13 ms·

> 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

• 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.
      • IncRnd 4y ago
        Go to stablediffusionweb.com and enter "a person like biden" into the box. You will see a picture exactly like President Biden. That picture will have been derived from the trained images of Joe Biden. That cannot be in dispute.
        • realusername 4y ago
          Just because it generates you an image like Biden still does not make it a derivative either. You can draw Biden yourself if you're talented and it's not considered a derivative of anything.
          • IncRnd 4y ago
            There is no need for rhetorical games. The actual issue is that Stable Diffusion does create derivatives of copyrighted works. In some cases the produced images contain pixel level details from the originals. [1] [1] https://arxiv.org/pdf/2212.03860.pdf https://arxiv.org/pdf/2212.03860.pdf
            • realusername 4y ago
              > The actual issue is that Stable Diffusion does create derivatives of copyrighted works. Nothing points to that, in fact even in this website they had to lie on how stablediffusion actually works, maybe a sign that their argument isn't really solid enough. > [1] https://arxiv.org/pdf/2212.03860.pdf https://arxiv.org/pdf/2212.03860.pdf You realize those are considered defects of the model right? Sure, this model isn't perfect and will be improved.
              • IncRnd 4y ago
                > You realize those are considered defects of the model right? Sure, this model isn't perfect. You can call copying of input as a defect, but why are you simultaneously arguing that it doesn't occur?
    • forgotusername6 4y ago
      If I were to take the first word from a thousand books and use it to write my own would I be guilty of copyright violations?
      • yazaddaruvala 4y ago
        Words have a special carve out in copyright law / precedent. So much so that a whole other category of Intellectual Property exists called Trademarks to protect special words. But back to your point “if you were to take the first sentence from a thousand books and use it in your own book”, then yes based on my understanding (I am not a lawyer) of copyright you would be in violation of IP laws.
        • basch 4y ago
          I doubt it would be a violation. Specifically fair use #3 "the amount and substantiality of the portion used in relation to the copyrighted work as a whole." A sentence being a copyright violation would make every book review in the world illegal.
    • basch 4y ago
      If I take a million copywritten images from magazines, cut them with scissors, and make a single collage, I would expect the resulting image to be fair use. Fair use is an affirmative defense, like self defense, where you justify your infringement. People are treating this like its a binary technical decision. Either it is or isn't a violation. Reality is that things are spectrums and judges judge. SD will likely be treated like a remix that sampled copywritten work, but just a tiny bit of each work, and sufficiently transformed it to create a new work.
      • chongli 4y ago
        If I take a million copywritten images from magazines, cut them with scissors, and make a single collage, I would expect the resulting image to be fair use. That’s not how it works. Your collage would be fine if it was the only one since you used magazines you bought. Where you’d get into trouble is if you started printing copies of your collage and distributing them. In that case you’d be producing derived works and be on the hook for paying for licenses from the original authors.
        • basch 4y ago
          That’s not how fair use works. It’s not a binary switch where commercial derivatives automatically require licensing. Such a college would be ruled transformative and non competitive. Me having bought the magazines also has nothing to do with anything. Would apply equally if they were gifted or free or stolen.
    • williamcotton 4y ago
      If I make software that randomly draws pixels on the screen then we can say for a fact that no copyrighted images were used. If that software happens to output an image that is in violation of copyright then it is not the fault of the model. Also, if you ran this software in your home and did nothing with the image, then there's no violation of copyright either. It only becomes an issue when you choose to publish the image. The key part of copyright is when someone publishes an image as their own. That they copy an image doesn't matter at all. It's what they DO with the image that matters! The courts will most likely make a similar distinction between the model, the outputs of the model, and when an individual publishes the outputs of the model. This would be that the copyright violation occurs when an individual publishes an image. Now, if tools like Stable Diffusion are constantly putting users at risk of unknowingly violating copyrights then this tool becomes less appealing. In this case it would make commercial sense to help users know when they are in violation of copyright. It would also make sense to update our copyright catalogues to facilitate these kinds of fingerprints.
    • smegger001 4y ago
      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.
      • manholio 4y ago
        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.
        • weknowbetter 4y ago
          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.
          • manholio 4y ago
            What do you mean, autism is well established as a personality trait that diminishes empathy and the ability to understand other people's desires and emotions, while having a strong affinity to things, for example machines and algorithms. 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.
    • rule72 4y ago
      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".
      • manholio 4y ago
        [flagged]
        • weknowbetter 4y ago
          I don't think that your phrasing is helpful or appropriate.
        • johannboehme 4y ago
          I've prepared a boiler-plate response for autistic nitpickers like yourself: https://cdn150.picsart.com/upscale-235459796047212.png?r1024x1024 https://cdn150.picsart.com/upscale-235459796047212.png?r1024...
    • bobbruno 4y ago
      That is not true. The dataset is needed, the same way that examples are used by a person learning to draw. But the dataset alone is not capable of producing images not derived from any part of it (and there are many examples of SD results that seem so far to be wholly original), so you can’t reduce stable diffusion to being only derived from the dataset. It may “remember” and generate parts of images in the dataset - but that is a bug, not a feature. With enough prompt tweaking, it may even generate a fairly good copy of pre-existing work - which was what the prompt requested, so responsibility should lie on the prompt writer, not on SD. But the fact that it often generates new content, that didn’t exist before, or at least doesn’t breach the limits of fair use, goes against the argument made in the lawsuit.
      • manholio 4y ago
        The model can generate original images, yes, and those images might be fair use. But it can also generate near verbatim copies of the source works or substantial parts thereof, so the model itself is not fair use, it's a wholly derivative work. For example, if a publish a music remix tool with a massive database of existing music, creators might use to create collages that are original and fall under fair use. But the tool itself is not and requires permission from the rights owners.
    • rsuelzer 4y ago
      So, is any sort of creation that relies upon copyrighted or patented works copyright infringement? Is any academic research or art that references brands or other creations illegal? This is such a clear case of fair use that it could be a textbook example.
  • yazaddaruvala 4y ago
    > 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 law can do whatever its writers want. The law is mutable, so the answer to your question is “maybe”. Maybe SD will get outlawed for copyright reasons on a single image. The law and the courts have done sillier things.
    • ghaff 4y ago
      All the handwringing about generative AI brings to mind the aphorism about genies returning to bottles. There can be lawsuits and laws--and there may even be cases where an output by chance or by tickling the input sufficiently looks very close to something in the training set. But anyone who thinks this technology will be banned in some manner is... mistaken.
      • b3morales 4y ago
        So as a code author I am pretty upset about Copilot specifically, and it seems like SD is similar (hadn't heard before about DeviantArt doing the same as what GitHub did). But I agree with this take: the tech is here, it's going to be used, and it's not going to be shut down by a lawsuit. Nor should it, frankly. What I object to is not the AI itself, or even that my code has been used to train it. It's the copyright for me but not for thee way that it's been deployed. Does GitHub/Microsoft's assertion that training sidesteps licensing apply to GitHub/Microsoft's own code? Do they want to allow (a hypothetical) FSFPilot to be trained on their proprietary source? Have they actually trained Copilot on their own source? If not, why not? I published my source subject to a license, and the force of that license is provided by my copyright. I'm happy to find other ways of doing things, but it has to be equitable. I'm not simply ceding my authorship to the latest commercial content grab.
        • ghaff 4y ago
          I doubt Microsoft sees fragments of Windows source code as a particular crown jewel these days. That said, some of it is decades old code that was intended for the public to see (unlike, presumably, anything in a public GitHub repository). And some of it is presumably third-party code licensed to Microsoft that was likewise never intended for public viewing. So, while it would be a good gesture on the part of Microsoft to scan their own code--if they haven't done so--I could see why it might be problematic. (Just as training on private GitHub repos would be.) tl;dr I think there's a distinction between training on copyrighted but public content and private content.
  • chongli 4y ago
    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 software itself is not at issue here. If they had trained the network on public domain images then there’d be no lawsuit. The legal question to settle is whether it’s allowable to train (and use) a model on copyrighted images without permission from the artists. They may actually be successful at arguing that the outputs are either copies or derived works which would require paying the original artist for licenses.
    • jdironman 4y ago
      Then I think any work of art or media inspired by past sources would fall into this category. It's a very grey line, and I haven't seen anyone or any case law put it into proper terms as of yet.
      • deely3 4y ago
        Does "inspired" equal to "learned by software neural network"?
      • Spivak 4y ago
        Olivia Rodrigo is a good case study here. Good For You was so heavily inspired by Paramore that Hayley Williams was given songwriter credit despite having no involvement in its making. So humans can already run afoul of copyright this way, the bar for NNs might end up lower.
• yazaddaruvala 4y ago
  lol thinking about this more: I understand people’s livelihoods are potentially at stake, but what a shame it would be if we find AGI, even consciousness but have to shut it down because of a copyright dispute.
  • readthenotes1 4y ago
    what if they shut us down because of a copyright dispute? :-)
    • yazaddaruvala 4y ago
      Seriously!!! I didn’t say it cuz I didn’t think it would resonate, but it’s a whole new world we are quickly entering.
  • jimnotgym 4y ago
    I think the result will be image sharing websites where you have to agree to have your image read into the model. I think it is likely github will do the same with copilot.
    • 8n4vidtmkvmk 4y ago
      maybe a fair price to pay for free repo hosting. wouldn't want my private repos being used for training though
    • voakbasda 4y ago
      Image sharing sites routinely steal artwork from the web. My business has a unique logo with the business name in it. It has repeatedly shown up on such sites, despite repeated DMCA takedown requests. Simply appearing on a shared hosting site should not be enough.
  • visarga 4y ago
    Didn't yesterday someone proclaim generative models can't destroy anything worth protecting? It was about chatGPT but the principle is the same.
• magnat 4y ago
  And how that's different from gzip or base64, which can re-create original image when given appropriate input?
  • bryanrasmussen 4y ago
    well I guess it wouldn't be different, only there aren't any companies zipping up millions of images and then offering people the chance to get those images by putting in the text prompt that recreates them without paying any fees to the artists whose images were used.
    • rysertio 4y ago
      Search engines do that.
      • bryanrasmussen 4y ago
        good point, but didn't Google Image search lose some case and have to change their behavior?
        • rule72 4y ago
          If it's what I'm thinking about, I think they were forced to have decentralized image caching (i.e. the "user" is the one downloading images, Google just indexes). LAION-5b is also just an indexer (in terms of images).
  • yazaddaruvala 4y ago
    That’s my point, Diffusion[1] does seem to be “just like” gzip or base64. And it would be illegal for me to sell or distribute zipped copies of images without the copyright holder’s consent. Similarly there might be an argument for why Diffusion[1] specifically can’t be built with copyrighted images. [1] which is just one part of something like Stable Diffusion
    • astrange 4y ago
• anothernewdude 4y ago
  Great. Now the defence shows an artist that can recreate an image. Cool, now people who look at images get copyright suits filed against them for encoding those images in their heads.
  • dylan604 4y ago
    Just because I look at an image does not mean that I can recreate it. storing it in the training data means the AI can recreate it. There's a world of difference that you are just writing off.
    • realusername 4y ago
      > 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.
      • dylan604 4y ago
        The pedantry gets tiring. If the AI can't recreate it exactly, it can recreate a likeness that is compelling enough that the average person would think it was the same. If it can't now, it will as it gets better. That's the point of using the training data.
        • astrange 4y ago
          That is not the point of using the training data. It's specifically trained to not do that. See https://openai.com/blog/dall-e-2-pre-training-mitigations/ https://openai.com/blog/dall-e-2-pre-training-mitigations/ "Preventing Image Regurgitation".
          • ghaff 4y ago
            That's probably a very relevant point. (I'm guessing.) If I ask for an image of a red dragon in the style of $ARTIST, and the algorithm goes off and says "Oh, I've got the perfect one already in my data"--or even "I've got a few like that, I'll just paste them together"--that's a problem.
• chii 4y ago
  > In fairness, Diffusion is arguably a very complex entropy coding similar to Arithmetic/Huffman coding. so, digits of pi anyone?
• vnorilo 4y ago
  Storing copies of training data is pretty much the definition of overfitting, right? The data must be encoded with various levels of feature abstraction for this stuff to work at all. Much like humans learning art, if devoid of the input that makes human art interesting (life experience). I think a more promising avenue for litigating AI plagiarism is to identify that the model understands some narrow slice of the solution space that contains copyrighted works, but is much weaker when you try to deviate from it. Then you could argue that the model has probably used that distinct work rather than learned a style or a category.
  • lolinder 4y ago
    Even that approach seems highly vulnerable to fair use. If the model does not recreate a copyrighted work with enough fidelity to be recognized as such, then how can it be said to be in violation of copyright?
• madaxe_again 4y ago
  In that vein, surely MD5 hashes should also be copyrighted, as they are derived from a work.
  • Xelynega 4y ago
    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".
    • madaxe_again 4y ago
      If an encrypted file for which there is no key is treatable as derivative by law, then so should be an md5 hash. Both require vast brute force to extract/establish the original data, but both could be said to contain a derived representation of the work in question.
• williamcotton 4y ago
  There's a key difference. A compression algorithm is made to be reversible. The point of compressing an MP3 is to be able to decompress as much of the original audio signal as possible. Stable Diffusion is not made to decompress the original and actually has no direct mechanism for decompressing any originals. The originals are not present. The only thing present is an embedding of key components of the original in a multi-dimensional latent space that also includes text. This doesn't mean that the outputs of Stable Diffusion cannot be in violation of a copyright, it just means that the operator is going to have to direct the model towards a part of that text/image latent space that violates copyright in some manner... and that the operator of the model, when given an output that is in violation of copyright, is liable for publishing the image. Remember, it is not a violation of copyright to photocopy an image in your house... it's a violation when you publish that image!
  • codeonline 4y ago
    Lossy compression isn't reversible but presumably the content when compressed tjis way is still covered by copyright.
    • williamcotton 4y ago
      Pedantically, yes, lossy compression is not 100 percent reversible. Practically, the usefulness of compression is that it does return the original content with as little loss as possible… so lossy compression is mostly reversible. All of my other points remain unchanged by this pedantry.
      • ouid 4y ago
        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.
        • eurleif 4y ago
          >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 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.wikipedia.org/wiki/Transformative_use https://en.wikipedia.org/wiki/Transformative_use).
• angusturner 4y ago
  Stable diffusion (or any likelihood-based generative model) is a learned compression algorithm. It is not the "container of compressed bytes". You can use a trained generative model to compress images, by combining it with some kind of entropy coding / arithmetic coding. In this sense, stable diffusion is more analogous to the JPEG algorithm than it is to a specific collection of JPEG files. As it stands, the originals trainng data is not stored, even in a compressed way.
• vintermann 4y ago
  > In fairness, Diffusion is arguably a very complex entropy coding similar to Arithmetic/Huffman coding. Not the way it's used in Stable Diffusion models. Compressed data can be decompressed knowing only the decompression algorithm. To recover data from a stable diffusion model, you need to know the algorithm and the prompt. A critical part of the information _isn't_ in the data you decompress, it has to come from you. (And this isn't that relevant, but it would be lossy, perceptual compression like jpeg or mp3, not lossless compression like Huffman or Arithmetic coding.)