Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

stablediffusionlitigation.com

Post reply on HN
Print view View original

351–360 of 473 posts

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#351

Post by ghaff »

b3morales wrote: post #338
ghaff wrote: post #295

Earlier quoted context omitted.

All the handwringing about generative AI brings to mind the aphorism about genies returning to bottles. There can be lawsuits and laws--and there may even be cases where an output by chance or by tickling the input sufficiently looks very close to something in the training set. But anyone who thinks this technology will be banned in some manner is... mistaken.

So as a code author I am pretty upset about Copilot specifically, and it seems like SD is similar (hadn't heard before about DeviantArt doing the same as what GitHub did). But I agree with this take: the tech is here, it's going to be used, and it's not going to be shut down by a lawsuit. Nor should it, frankly. What I object to is not the AI itself, or even that my code has been used to train it. It's the copyright…

I doubt Microsoft sees fragments of Windows source code as a particular crown jewel these days. That said, some of it is decades old code that was intended for the public to see (unlike, presumably, anything in a public GitHub repository). And some of it is presumably third-party code licensed to Microsoft that was likewise never intended for public viewing. So, while it would be a good gesture on the part of Microsoft to scan their own code--if they haven't done so--I could see why it might be problematic. (Just as training on private GitHub repos would be.)

tl;dr I think there's a distinction between training on copyrighted but public content and private content.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#352

Post by lolinder »

vnorilo wrote: post #120
yazaddaruvala wrote: post #28

Earlier quoted context omitted.

> 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…

Storing copies of training data is pretty much the definition of overfitting, right? The data must be encoded with various levels of feature abstraction for this stuff to work at all. Much like humans learning art, if devoid of the input that makes human art interesting (life experience). I think a more promising avenue for litigating AI plagiarism is to identify that the model understands some narrow slice of the so…

Even that approach seems highly vulnerable to fair use. If the model does not recreate a copyrighted work with enough fidelity to be recognized as such, then how can it be said to be in violation of copyright?

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#353

Post by Imnimo »

grandmczeb wrote: post #350
Imnimo wrote: post #339

They've got a copy of a figure from the original diffusion paper, showing a diffusion process on a spiral dataset. They seem to completely misunderstand it. The figure does not show image diffusion, rather it shows a diffusion process in which each data item is a 2D point. The figure is showing diffusion on an entire dataset and demonstrating that it can approximately reconstruct the spiral-shaped distribution. I'm s…

Wow, not only do they get this wrong, it’s the core example they use to demonstrate copying.

Yeah, and their next figure isn't any better. They show a latent space interpolation figure from DDPM, and they seem to think this is how Diffusion models produce a "collage" (as they describe the process). Of course, this figure has nothing to do with how image generation is actually performed. It's just an experiment for the purpose of the paper to demonstrate that the latent space is structured.

In fact, this only works because the source images are given as input to the forward process - thus, the details being interpolated are from the inputs not from the model. If you look at Appendix Figure 9 from the same paper (https://arxiv.org/pdf/2006.11239.pdf) it is clear what's going on. Only when you take a smaller number of diffusing (q) steps can you successfully interpolate. When you take a large number of diffusing steps (top row of figure 9), all of the information from the input images is lost, and the "interpolations" are now just novel samples.

It's very hard for me to find a reason to include Figure 8 but not Figure 9 in their lawsuit that isn't either a complete lack of understanding, or intentional deception.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#354

Post by williamcotton »

IncRnd wrote: post #146
realusername wrote: post #125

Earlier quoted context omitted.

The training data set is indeed mandatory but that doesn't make the resulting model a derivative in itself. In fact the training is specifically made to remove derivatives.

Go to stablediffusionweb.com and enter "a person like biden" into the box. You will see a picture exactly like President Biden. That picture will have been derived from the trained images of Joe Biden. That cannot be in dispute.

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 work.

Let's think about a cartoonish caricature of Joe Biden. What "makes up" Joe Biden?

https://www.youtube.com/watch?v=QRu0lUxxVF4

To what extent are these "constituent parts" present in every image of Joe Biden? All of them? Is the latent space not something that is instead hidden in all images of Joe Biden? Can an image of Joe Biden be made by anyone that is not derived from these "high order" characteristics of what is recognizable as Joe Biden across a number of different renderings from disparate individuals?

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#355

Post by danaris »

yazaddaruvala wrote: post #333
danaris wrote: post #275

Earlier quoted context omitted.

> 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.

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?

I would assert (with no legal backing, since this is the first suit that actually attempts to address the issue either way) that the trained model is a copyright infringement in itself. It is a novel kind of copyright infringement, to be sure, but I believe that use of copyrighted material in a neural net's training set without the creator's permission should be considered copyright infringement without any further act required to make it so.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#356

Post by jdironman »

chongli wrote: post #294
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…

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 software itself is not at issue here. If they had trained the network on public domain images then there’d be no lawsuit. The legal question to settle is whether it’s allowable to train (and use) a model on copyrighted images without permission from the artists. They may actually be succ…

Then I think any work of art or media inspired by past sources would fall into this category. It's a very grey line, and I haven't seen anyone or any case law put it into proper terms as of yet.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#357

Post by b3morales »

ghaff wrote: post #351
b3morales wrote: post #338

Earlier quoted context omitted.

So as a code author I am pretty upset about Copilot specifically, and it seems like SD is similar (hadn't heard before about DeviantArt doing the same as what GitHub did). But I agree with this take: the tech is here, it's going to be used, and it's not going to be shut down by a lawsuit. Nor should it, frankly. What I object to is not the AI itself, or even that my code has been used to train it. It's the copyright…

I doubt Microsoft sees fragments of Windows source code as a particular crown jewel these days. That said, some of it is decades old code that was intended for the public to see (unlike, presumably, anything in a public GitHub repository). And some of it is presumably third-party code licensed to Microsoft that was likewise never intended for public viewing. So, while it would be a good gesture on the part of Microso…

Private third-party GitHub repos is another good example. If licenses don't apply to training data, as GitHub has asserted, why not use those too? Do they think they'll get in trouble over it? Why doesn't the same trouble apply to my publicly-readable GPL-licensed code?

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#358

Post by skissane »

b3morales wrote: post #338
ghaff wrote: post #295

Earlier quoted context omitted.

All the handwringing about generative AI brings to mind the aphorism about genies returning to bottles. There can be lawsuits and laws--and there may even be cases where an output by chance or by tickling the input sufficiently looks very close to something in the training set. But anyone who thinks this technology will be banned in some manner is... mistaken.

So as a code author I am pretty upset about Copilot specifically, and it seems like SD is similar (hadn't heard before about DeviantArt doing the same as what GitHub did). But I agree with this take: the tech is here, it's going to be used, and it's not going to be shut down by a lawsuit. Nor should it, frankly. What I object to is not the AI itself, or even that my code has been used to train it. It's the copyright…

> Have they actually trained Copilot on their own source? If not, why not?

People have posted illegal Windows source code leaks to GitHub. Microsoft doesn’t seem to care that much because these repos stay up for months or even years at a time without Microsoft DMCAing them-if you go looking you’ll find some right now. I think it is entirely possible, even likely, that some of those repos were included in Copilot’s training data set. So Copilot actually was trained on (some of) Microsoft’s proprietary source code, and Microsoft doesn’t seem to care.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#359

Post by bluefirebrand »

derangedHorse wrote: post #337
bluefirebrand wrote: post #297

Earlier quoted context omitted.

The difference is that computers create perfect copies of images by default, people don't. If a person creates a perfect copy of something it shows they have put thousands of hours of practice into training their skills and maybe dozens or even hundreds of hours into the replica. When a computer generates a replica of something it's what it was designed to do. AI art is trying to replicate the human process, but it w…

You’re acting like the “computer” has a will of it’s own. Generating a perfect copy of an image would be a completely separate task from training a model for image generation. There are no models I know of with the ability to generate an exact copy of an image from its training set unless it was solely trained on that image to the point it could. In that case I could argue the model’s purpose was to copy that image r…

> There are no models I know of with the ability to generate an exact copy of an image from its training set

Is it "the model cannot possibly recreate an image from its training set perfectly" or is it "the model is extremely unlikely to recreate an image from its training set perfectly, but it could in theory"?

Because I am willing to bet it's the latter.

> You’re acting like the “computer” has a will of it’s own. Generating a perfect copy of an image would be a completely separate task from training a model for image generation.

Not my intent, of course I don't think computers have a will of their own. What I meant, obviously, is that it's always possible for a bad actor of a human to make the computer behave in a way that is detrimental to other humans and then justify it by saying "the computer did it, all I did is train the model".

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#360

Post by Ephil012 »

jeroenhd wrote: post #311
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…

If you can put a bunch of large things together into a small file and then later (lossily) extract the large thing out of that smaller file, I'd argue that's compression, yeah. It doesn't really matter if it was intended to be art up as a compression algorithm or not in my opinion. If anything, this approach can be considered a revolution in lossy image compression, even though there's no real market for that at the…

I still would not call the diffusion process a form of compression. The reason why is because as a whole these models don’t aim to exactly replicate their dataset. If they did, that’s considered overfitting which is a failure of the model (as another commenter said). Generally, these models can almost never be coaxed to give their original data back. To really be considered a form of compression, you’d have to make it easier to do that. Technically, you can do it (e.g. describing a very specific scene in a very specific style), but at that point you’re basically just giving detailed instructions on what to do. If I told a human to paint a very picture and gave them extremely specific steps, that would not be considered compression. That would just be them knowing how existing art patterns work and using that knowledge to follow my instructions. In general, I don’t think it should be considered compression because the results are almost always novel and it’s extremely hard to get anything even close to the original dataset.
Post reply on HN