDiffusion/comments/wby0ob/it_might_be_possible_for_stable_diffusion_models/ https://www.reddit.com/r/StableDiffusion/comments/wby0ob/it_...
        4y ago
TheDong 4y ago
It doesn't matter if they exist as exact copies in my opinion. The law doesn't recognize a mathematical computer transformation as creating a new work with original copyright. If you give me an image, and I encrypt it with a randomly generated password, and then don't write down the password anywhere, the resulting file will be indistinguishable from random noise. No one can possibly derive the original image from it. But, it's still copyrighted by the original artist as long as they can show "This started as my image, and a machine made a rote mathematical transformation to it" because machine's making rote mathematical transformations cannot create new copyright. The argument for stable diffusion would be that even if you cannot point to any image, since only algorithmic changes happened to the inputs, without any human creativity, the output is a derived work which does not have its own unique copyright.
- dymk 4y ago
  > But, it's still copyrighted by the original artist as long as they can show "This started as my image, and a machine made a rote mathematical transformation to it" because machine's making rote mathematical transformations cannot create new copyright. Do you have evidence that this is actually what the courts have decided with respect to NNs?
- limitedsupply 4y ago
  So what happens if you put a painting into a mechanical grinder? Is the shapeless pile of dust still copyrighted work? I don’t think so.
  - jimnotgym 4y ago
    The owner of that Banksy painting certainly thinks so.
    - limitedsupply 4y ago
      The painting that has several cuts in about 25% of the surface area? Don’t think that constitutes as a shapeless pile of dust.
yazaddaruvala 4y ago
> That’s going to be hard to argue. Where are the copies? In fairness, Diffusion is arguably a very complex entropy coding similar to Arithmetic/Huffman coding. Given that copyright is protectable even on compressed/encrypted files, it seems fair that the “container of compressed bytes” (in this case the Diffusion model) does “contain” the original images no differently than a compressed folder of images contains the original images. A lawyer/researcher would likely win this case if they re-create 90%ish of a single input image from the diffusion model with text input.
- visarga 4y ago
  > 90%ish of a single input image Oh, one image is enough to apply copyright as if it were a patent, to ban a process that makes original works most of the time? The article authors say it works as a "collage tool" trying to minimise the composition and layout of the image as unimportant elements. At the same time forgetting that SD is changing textures as well, so it's a collage minus textures and composition? Is there anything left to complain about? unless, by draw of luck, both layout and textures are very similar to a training image. But ensuring no close duplications are allowed should suffice. Copyright should apply one by one, not in bulk. Each work they complain about should be judged on its own merits.
  - manholio 4y ago
    But they are not original works, they are wholly derived works of the training data set. Take that data set away and the algorithm is unable to produce a single original pixel. The fact that the derivation involves millions of works as opposed to a single one is immaterial for the copyright issue.
    - realusername 4y ago
      The training data set is indeed mandatory but that doesn't make the resulting model a derivative in itself. In fact the training is specifically made to remove derivatives.
synu 4y ago
You could make the same argument that as long as you are using lossy compression you are unable to infringe on copyright.
- visarga 4y ago
  That's a huge understatement. 5 billion images to a model of 5GB. 1 byte per image. Let's see if one byte per image would constitute a copyright violation in other fields than neural networks.
  - synu 4y ago
    It will be interesting to see how they legally define the moment where compression stops being compression and starts being an original work. If I train on one image I can get it right back out. Even two, maybe even a thousand? Not sure what the line would be where it becomes ok vs not but there will have to be some answer.
    - Xelynega 4y ago
      There only needs to be an answer if it's determined that some number isn't copyright infringement. The easy answer would be to say that the process is what prevents the works from being transformative(and thus copyrightable) and not the size of the training set.
  - forgotusername6 4y ago
    The distribution of the bytes matters a bit here. In theory the model could be over trained against one copyrighted work such that it is almost perfectly preserved within the model.
    - synu 4y ago
      You can see this with the Mona Lisa. You can get pretty close reproductions back by asking for it (or at least you could in one of the iterations). Likely it overfit due to it being such a ubiquitous image.
whateveracct 4y ago
This feels like the argument of a money launderer.
anothernewdude 4y ago
It's going to be very hard to them to argue against Stable Diffusion and not reach the conclusion that people looking at art are doing exactly what training the AI did. You looked at my art, now I can use copyright against the copies in your brain.
- visarga 4y ago
  By forcing the AI community to develop technology to avoid replication of training examples they might disclose every bit of human copying as well. What can detect copyright violations in AI can be applied on human works as well.
  - Filligree 4y ago
    I’m afraid we won’t like the outcome.
groestl 4y ago
> It is, in short, a 21st-century collage tool. Interesting that they mention collages. IANAL but it was my impression that collages are derivative work if they incorporate many different pieces and only small parts of the original. Their compression argument seems more convincing.
- Filligree 4y ago
  Compression down to two bytes per image? You run into the pigeonhole argument. That level of compression can only work if there are less than seventy thousand different images in existence, total. Certainly there’s a deep theoretical equivalent between intelligence and compression, but this scenario isn’t what anyone means by “compression” normally.
  - Xelynega 4y ago
    When gzip turns my 10k character ASCII text file into a a 2kb archive, has it "compressed each character down to a fifth of a byte per character"? No, thats a misunderstanding of compression. Just like gzip, training stable diffusion certainly removes a lot of data, but without understanding the effect of that transformation of the entropy of the data it's meaningless to say thing like "two bytes per image" because(like gzip) you need the whole encoded dataset to recover the image. It's compressing many images into 10GB of data, not a single image into two bytes. This is directly analogous to what people usually mean by "compression"
bsder 4y ago
> That’s going to be hard to argue. Where are the copies? If you take that tack, I'll go one step further back in time and ask "Where is your agreement from the original author who owns the copyright that you could use this image in the way you did?" The fact that there is suddenly a new way to "use an image" (input to a computer algorithm) doesn't mean that copyright magically doesn't also apply to that usage. A canonical example is the fact that television programs like "WKRP in Cincinnati" can't use the music licenses from the television broadcast if they want to distribute a DVD or streaming version--the music has to be re-licensed.
- huggingrear 4y ago
  My assumption would be 'fair use'. Artists themselves make use of this extremely often, like when doing paintovers on copyrighted images (VERY common), fan art where they paint trademarked characters (also VERY common). The are often done for commission as well. AFAIK, downloading and learning from images, even copyrighted images, fall under fair use, this is how practically every artist today learns how to draw. Stable Diffusion does not create 1:1 copies of artwork it has been trained on, and its purpose is quite the opposite, there may be cases where the transformative aspect of a generated image may be argued as not being transformative enough, but so far I've only seen one such reproducable image, which would be the 'bloodborne box art' prompt, which was also mentioned in this discussion.
  - zowie_vd 4y ago
    > when doing paintovers on copyrighted images (VERY common) What are you talking about? I've been doing drawing and digital painting as a hobby for a long time and tracing is absolutely not "VERY common". I don't know anybody who has ever done this. > fan art where they paint trademarked characters (also VERY common) This is true in the sense that many artists do it (besides confusing trademark law and copyright law: the character designs are copyright-protected, trademarks protect brand names and logos). However, it is not fair use (as far as I'm aware at least, I'm not a lawyer). A rightholder can request for fanart to be removed and the artist would have to remove it. Rightsholders almost never do, because fanart doesn't hurt them. There's also more examples of it reproducing copyright-protected images, I pulled the "bloodborne box art" prompt from this article: https://arxiv.org/pdf/2212.03860.pdf https://arxiv.org/pdf/2212.03860.pdf But I agree with you that reproducing images is very much not the intention of Stable Diffusion, and it's already very rare. The way I see it, the cases of Stable Diffusion reproducing images too closely is just a gotcha for establishing a court case.
rysertio 4y ago
I would agree that we're acting like hypocrites here. But unlike stable diffusion, GitHub didn't release their model. So it's extremely hard to know what's going on inside copilot, on the other hand we have the model of stable diffusion and we can see wether or not it has memorized copyrighted images.
locutous 4y ago
> That’s going to be hard to argue. Where are the copies? Discovery will show exactly what the base images for training are. You can view that the outputs are derivative works. I don't think the mechanism is going to shield the violation, and frankly it shouldn't. License your source material for the purpose and do it right. Doesn't everyone know it's wrong to steal?
- miohtama 4y ago
  People in art school also practice by studying existing art and images.
  - thethimble 4y ago
    I think what’s clear is that this is an unprecedented type of use. I’m really interested in seeing how the courts rule on this one as it has wide implications for the AI era.
    - joshspankit 4y ago
      If not done extremely carefully, it also has wide implications for human artists
    - speleding 4y ago
      Because this use is unprecedented, as you say, it's clear that the law wasn't written with this use case in mind. The more interesting question in my mind is what we think the new law should be, rather than what the courts happen to make of the existing law. I.e., I think the answer should come from politicians not from judges.
jrm4 4y ago
This is a gross misunderstanding of "copyright?" The model doesn't need to "contain" the images anymore than a Harry Potter knockoff needs to "contain" huge chunks of text from the originals.
- ghaff 4y ago
  It depends. If names are different, character and plot details differ, etc., a book about students at a school for wizards battling great evil may be a not particularly imaginative rip-off and may even invite litigation if it's too close, but I'm guessing it wouldn't win in court. See also The Sword of Shannara and Tolkien. https://en.wikipedia.org/wiki/The_Sword_of_Shannara https://en.wikipedia.org/wiki/The_Sword_of_Shannara Creators mimic styles and elements of others' works all the time. Unless an ML algorithm crosses some literal copying threshold, I fail to see it as doing anything substantially different from what people routinely do.
baxtr 4y ago
One idea I had was to try to recreate the original using a prompt. If you succeed, it should be obvious that the original was in the training set?
- zowie_vd 4y ago
  The LAION-5B dataset is public, so you can check directly whether a picture is in there or not. StabilityAI only takes a very limited amount of information from each individual picture, so for Stable Diffusion to closely reproduce a picture it would need to appear quite frequently in the dataset. There are examples of this, such as old famous paintings, "bloodborne box art" and probably many others, though I haven't looked deeply into it.
- gedy 4y ago
  No, the "original" is in the (likely detailed) prompt you give it.
- nhtsamera 4y ago
  This is quite easy to do, but the results can be off in funny ways. For example, try putting this into SD with Euler a sampling and a cfg scale of 10: "The Night Watch, a painting made by Rembrandt in 1642" It generates a convincing low-res imitation about half the time, but it also has a tendency to make the triband flag into an American flag, or put an old ship in the background, or replace the dark city arch with a sunset... If you keep refining the prompt, you can get closer, but at that point you're just describing what the painting should look like, rather than asking the model to recall an original work.
Aerroon 4y ago
Models for Stable Diffusion are about 2-8GB in size. 5 billion images means that every image gets about 1 byte. It seems to me that they're claiming here that Stability has somehow manage to store copies of these images in about 1 byte of space each. That's an incredible compression ratio!
- SillyUsername 4y ago
  It is a form compression that loses some much of the uniqueness which gives it the high ratio. If the concept is a little hard to grasp consider an AI model like a finite state machine, but it stores affinity and weights of the data's relationship to each other too. In GPT this is words and phrases, e.g. "Frodo Baggins" high affinity, "Frodo Superman" will be negligible. Now consider all words that may link to those words - potentially billions of words (or phrases), but (probably/hopefully) none replicated. The phrases are out of specific context because they cover _all contexts_ in the training data. When you speak to GPT it randomises these words in response to you, typically choosing the words/phrases with the highest affinity, to the words you prompted, this almost gives it the appearance of emergent AI, because it is crossing different concepts (texts) in it's answers. Stable Diffusion works similarly but with colours (words), and patterns/styles (phrases). Now if you ask for a green field in the style of Van Gogh, it could compare Van Gogh's work to a backdrop from Windows XP. You could argue depending on the degree of those things it gives you you are violating copyrights, however that narrow view doesn't take into account that although you've specifically asked for Van Gogh and that's where it concentrates, it's also pulling in work from potentially hundreds of other lower affinity sources. It's this dilution which means you'll never see an untainted original source image. So in essence, it's the user who is breaching the copyright by specifying concentration on specific terms in the prompt, not the model. The model is simply a set of patterns, and the user is making those patterns breach copyright which IMHO is no different to the user copying a painting with a brush. The brush isn't the thing you sue.
  - Aerroon 4y ago
    I think so too. I also think that this is a dangerous issue, because we don't really know how our brains work. If we set legal restrictions over this and then it turns out our brains work in a similar manner, then what?

codeflo 4y ago

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.

Filligree 4y ago
I’m curious. Can you give an example of that happening for a painting that’s still in copyright?
Aerroon 4y ago
Photoshop can also recreate existing paintings if you just "prompt it with the correct input", no?
- codeflo 4y ago
  So you're saying "if I put the made-up straw man argument that I intend to knock down in quotation marks, it's less obvious that it's not actually what the other person wrote"?
  - Aerroon 4y ago
    I'm pointing out that the model has a piece missing - the input from the user. You can't just flippantly dismiss it, because input from the user is a crucial part of recreating the works the model is supposedly copying. It's an important factor to consider, because any digital painting program will let you recreate any art work with the correct user input. It's not sufficient to just consider whether it can reproduce an image, but also how much user input was required to do so.
gdubs 4y ago
Models like MidJourney and StableDiffusion can generate very close renditions of some very well known paintings – and if it has enough of a conceptual understanding of even a less known painting, it can do a pretty impressive rendition of that as well. 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%.

akjetma 4y ago

I don't think you have to reproduce an entire original work to demonstrate copyright violation. Think about sampling in hip hop for example. A 2 second sample, distorted, re-pitched, etc. can be grounds for a copyright violation.

Salgat 4y ago
The difference here is that the images aren't stored, but rather an extremely abstract description of the image was used to very slightly adjust a network of millions of nodes in a tiny direction. No semblance of the original image even remotely exists in the model.
- akjetma 4y ago
  there are some artists with very strong, recognizable styles. if you provide one of these artists' name in your prompt and get a result back that employs their strong, recognizable style, i think that demonstrates that the network has a latent representation of the artists work stored inside of it.
  - andybak 4y ago
    I was with you right up until the final sentence. How did "style" become "work"?
    - limitedsupply 4y ago
      That’s the key question of the lawsuit IMO!
    - WA 4y ago
      Because in some cases, adding a style prompt gives almost the original image: https://www.reddit.com/r/StableDiffusion/comments/wby0ob/it_might_be_possible_for_stable_diffusion_models/ https://www.reddit.com/r/StableDiffusion/comments/wby0ob/it_...
      - 4y ago

TheDong 4y ago

It doesn't matter if they exist as exact copies in my opinion. The law doesn't recognize a mathematical computer transformation as creating a new work with original copyright. If you give me an image, and I encrypt it with a randomly generated password, and then don't write down the password anywhere, the resulting file will be indistinguishable from random noise. No one can possibly derive the original image from it. But, it's still copyrighted by the original artist as long as they can show "This started as my image, and a machine made a rote mathematical transformation to it" because machine's making rote mathematical transformations cannot create new copyright. The argument for stable diffusion would be that even if you cannot point to any image, since only algorithmic changes happened to the inputs, without any human creativity, the output is a derived work which does not have its own unique copyright.

dymk 4y ago
> But, it's still copyrighted by the original artist as long as they can show "This started as my image, and a machine made a rote mathematical transformation to it" because machine's making rote mathematical transformations cannot create new copyright. Do you have evidence that this is actually what the courts have decided with respect to NNs?
limitedsupply 4y ago
So what happens if you put a painting into a mechanical grinder? Is the shapeless pile of dust still copyrighted work? I don’t think so.
- jimnotgym 4y ago
  The owner of that Banksy painting certainly thinks so.
  - limitedsupply 4y ago
    The painting that has several cuts in about 25% of the surface area? Don’t think that constitutes as a shapeless pile of dust.

yazaddaruvala 4y ago

> That’s going to be hard to argue. Where are the copies? In fairness, Diffusion is arguably a very complex entropy coding similar to Arithmetic/Huffman coding. Given that copyright is protectable even on compressed/encrypted files, it seems fair that the “container of compressed bytes” (in this case the Diffusion model) does “contain” the original images no differently than a compressed folder of images contains the original images. A lawyer/researcher would likely win this case if they re-create 90%ish of a single input image from the diffusion model with text input.

visarga 4y ago
> 90%ish of a single input image Oh, one image is enough to apply copyright as if it were a patent, to ban a process that makes original works most of the time? The article authors say it works as a "collage tool" trying to minimise the composition and layout of the image as unimportant elements. At the same time forgetting that SD is changing textures as well, so it's a collage minus textures and composition? Is there anything left to complain about? unless, by draw of luck, both layout and textures are very similar to a training image. But ensuring no close duplications are allowed should suffice. Copyright should apply one by one, not in bulk. Each work they complain about should be judged on its own merits.
- manholio 4y ago
  But they are not original works, they are wholly derived works of the training data set. Take that data set away and the algorithm is unable to produce a single original pixel. The fact that the derivation involves millions of works as opposed to a single one is immaterial for the copyright issue.
  - realusername 4y ago
    The training data set is indeed mandatory but that doesn't make the resulting model a derivative in itself. In fact the training is specifically made to remove derivatives.

synu 4y ago

You could make the same argument that as long as you are using lossy compression you are unable to infringe on copyright.

visarga 4y ago
That's a huge understatement. 5 billion images to a model of 5GB. 1 byte per image. Let's see if one byte per image would constitute a copyright violation in other fields than neural networks.
- synu 4y ago
  It will be interesting to see how they legally define the moment where compression stops being compression and starts being an original work. If I train on one image I can get it right back out. Even two, maybe even a thousand? Not sure what the line would be where it becomes ok vs not but there will have to be some answer.
  - Xelynega 4y ago
    There only needs to be an answer if it's determined that some number isn't copyright infringement. The easy answer would be to say that the process is what prevents the works from being transformative(and thus copyrightable) and not the size of the training set.
- forgotusername6 4y ago
  The distribution of the bytes matters a bit here. In theory the model could be over trained against one copyrighted work such that it is almost perfectly preserved within the model.
  - synu 4y ago
    You can see this with the Mona Lisa. You can get pretty close reproductions back by asking for it (or at least you could in one of the iterations). Likely it overfit due to it being such a ubiquitous image.

whateveracct 4y ago

This feels like the argument of a money launderer.

anothernewdude 4y ago

It's going to be very hard to them to argue against Stable Diffusion and not reach the conclusion that people looking at art are doing exactly what training the AI did. You looked at my art, now I can use copyright against the copies in your brain.

visarga 4y ago
By forcing the AI community to develop technology to avoid replication of training examples they might disclose every bit of human copying as well. What can detect copyright violations in AI can be applied on human works as well.
- Filligree 4y ago
  I’m afraid we won’t like the outcome.

groestl 4y ago

> It is, in short, a 21st-century collage tool. Interesting that they mention collages. IANAL but it was my impression that collages are derivative work if they incorporate many different pieces and only small parts of the original. Their compression argument seems more convincing.

Filligree 4y ago
Compression down to two bytes per image? You run into the pigeonhole argument. That level of compression can only work if there are less than seventy thousand different images in existence, total. Certainly there’s a deep theoretical equivalent between intelligence and compression, but this scenario isn’t what anyone means by “compression” normally.
- Xelynega 4y ago
  When gzip turns my 10k character ASCII text file into a a 2kb archive, has it "compressed each character down to a fifth of a byte per character"? No, thats a misunderstanding of compression. Just like gzip, training stable diffusion certainly removes a lot of data, but without understanding the effect of that transformation of the entropy of the data it's meaningless to say thing like "two bytes per image" because(like gzip) you need the whole encoded dataset to recover the image. It's compressing many images into 10GB of data, not a single image into two bytes. This is directly analogous to what people usually mean by "compression"

bsder 4y ago

> That’s going to be hard to argue. Where are the copies? If you take that tack, I'll go one step further back in time and ask "Where is your agreement from the original author who owns the copyright that you could use this image in the way you did?" The fact that there is suddenly a new way to "use an image" (input to a computer algorithm) doesn't mean that copyright magically doesn't also apply to that usage. A canonical example is the fact that television programs like "WKRP in Cincinnati" can't use the music licenses from the television broadcast if they want to distribute a DVD or streaming version--the music has to be re-licensed.

huggingrear 4y ago
My assumption would be 'fair use'. Artists themselves make use of this extremely often, like when doing paintovers on copyrighted images (VERY common), fan art where they paint trademarked characters (also VERY common). The are often done for commission as well. AFAIK, downloading and learning from images, even copyrighted images, fall under fair use, this is how practically every artist today learns how to draw. Stable Diffusion does not create 1:1 copies of artwork it has been trained on, and its purpose is quite the opposite, there may be cases where the transformative aspect of a generated image may be argued as not being transformative enough, but so far I've only seen one such reproducable image, which would be the 'bloodborne box art' prompt, which was also mentioned in this discussion.
- zowie_vd 4y ago
  > when doing paintovers on copyrighted images (VERY common) What are you talking about? I've been doing drawing and digital painting as a hobby for a long time and tracing is absolutely not "VERY common". I don't know anybody who has ever done this. > fan art where they paint trademarked characters (also VERY common) This is true in the sense that many artists do it (besides confusing trademark law and copyright law: the character designs are copyright-protected, trademarks protect brand names and logos). However, it is not fair use (as far as I'm aware at least, I'm not a lawyer). A rightholder can request for fanart to be removed and the artist would have to remove it. Rightsholders almost never do, because fanart doesn't hurt them. There's also more examples of it reproducing copyright-protected images, I pulled the "bloodborne box art" prompt from this article: https://arxiv.org/pdf/2212.03860.pdf https://arxiv.org/pdf/2212.03860.pdf But I agree with you that reproducing images is very much not the intention of Stable Diffusion, and it's already very rare. The way I see it, the cases of Stable Diffusion reproducing images too closely is just a gotcha for establishing a court case.

rysertio 4y ago

I would agree that we're acting like hypocrites here. But unlike stable diffusion, GitHub didn't release their model. So it's extremely hard to know what's going on inside copilot, on the other hand we have the model of stable diffusion and we can see wether or not it has memorized copyrighted images.

locutous 4y ago

> That’s going to be hard to argue. Where are the copies? Discovery will show exactly what the base images for training are. You can view that the outputs are derivative works. I don't think the mechanism is going to shield the violation, and frankly it shouldn't. License your source material for the purpose and do it right. Doesn't everyone know it's wrong to steal?

miohtama 4y ago
People in art school also practice by studying existing art and images.
- thethimble 4y ago
  I think what’s clear is that this is an unprecedented type of use. I’m really interested in seeing how the courts rule on this one as it has wide implications for the AI era.
  - joshspankit 4y ago
    If not done extremely carefully, it also has wide implications for human artists
  - speleding 4y ago
    Because this use is unprecedented, as you say, it's clear that the law wasn't written with this use case in mind. The more interesting question in my mind is what we think the new law should be, rather than what the courts happen to make of the existing law. I.e., I think the answer should come from politicians not from judges.

jrm4 4y ago

This is a gross misunderstanding of "copyright?" The model doesn't need to "contain" the images anymore than a Harry Potter knockoff needs to "contain" huge chunks of text from the originals.

ghaff 4y ago
It depends. If names are different, character and plot details differ, etc., a book about students at a school for wizards battling great evil may be a not particularly imaginative rip-off and may even invite litigation if it's too close, but I'm guessing it wouldn't win in court. See also The Sword of Shannara and Tolkien. https://en.wikipedia.org/wiki/The_Sword_of_Shannara https://en.wikipedia.org/wiki/The_Sword_of_Shannara Creators mimic styles and elements of others' works all the time. Unless an ML algorithm crosses some literal copying threshold, I fail to see it as doing anything substantially different from what people routinely do.

baxtr 4y ago

One idea I had was to try to recreate the original using a prompt. If you succeed, it should be obvious that the original was in the training set?

zowie_vd 4y ago
The LAION-5B dataset is public, so you can check directly whether a picture is in there or not. StabilityAI only takes a very limited amount of information from each individual picture, so for Stable Diffusion to closely reproduce a picture it would need to appear quite frequently in the dataset. There are examples of this, such as old famous paintings, "bloodborne box art" and probably many others, though I haven't looked deeply into it.
gedy 4y ago
No, the "original" is in the (likely detailed) prompt you give it.
nhtsamera 4y ago
This is quite easy to do, but the results can be off in funny ways. For example, try putting this into SD with Euler a sampling and a cfg scale of 10: "The Night Watch, a painting made by Rembrandt in 1642" It generates a convincing low-res imitation about half the time, but it also has a tendency to make the triband flag into an American flag, or put an old ship in the background, or replace the dark city arch with a sunset... If you keep refining the prompt, you can get closer, but at that point you're just describing what the painting should look like, rather than asking the model to recall an original work.

Aerroon 4y ago

Models for Stable Diffusion are about 2-8GB in size. 5 billion images means that every image gets about 1 byte. It seems to me that they're claiming here that Stability has somehow manage to store copies of these images in about 1 byte of space each. That's an incredible compression ratio!

SillyUsername 4y ago
It is a form compression that loses some much of the uniqueness which gives it the high ratio. If the concept is a little hard to grasp consider an AI model like a finite state machine, but it stores affinity and weights of the data's relationship to each other too. In GPT this is words and phrases, e.g. "Frodo Baggins" high affinity, "Frodo Superman" will be negligible. Now consider all words that may link to those words - potentially billions of words (or phrases), but (probably/hopefully) none replicated. The phrases are out of specific context because they cover _all contexts_ in the training data. When you speak to GPT it randomises these words in response to you, typically choosing the words/phrases with the highest affinity, to the words you prompted, this almost gives it the appearance of emergent AI, because it is crossing different concepts (texts) in it's answers. Stable Diffusion works similarly but with colours (words), and patterns/styles (phrases). Now if you ask for a green field in the style of Van Gogh, it could compare Van Gogh's work to a backdrop from Windows XP. You could argue depending on the degree of those things it gives you you are violating copyrights, however that narrow view doesn't take into account that although you've specifically asked for Van Gogh and that's where it concentrates, it's also pulling in work from potentially hundreds of other lower affinity sources. It's this dilution which means you'll never see an untainted original source image. So in essence, it's the user who is breaching the copyright by specifying concentration on specific terms in the prompt, not the model. The model is simply a set of patterns, and the user is making those patterns breach copyright which IMHO is no different to the user copying a painting with a brush. The brush isn't the thing you sue.
- Aerroon 4y ago
  I think so too. I also think that this is a dangerous issue, because we don't really know how our brains work. If we set legal restrictions over this and then it turns out our brains work in a similar manner, then what?

“Sta­ble Dif­fu­sion con­tains unau­tho­rized copies of mil­lions—and pos­si­bly bil­lions—of copy­righted images.” That’s going to be hard to argue. Where are

“Sta­ble Dif­fu­sion con­tains unau­tho­rized copies of mil­lions—and pos­si­bly bil­lions—of copy­righted images.” That’s going to be hard to argue. Where are

“Stable Diffusion contains unauthorized copies of millions—and possibly billions—of copyrighted images.” That’s going to be hard to argue. Where are

“Stable Diffusion contains unauthorized copies of millions—and possibly billions—of copyrighted images.” That’s going to be hard to argue. Where are