3 ms·
> Regardless of the lawsuit, this seems like a quite spurious, self-serving argument in and of itself. If the “coordinates” of the image were not equivalent to
by alex_sf 4y ago
> Regardless of the lawsuit, this seems like a quite spurious, self-serving argument in and of itself. If the “coordinates” of the image were not equivalent to the image ...
It's simply not. Stable Diffusion 1.5 was trained on over two billion images. Even if we assume the images were only 10kb on average, that would require 20TB of storage space. The pruned 1.5 model is only 4.27GB, or 4,684x smaller. It is fundamentally and provably impossible to achieve that sort of compression ratio on diverse and already compressed images.
'Coordinates of the image' is a layman's explanation of latent space and the training process, it should not be taken literally.
> how would it be possible to fine tune the model on a set of images and recreate their style?
The fine tune process represents additional training, and to reliably and consistent reproduce a consistent style generally requires overfitting. It is very roughly analagous to an artist using a reference while drawing/painting.
> This is setting aside the myriad examples where SD regurgitates fairly close copies of individual works.
Some works were overrepresented in the dataset because they are overrepresented in the world. There are substantially more images and variants of the Mona Lisa on the internet than there are Random Twitter Artist's Furry Waifu.
This works in much the same way for humans, who are more far more likely to be influenced by the Mona Lisa than Furry Waifu.
> This is a bit like training a model on the works of Shakespeare, but then claiming that the tensors resulting from ingesting the data are not actually Shakespeare’s writing.
.. They aren't. Shakespeare did not write them. His works can't be reproduced from them. There is, provably, not enough data for it. This is more different than if an individual read and referenced Shakespeare while writing a play, for all that entails. Specifically: whether it's a human or a model generating the content, the content that is generated could be a violation of copyright.
You'll note that this is no different to if I copy and paste Mickey Mouse onto a tshirt design, or if I draw him on a piece of paper with a crayon.
Should we also be up in arms about copy/paste and crayons?
> Oh really, where’d they come from then? Thin air?
This hits on a more important point than I think you realize here. Where did inspiration for the human artists come from? Did they spring from a formless void? Or have they seen a lot of images, internalized what they think was important from it, and then generated art from that?
- bugglebeetle 4y ago> They aren't. Shakespeare did not write them. His works can't be reproduced from them. There is, provably, not enough data for it. Oh really? Try googling overfitting. Or ask ChatGPT!
- alex_sf 4y agoYou're not exactly communicating in good faith here, given that I addressed exactly this: > The fine tune process represents additional training, and to reliably and consistent reproduce a consistent style generally requires overfitting ... It's clear you have a perspective that is set in stone, and insist on not understanding the technology. Hopefully you'll re-evaluate when the plaintiffs in these suits inevitably lose.
- bugglebeetle 4y agoNo, I don’t care about the lawsuit because the intent with releasing SD was to get sued and then lock in a monopoly based on big players being the only ones capable of rights enforcement. See my other comment. > I don’t really care about the copyright argument as it relates to human learning because I think this is all a Napster-style false flag by capital owners to enclose ALL data on the internet. The intent isn’t to argue about these models from first principles such that we all have IP-restriction free access from them. It’s to make them do enough legally gray things at scale that they get restricted to only a few power players.