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

In fairness, Diffusion is arguably a very complex entropy coding similar to Arithmetic/Huffman coding.

Given that copyright is protectable even on compressed/encrypted files, it seems fair that the “container of compressed bytes” (in this case the Diffusion model) does “contain” the original images no differently than a compressed folder of images contains the original images.

A lawyer/researcher would likely win this case if they re-create 90%ish of a single input image from the diffusion model with text input.

>>yazadd+X3
Great. Now the defence shows an artist that can recreate an image. Cool, now people who look at images get copyright suits filed against them for encoding those images in their heads.

>>anothe+96
Just because I look at an image does not mean that I can recreate it. storing it in the training data means the AI can recreate it.

There's a world of difference that you are just writing off.

>>dylan6+07
No, it means there is a 512 bit number you can combine with the training data to reproduce a reasonable though not exact likeness (attempts to use SD and others as compression algorithms show they're pretty bad at it, because while they can get "similar" they'll outright confabulate details in a plausible looking way - i.e. redrawing the streets of San Francisco in images of the golden gate bridge).

Which of course then arrives at the problem: the original data plainly isn't stored in a byte exact form, and you can only recover it by providing an astounding specific input string (the 512 bit latent space vector). But that's not data which is contained within Stable Diffusion. It's equivalent to trying to sue a compression codec because a specific archive contains a copyrighted image.

>>XorNot+99
> It's equivalent to trying to sue a compression codec because a specific archive contains a copyrighted image.

That's plainly untrue, as Stable Diffusion is not just the algorithm, but the trained model—trained on millions of copyrighted images.

>>danari+SK
But in fairness, even a human could know how to violate copyright but cannot be sued until they do violate it.

SD might know how to violate copyright but is that enough to sue it? Or can you only sue violations it helps create?