321–330 of 337 posts
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Make a mouse cartoon in the style of Disney and tell me how well that goes down.
That's because you run into trademark laws, not copyright. Not to mention, if you can make the case that your art of the mouse is Parody, then it falls squarely under fair use.
https://en.wikipedia.org/wiki/List_of_songs_subject_to_plagi...
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Can a human "generate anything" beyond what essentially equates to random noise if they have never had any sensory input? Comparing a "trained" human brain with a "newborn" model seems strange if we actually want to delineate between what is and isn't art.
Ignoring the straw man argument here yes actually there are plenty of examples of individuals with no outside influence of art styles or references creating artworks. It's called outside art. https://en.wikipedia.org/wiki/Outsider_art
Second, your Outsider Art is something completely different, funnily enough a strawman. Surely you're not claiming that the creators of outside art have literally never had any sensory input in their lives? Or do you really think that one painter in two timelines, in one blind and in the other not, would paint exactly the same stuff?
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Some artists images just don't contain much entropy though? If an AI art engine outputs a frame of solid blue, is it infringing the copyright of Yves Klein's solid blue "IKB 79"? I think that some artists' styles can be accurately replicated without training on any of their work: because the artists' style is generic enough that it can be exhaustively encoded via the works of others. This seems like a bad test becaus…
> If an AI art engine outputs a frame of solid blue, is it infringing the copyright of Yves Klein's solid blue "IKB 79"? Probably not, though even this may be debatable given the specific prompt and specific similarities (for example, if it generated the exact color and exact aspect ratio for a prompt like "Yves Klein IKB 79", I could see an argument for infringement; if it generated the same thing for a prompt like…
Solid blue is superlative example, but I think the amount of creativity in different artworks has a HUGE amount of variance. You can kind of "score" any artwork using and AI Art engine in terms of "what is the minimum number of terms in a prompt that I can use to recreate a substantially similar image (that wasn't a part of the training set)"
Some artists' styles can probably be articulated in no fewer than 600 words. Other artists can probably be articulated in 6. The quantifiable amount of interesting decisions in a piece of art has orders of magnitude of variance.
If someone (manually) copies your style and lets AI train on their works, your 600-word masterpiece could instantly drop to 15-words once (human created non-copyright infringing) derivatives are in the training set.
We are explorers of the frontiers of latent space, and theres going to be all sorts of new things for people to get mad about along the way.
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> An NN is simply an approximation of a multi-valued function, whose parameters are adjusted by minimizing the difference between the output of the NN and the output of the real function for a certain input. Right, but that equally fits a biological NN if you zoom in that close. You'll need more than wikipedia to appreciate what deep-neural-networks are doing here, it's dimensional space that's key. What DNNs do that…
> Right, but that equally fits a biological NN if you zoom in that close. First of all, we have no idea how biological NNs learn, how they represent information, how they reason etc. Given what we do know, there is no reason to assume any similarity with ANNs on any of those fronts. Just to give one example, we know very well that a single biological neuron encodes significant information and is capable of reasoning…
What is laughable is that these abilities could come from interpolation or collage (not your claim but the plaintiff's). The only way these abilities could occur is if Stable Diffusion can represent image and text very similar to the way human brains comprehend them. The argument here is simple: what are the odds that StableDiffusion/DNNs have hit on a representational method that is totally different from human brains yet yields the same recognition, praise and admiration for the artist from everyone who sees it? Seems to me close to 0.
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I think that's the point of this blog post: it doesn't matter if the inputs are copyrighted, it matters if the output is infringing. It appears to be almost impossible to directly recreate a source image with SD, but it seems Copilot tends to produce a single input as its output, verbatim. Copilot isn't doing "synthesis" as does SD, it's acting more like a search engine.
Look at these images: > https://huggingface.co/spaces/stabilityai/stable-diffusion/d... They were prompted with the text "Mona Lisa Smile". Would you not say that they are an extremely close reproduction of the Mona Lisa, with barely any kind of synthesis?
I can hand paint a Mona Lisa like image that are this removed and be fine.
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It is different simply because it’s not a human. We can and often do assign laws that affect the automation of something a human can do. For example, installing a device on a firearm that repeatedly pulls the trigger creates a machine gun that is highly restricted legally, regardless of whether a human can easily pull the trigger at the same rate. Further, just because we can talk about how artists, at a high level d…
> It is different simply because it’s not a human So? An excavator clearly isn't a human, but it digs holes in the ground by the same principles that a human using only his bare hands would, only faster and more efficient.
In Washington you must dig for clams with human power, you cannot use a hydraulic clam pump. There was a time where you could down 50 birds with a single firing of a punt gun. This was made illegal, even if you could still eventually bag 50 birds with a normal shotgun.
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The LAION-5B dataset is metadata and URI pairs; all the images are publicly accessible on the Internet. Stable Diffusion's U-Net is trained to remove noise from images in latent space, which the variational autoencoder (VAE) converts to and from pixel space. CLIP embeddings are used to improve the denoising step of the U-Net by using the correlations between human language descriptions of the pixel image to reduce la…
It’s deeply disingenuous to say the U-Net is not trained on the images because it’s trained on the latent representations. Latents are a compressed representation of the source images that are fully recoverable. If you train a model on a compressed jpg of an image, or on any deterministic transformation of it, you’re still training it on that image. Any suggestion otherwise is only because someone is trying to put so…
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> why would it be the same for an automated process? It's perfectly acceptable for a human being to drive a a car, but driving one drunk is completely unacceptable. Conversely, there is no rule against creating or consuming art while intoxicated. So to answer your question, because it is not a matter of life and death. Take your argument and apply it to mass produced goods that were once the realm of only skilled cra…
> It's perfectly acceptable for a human being to drive a a car, but driving one drunk is completely unacceptable. Conversely, there is no rule against creating or consuming art while intoxicated. You've lost me here. Are you saying that the most important factor when judging whether or not something is appropriate is based on whether or not the activity is dangerous enough to be fatal? There are plenty of laws and cu…
> ask the hypothetical person with a notebook to provide you with a 4K rendering of the scene over the last 30 days.
You just seemlessly transitioned from a machine learning model to literal recording. These aren’t at all the same. In the context of your example, the person on the bench could have easily been wearing a body cam or recording with their cell phone, in certainly something they are capable of doing, so why would I treat it any different? The camera you mentioned could also be a CCTV feed with no DVR, in which case it couldn’t reproduce anything. The AI/person would be what would allow instant pattern recollection, like, “the person usually leaves in a hurry, but not on the weekends with a few exceptions” or “they usually turn lights on around X in the morning, and Y minutes after sunset”
> norms that restrict behavior for other reasons
What’s a concrete example of a tool that has been banned for other reasons. ML models like SD are tools, we usually let people use tools freely unless they can cause great bodily harm, and often even if they can.
> Stability AI has already announced that it is removing users’ ability to request images in a particular artist’s style and further, that future releases of Stable Diffusion will comply with any artist’s requests to remove their images from the training dataset. With that removal, the most outrage-inducing and troublesome output examples disappear from this case, leaving a much more complex and muddled set of facts…
Where is the form to remove my reddit comments from chat gpt training data? Or my blog posts from gpt training data? I have a paragraph on the Internet that someone read and got an idea - I want my royalties. These artists complaints are ridiculous, and are being made by people who don’t understand how things work. If some other person draws a picture in their “style”, no one has to ask permission. That’s not a thing…
Try making a comic book with a character that looks like Mickey Mouse and see how well that goes.
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> Right, but that equally fits a biological NN if you zoom in that close. First of all, we have no idea how biological NNs learn, how they represent information, how they reason etc. Given what we do know, there is no reason to assume any similarity with ANNs on any of those fronts. Just to give one example, we know very well that a single biological neuron encodes significant information and is capable of reasoning…
My initial definition was "like a super-humanly talented artist": this is very different from a human being who also happens to be an artist. Stable Diffusion does only art with text-prompting well, nothing else, and will take a very different "mental" route to creation as a human. But nevertheless it still creates "super-humanly talented" art because it is widely recognized as incredibly good, few artists can do thi…
I very much disagree. Pretty much any halfway decent artist (say, anyone able to at least caricature recognizable people) is able to produce this kind of imitative art, when/if they are aiming for this type of copying. I've seen nothing coming out of SD that I couldn't expect to find on DeviantArt, at least if I commissioned it specifically. Most human artists of course don't do this, since people usually don't like reproductions (apart from posters) or copying others' style. Note as well the huge problem SD has with consistent fine details (especially text, but also often hands and even faces).
Of course, I fully agree on the speed factor (and would add scale/cost) in which SD without a question is far beyond humanity, obviously. That is a meaningful difference that is very likely to affect markets like decorative prints and other low-value art.
Perhaps this basic disagreement (which is of course ultimately subjective, unless someone is going to do a blind taste test) explains the difference of opinions for the rest of the points.