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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

#451

Post by ghaff »

astrange wrote: post #420
ghaff wrote: post #330

Earlier quoted context omitted.

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.

I realize that's not how it works. My point was that they're apparently taking deliberate steps to try to make sure the model trains over a large number of images and doesn't overfit on a small sample given a sufficiently specific "in the style of," etc.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#452

Post by woah »

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…

Microsoft is not training copilot on your proprietary code that you keep on your own systems, just like they are not training it on their proprietary code.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#453

Post by fritzo »

puppydups wrote: post #265
Kim_Bruning wrote: post #241

I keep getting reminded of the Tom Scott near-future video on how lawyers end up ruining the singularity. [1] As the line between artificial neural nets and natural neural nets continue to blur, surely the same rules should apply to both? Of course the counter-argument "some NNs are somehow different than others based on color [2]" walks you straight into an ongoing ethical minefield in the social sciences and biolog…

>>I keep getting reminded of the Tom Scott near-future video on how lawyers end up ruining the singularity If you think that this tech is remotely close to anything resembling general intelligence or a singularity, I've got an image model to sell you.

general intelligence is just an ecosystem of specialized models stitched together, interacting. if laws prohibit these components, then the system can't be built legally

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#454

Post by datacruncher01 »

I get their argument on the basis of the idea. But I think it's not valid when you apply the scale of the stable diffusion model. They show a case of a simple spiral and that the technology can create a similar looking spiral calling it a copy. But when you factor in the billions of trained images, the amount of specific information from all of these sources is like 1 byte.

They are going to have to show that the model copies ALL source images with perfect retention, and they are 100 percent full of shit if they think they can demonstrate that. What you may find is that some models out there are heavily biased on source images and can produce some outputs that are too similar to original works, in that case, there may be an issue.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#455

Post by 8n4vidtmkvmk »

galleywest200 wrote: post #342
8n4vidtmkvmk wrote: post #214

Earlier quoted context omitted.

Not a copy, a hash or fingerprint. Just enough data to measure if it's substantially similar. But yes, it may be infeasible to index and compare against every image ever uploaded.

Couldn't I just add a few non-sense bytes into my images to change the hash/fingerprint?

Hash yes, fingerprint maybe no. Maybe I'm using the term incorrectly here, but I think of fingerprint like a lossy hash. Like one way of doing this would be to resize the image to, say, 8 by 8, and quantize it to say, 16 colors. So the fingerprint size is 884 bits=32 bytes. Tiny changes aren't likely to change the fingerprint. You'd probably have to do something a little more clever so as not to get too many false positives though. Or once you get a hit, do a deeper comparison.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#456

Post by 8n4vidtmkvmk »

Kim_Bruning wrote: post #255
8n4vidtmkvmk wrote: post #214

Earlier quoted context omitted.

Not a copy, a hash or fingerprint. Just enough data to measure if it's substantially similar. But yes, it may be infeasible to index and compare against every image ever uploaded.

If I understand correctly, wouldn't a hash database of be larger than the actual model? (in fact by 1 or 2 orders of magnitude?)

Yeah, I guess so. The models are only 4 or 8 GB. A giant list of hashes would be bigger, sure. But they're 2 very different things. Model is for generating new images, this hash database is copyright enforcement. If you really want to check for violations I don't know how else you're going to do it.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#457

Post by soerxpso »

codeonline wrote: post #386
williamcotton wrote: post #329

Earlier quoted context omitted.

There's a key difference. A compression algorithm is made to be reversible. The point of compressing an MP3 is to be able to decompress as much of the original audio signal as possible. Stable Diffusion is not made to decompress the original and actually has no direct mechanism for decompressing any originals. The originals are not present. The only thing present is an embedding of key components of the original in a…

Lossy compression isn't reversible but presumably the content when compressed tjis way is still covered by copyright.

At what point does it become lossy enough that it's not protected, though? You can imagine a lossy compression algorithm that merely stores a 1 for images that are "more red" and a 0 for images that are "more blue." Such a compression algorithm would be storing some information about the thing it's compressing, but the closest reconstruction you could get from the compressed data is a red square or a blue square. Surely that's not copyright infringement? What about an algorithm that counts the fingers portrayed in an image and just reconstructs an image with the same amount of fingers? Where's the line?

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#458

Post by IncRnd »

williamcotton wrote: post #400
IncRnd wrote: post #396

Earlier quoted context omitted.

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.

Yes, and we are now using the artistic definition of “derived” and not the legal definition. You cannot copyright “any image that resembles Joe Biden”.

This isn't about what can be copyrighted but that there are copyrighted images being used without following the legal requirements.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#459

Post by SillyUsername »

"we’ve filed a class-action law­suit against Sta­bil­ity AI, DeviantArt, and Mid­jour­ney for their use of Sta­ble Dif­fu­sion"

Good luck with that - DevianArt doesn't produce work, just hosts it, which is mostly indeterminable from human input, and Midjourney use their own engine trained on different data. Advertising the fact you've not done adequate due diligence before public announcement of intent to sue doesn't (imho) give me the best impression of your lawyering chops.

Re: We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion

#460

Post by SillyUsername »

astrange wrote: post #420
ghaff wrote: post #330

Earlier quoted context omitted.

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.

Actually that's partly how it works.

A trained model holds relationships between patterns/colours in artwork and their affinity to the other images in the model (ignoring the English tagging of images data within this model for a minute). To this degree, it holds relationships between millions of images and the degree of similarities (i.e. affinity weighting of the patterns within them) in a big blob (the model).

When you ask for a dragon by $ARTIST it will find within it's model an area of data with high affinity to a dragon and that of $ARTIST. What has been glossed over in discussion here is that there are millions of other bits of related images - that have lower affinity - from lots of unrelated artwork which gives the generated image uniqueness. Because of this, you can never recreate 1:1 the original image, it's always diluted by the relationships from the huge mass of other training data, e.g. a colour from a dinosaur exhibit in a museum may also be incorporated as it looks like a dragon, along with many other minor traits from millions of other images, chosen at random (and other seed values).

Another interesting point is that a picture of a smiling dark haired woman would have high affinity with Mona Lisa, but when you prompt for Mona Lisa you may get parts of that back and not the patterns from the Mona Lisa*, even though it looks the same. That arguably (not getting Mona Lisa) is no longer the copyrighted data.

* Nb. this is a contrived example, since in SD the real Mona Lisa weightings will out number the individual dark haired woman's many times, however this concept might be (more) appropriate for minor artists whose work is not popular enough to form a significantly large amount of weighting in the training data.

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