My perspective is there are two different main issues about AI (especially Stable Diffusion). One is how it works consistently with the current law. Ml model is basically a highly lossy compressed data format. If you collect millions of copyrighted images, merge them into a super big image, then compress it into a .jpg. Are you allowed to redistribute this .jpg file? To me, it's mostly depending on how lossy (low qua…
To the extent that Stable Diffusion models are "lossy compression", the main one is somewhere between 1 and 10 bytes per image depending on whose answer I use for the question "how many images was it trained on?" (I assume the cause is 1.5, 2.0 and SDXL having different answers and the reporters conflating them). The geometric mean of those is ~three bytes, which is only enough for one single RGB pixel per image. For…
Here is a catch tho. It's just "by average" several bytes. We can't tell if some images practically contribute 0 bit to the final results while some others contribute more.
(I know this "contribute" word is a little non-sense in the context of ML. But existing lossy compression algorithms are not that different in this sense: if you compress a 1M frames produced by a 3D renderer to a .mpeg video, each frame doesn't contribute the same amount of bytes to the final result.)