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We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

stablediffusionlitigation.com

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Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#411

Post by bobbruno »

IncRnd wrote: post #396
williamcotton wrote: post #354

Earlier quoted context omitted.

You've made some errors in reasoning. First, there is a legal definition of a "derivative work" and there is an artistic notion of a "derivative work". If the two of us both draw a picture of the Statue of Liberty, artistically we have both derived the drawing based on the original statue. However, neither of these drawings in relation to the original sculpture nor the other drawing is legally considered a derivative…

I can draw Biden, yes, but SD can only draw Biden by deriving it's output from the images on which it was trained. This is a simple tautology, because SD cannot draw Biden without having been trained on that data. SD both creates derivative works and also sometimes creates pixel level copies from portions of the trained data.

Can you draw Biden without ever having seen him or a picture of him? So,why is it that you are not deriving but SD is?

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#412

Post by riversflow »

chii wrote: post #102
riversflow wrote: post #76

Earlier quoted context omitted.

> Are image generators giving exact (or very similar) copies of existing works? um, yes.[1][2] What else would they be trained on? According to the model card: [1] https://github.com/CompVis/stable-diffusion/blob/main/Stable... it was trained on this data set(which has hyperlinks to images, so feel free to peruse): [2] https://huggingface.co/datasets/laion/laion2B-en

> What else would they be trained on? why does it matter how it was trained? The question is, does the generative AI _output_ copyrighted images? Training is not a right that the copyright holder owns exclusively. Reproducing the works _is_, but if the AI only reproduces a style, but not a copy, then it isn't breaking any copyright.

Agree 100%. I misread the post as "given" rather than "giving" and was answering what I perceived the question to be–are models given copyright images–oops.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#413

Post by max47 »

Xelynega wrote: post #308
visarga wrote: post #88

Earlier quoted context omitted.

That's a huge understatement. 5 billion images to a model of 5GB. 1 byte per image. Let's see if one byte per image would constitute a copyright violation in other fields than neural networks.

You took the images, encoded them in a computer process, and the result is able to reproduce some of those images. I fail to see why the size of the training set in bytes and the size of the model in bytes matters. Especially if, as other commenters have noted, much if the training data is repeated(mentions of thousands of mina Lisa's) so a straight division(training size/parameters size) says nothing about the bytes…

Except that you can't recreate them. At least not without a process that would be similar to asking an artist to create a replica of a painting. Just because photoshop has the right color palet available to recreate art, it doesn't mean the software itself is one big massive copyright infrigement against every art piece that exist.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#414

Post by bobbruno »

manholio wrote: post #84
visarga wrote: post #42

Earlier quoted context omitted.

> 90%ish of a single input image Oh, one image is enough to apply copyright as if it were a patent, to ban a process that makes original works most of the time? The article authors say it works as a "collage tool" trying to minimise the composition and layout of the image as unimportant elements. At the same time forgetting that SD is changing textures as well, so it's a collage minus textures and composition? Is the…

But they are not original works, they are wholly derived works of the training data set. Take that data set away and the algorithm is unable to produce a single original pixel. The fact that the derivation involves millions of works as opposed to a single one is immaterial for the copyright issue.

That is not true. The dataset is needed, the same way that examples are used by a person learning to draw. But the dataset alone is not capable of producing images not derived from any part of it (and there are many examples of SD results that seem so far to be wholly original), so you can’t reduce stable diffusion to being only derived from the dataset. It may “remember” and generate parts of images in the dataset - but that is a bug, not a feature. With enough prompt tweaking, it may even generate a fairly good copy of pre-existing work - which was what the prompt requested, so responsibility should lie on the prompt writer, not on SD.

But the fact that it often generates new content, that didn’t exist before, or at least doesn’t breach the limits of fair use, goes against the argument made in the lawsuit.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#415

Post by EMIRELADERO »

bsder wrote: post #410
EMIRELADERO wrote: post #404

Earlier quoted context omitted.

The amount of the work taken is just one of the fair use factors. Courts often perform holistic analysis on all of them to decide if fair use applies.

That is why I pointed out both the scholarly exemption as well as the collage exception. There are arguments to be made for fair use--I'm just not sure the current crop of GPT falls under any of them.

But the point is that fair use is almost completely principles-based rather than rules-based. Besides the four factors in the statute and some judicial precedent it's pretty much at the discretion of the court.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#416

Post by ifdefdebug »

XorNot wrote: post #389
ifdefdebug wrote: post #345

Earlier quoted context omitted.

I think it boils down to one question: can you prompt the model to show mostly unchanged pictures from artists? Then it's definitely problematic. If not, then I don't have enough knowledge of the topic to give a strong opinion. (my previous answer was just an use case that fits your argument)

I mean no, it doesn't. It's like drawing something in Photoshop which is a copyright'd work: the act of creating it is the violation, it doesn't prove that Photoshop contains the content directly. The way SD model weights work, if you managed to prompt engineer a recreation of one specific work, it would only have been generated as a product of all the information in the entire training set + noise seed + the prompt.…

> And the prompt wouldn't look anything like a reasonable description of any specific work.

I think this is the most relevant line of your argument. Because if you could just ask it like "show me the latest picture of [artist]" then you'll have a hard time convincing me that this is fundamentally different from a database with a fancy query language and lots of copyrighted work in it.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#417

Post by puppydups »

ImprobableTruth wrote: post #378
puppydups wrote: post #257

Does anyone else think it's grifty for a company to scrape up your (and other's) intellectual property, reconfigure it, and then attempt to sell it back to you for just $9.99 via dreambooth?

If they also give you the means to just do it yourself? Imo something like dall-e or midjourney is much worse.

They are all horrible, including the open source one (SD). I would never wish MY OWN work to be stolen and used, so why would I ever use a tool that stole someone else's work? I try not to be hypocritical.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#418

Post by Ephil012 »

Ephil012 wrote: post #384
Ephil012 wrote: post #104

“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.” This seems like it’s not an accurate description of what diffusion is doing. A diffusion model is not the same as compression. They’re implying t…

I should clarify a bit about how latent space works as I didn't in the original comment. Stable diffusion has something called an encoder and decoder. What the encoder does is it takes an image, finds it's fundamental characteristics, and then converts it into a data point (for the sake of simplicity we will use a vector even though it doesn't have to be). Let's say the vector represents a black dog. If you took a si…

Update: As I’ve looked more into the topic the less sure I am now about if I’m correct. I still think that there’s probably little chance that the whole dataset is shipped with stable diffusion. However, I am wondering about if maybe partial examples are shipped with it (e.g. a dictionary of certain concepts) or if there any any other caveats where stable diffusion might contain traces of the original data (note: I don’t think it contains the whole dataset still). I am not an expert so there’s a chance I could be wrong about all of this. So take my words with a grain of salt. Regardless, I still don’t believe the characterization of stable diffusion just copying and pasting images is correct and I believe the lawsuit still is making several factual errors as others online have pointed out.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#419

Post by SillyUsername »

Aerroon wrote: post #371
dr_dshiv wrote: post #2

“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 recom­bine…

Models for Stable Diffusion are about 2-8GB in size. 5 billion images means that every image gets about 1 byte. It seems to me that they're claiming here that Stability has somehow manage to store copies of these images in about 1 byte of space each. That's an incredible compression ratio!

It is a form compression that loses some much of the uniqueness which gives it the high ratio. If the concept is a little hard to grasp consider an AI model like a finite state machine, but it stores affinity and weights of the data's relationship to each other too.

In GPT this is words and phrases, e.g. "Frodo Baggins" high affinity, "Frodo Superman" will be negligible. Now consider all words that may link to those words - potentially billions of words (or phrases), but (probably/hopefully) none replicated. The phrases are out of specific context because they cover _all contexts_ in the training data. When you speak to GPT it randomises these words in response to you, typically choosing the words/phrases with the highest affinity, to the words you prompted, this almost gives it the appearance of emergent AI, because it is crossing different concepts (texts) in it's answers.

Stable Diffusion works similarly but with colours (words), and patterns/styles (phrases). Now if you ask for a green field in the style of Van Gogh, it could compare Van Gogh's work to a backdrop from Windows XP. You could argue depending on the degree of those things it gives you you are violating copyrights, however that narrow view doesn't take into account that although you've specifically asked for Van Gogh and that's where it concentrates, it's also pulling in work from potentially hundreds of other lower affinity sources. It's this dilution which means you'll never see an untainted original source image.

So in essence, it's the user who is breaching the copyright by specifying concentration on specific terms in the prompt, not the model. The model is simply a set of patterns, and the user is making those patterns breach copyright which IMHO is no different to the user copying a painting with a brush.

The brush isn't the thing you sue.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#420

Post by astrange »

ghaff wrote: post #330
astrange wrote: post #170

Earlier quoted context omitted.

That is not the point of using the training data. It's specifically trained to not do that. See https://openai.com/blog/dall-e-2-pre-training-mitigations/ "Preventing Image Regurgitation".

That's probably a very relevant point. (I'm guessing.) If I ask for an image of a red dragon in the style of $ARTIST, and the algorithm goes off and says "Oh, I've got the perfect one already in my data"--or even "I've got a few like that, I'll just paste them together"--that's a problem.

That's extremely not how it works. If there's only one training example it's not going to remember anything like actual visual details of it.
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