3 ms·

Yup. There’s also this, FTA: > the original images themselves aren’t stored in the Stable Diffusion model, with over 100 terabytes of images used to create a t

• friend_and_foe 4y ago
  If you can't reproduce a quantitatively (not qualitatively) similar likeness of an image then it is not just a compressed image.
• marmada 4y ago
  By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. I wager 100 TB => 4GB is different from JPEG compression and more similar to what happens in our brains. "Neural compression" so to speak
  • notamy 4y ago
    > By that case all art should be copyrighted since our brain stores a highly compressed version of everything we've seen. Good thing this is already the case! https://en.wikipedia.org/wiki/Berne_Convention https://en.wikipedia.org/wiki/Berne_Convention > The Berne Convention formally mandated several aspects of modern copyright law; it introduced the concept that a copyright exists the moment a work is "fixed", rather than requiring registration. It also enforces a requirement that countries recognize copyrights held by the citizens of all other parties to the convention.
    • marmada 4y ago
      This doesn't make any sense in this context and I think you know it bud. I was making the point that stable diffusion != JPEG compression
  • wnkrshm 4y ago
    The fact that it is a different form of compression doesn't change that it's compression. What is the argument here, that a numerical method should have the same rights as a person?
• pulvinar 4y ago
  The difference is that JPEG does store the real image, at least close enough to within the given tolerance (determined by the compression factor). That image is as real as say an image on film (also not exact, nor in "original" form). With Stable Diffusion it's storing the style, but can't reproduce any single input image-- there aren't enough bits [0]. (except by luck, but that's really true for any storage). [0] https://en.wikipedia.org/wiki/Shannon–Hartley_theorem https://en.wikipedia.org/wiki/Shannon–Hartley_theorem
  • peoplefromibiza 4y ago
    > there aren't enough bits you can create compressed copy of a file containing 100TB of the letter "A" in much less than 4GB there could be enough bits in there to reproduce some of the inputs.
    • CuriouslyC 4y ago
      What this analogy is saying is that if an image is generic and derivative enough (or massively overrepresented in the training data) it may be possible to reconstruct a very close approximation from the model. If the training data is unbiased, I question the validity of copyright claims on an image that is sufficiently derivative that it can be reproduced in this manner.
      • gort19 4y ago
  • mjburgess 4y ago
    The weights of a NN are just a compressed representation of the training data, think lossy zip. Rank all generated images by similarity to the training data (etc.) and you can see what's stored. The Shannon-Hartley theorem isnt relevant. A 4GB zip of 100TB text data can exactly reproduce the initial 100TB for some distributions of that initial dataset.
    • 4y ago
• esperent 4y ago
  > Where do we draw the line? This is what we have courts and legislation for. I expect there's existing legislation here about what constitutes a different work versus an exact copy but it may need some updates for AI.
• hmahncke 4y ago
  The author of the original post (Andy Baio) found exactly where the line was. He released a (great) chip tune version of the jazz classic Kind of Blue (named Kind of Bloop), fully handled the music copyrights, and was promptly sued by the cover artist for Kind of Blue who believed that the pixel art cover of Kind of Bloop was not adequately transformative. https://waxy.org/2011/06/kind_of_screwed/ https://waxy.org/2011/06/kind_of_screwed/