zlacker

>>zacwes+(OP)
“Sta­ble Dif­fu­sion con­tains unau­tho­rized copies of mil­lions—and pos­si­bly bil­lions—of copy­righted images.”

That’s going to be hard to argue. Where are the copies?

“Hav­ing copied the five bil­lion images—with­out the con­sent of the orig­i­nal artists—Sta­ble Dif­fu­sion relies on a math­e­mat­i­cal process called dif­fu­sion to store com­pressed copies of these train­ing images, which in turn are recom­bined to derive other images. It is, in short, a 21st-cen­tury col­lage tool.“

“Diffu­sion is a way for an AI pro­gram to fig­ure out how to recon­struct a copy of the train­ing data through denois­ing. Because this is so, in copy­right terms it’s no dif­fer­ent from an MP3 or JPEG—a way of stor­ing a com­pressed copy of cer­tain dig­i­tal data.”

The examples of training diffusion (eg, reconstructing a picture out of noise) will be core to their argument in court. Certainly during training the goal is to reconstruct original images out of noise. But, do they exist in SD as copies? Idk

>>dr_dsh+12
One idea I had was to try to recreate the original using a prompt. If you succeed, it should be obvious that the original was in the training set?

>>baxtr+TV
This is quite easy to do, but the results can be off in funny ways. For example, try putting this into SD with Euler a sampling and a cfg scale of 10:

"The Night Watch, a painting made by Rembrandt in 1642"

It generates a convincing low-res imitation about half the time, but it also has a tendency to make the triband flag into an American flag, or put an old ship in the background, or replace the dark city arch with a sunset...

If you keep refining the prompt, you can get closer, but at that point you're just describing what the painting should look like, rather than asking the model to recall an original work.