Same for code generating models trained on Open Source and Free Software. Tons of licenses violated, from strong copyleft to source available models and reproduced (almost) verbatim with comments intact.
Some researcher's codebase is almost completely reproducible without any licensing information just by hinting the function names.
Maybe for the image compression it's borderline impossible for now due to network size, but for text and code, generation of training data almost verbatim is very possible and straightforward.
Also in image generation models, style transfer is the bigger problem, because it completely eliminates the artist who uses/created the style in the first place. "You pioneered this, and we fine tuned this model with your images, and we can do your work for free, without you, have a nice day". However, the artist's life expenses doesn't disappear when they're transferred to an image generation model.
This is also unethical.
Just because you can doesn’t mean you should. That's what I'm trying to say.
IIRC it was like 1.4 bytes before adding in random initial and prompt. And Amiga Four-byte Burger is 4 bytes long.
[0]: https://bytecellar.com/2023/04/24/lost-amiga-four-byte-burge...
If you divide Stable Diffusion's file size by the number of images used to train it, you get something like 1.2 bits per image, and it is physically impossible to get this kind of a compression ratio.
The actual problem with AI is that it sometimes plagiarizes random fragments of the work it is trained on, even if it is not the user's intend, and we currently don't really know how to fully prevent this.