This would be fantastic imo. A new era of the commons.
>Adobe
I disagree here. Adobe has trained only on public domain and their own stock images. So why would adobe be against training on unlicensed data being an infringement? It would eliminate much of their competition...
Adobe is lying. They are relying on general ignorance about the technology to get away with it.
Adobe has not shown how they train the text encoders in Firefly, or what images were used for the text-based conditioning (i.e. "text to image") part of their image generation model. They are almost certainly using CLIP or T5, which are trained on LAION2b, an image dataset with the very problems they are trying to address, C4 (a text dataset similarly encumbered) and similar.
bUt nO oNe eLsE hAs bRoUgHt tHiS uP. It's so arcane for non-practitioners. Talk about this directly with someone like Astropulse, who monetizes a Stable Diffusion model: no confusion, totally agrees with me. By comparison, I've pinged the Ars Technica journalist who just wrote about this issue: crickets. Posted to the Adobe forum: crickets. E-mailed them on their specific address for this: crickets. I have no idea why something so obvious has slipped by everyone's radar!
So no chance. I think it's a big fat lie. They'd have to have made some other scientific breakthrough, which they didn't.
Using information from https://openai.com/research/clip and https://github.com/mlfoundations/open_clip, it's possible to answer this question.
It's certainly not impossible, but it's impracticable. On 248m images (roughly the size of Adobe Stock), CLIP gets 37% on ImageNet, and on the 2000m from LAION, it performs 71-80%. And even with 2000m images, CLIP is substantially worse performing than the approach that Imagen uses for "text comprehension," which relies on essentially many billions more images and text tokens.