The issues of copyright infringement with AI are real though. Much of today’s AI is directly copying subregions of training data, and can sometimes be prompted to reproduce images from the training data verbatim. Humans don’t do that unintentionally, even though sometimes they do mean to steal from others. Suggesting that art school is the same thing as a training dataset is a bit hyperbolic.
And, much like with our brains, when it happens it doesn’t actually exactly reproduce parts of the source image. But, you have actively pay attention to notice what happened. It makes an image that is overly similar conceptually. To our brains that feels the same. So, that’s enough to convince someone at a glance that it is the same.
But, if you look at an overfit result of “The Beatles Abbey Road album cover”, you’ll see things like: Band members are crossing the road, but they are all variations of Ringo. Vehicles from that era are in the background, but they are in a different arrangement and none of them are directly from the source. The Band members are wearing suits, but they are the wrong style and color. There are the wrong number of stripes on the road. It’s not the same as a highly skilled human drawing an iconic image from memory. But, it sure is darn similar.
And, besides all that, everyone working in the tech considers the overfitting of iconic images to be a failure case that is being actively addressed. It won’t be long before it stops happening entirely.
In the meantime, I’d challenge anyone to try to make an overfit result that significantly reproduces a specific work of every promoter’s favorite, Greg Rutkowski, using Dall-e, Midjourney or the Stable Diffusion models released directly by Stability AI. Greg’s pixels aren’t in the model file to be copied. Only a conceptual impression of his style.
Not really, though that is another legitimate issue.
I was talking about 1) the fundamental training and inference process, which remembers pixels, not concepts or techniques. Today’s AI learns to create imagery in a fundamentally different way than people do. And 2) image generation AI based on text prompts like Stable Diffusion can easily be asked to reproduce training data by having a prompt that is narrow and specific enough. This is not over fitting, it’s a function of the fact that some inputs are quite unique, and you can use the prompt to focus on that uniqueness.
I’d like to see examples of using SD to copy some specific piece of art that hasn’t been plastered millions of times across the internet. Sure, you can get a decent Mona Lisa knock off. Maybe even a strong impression of the Bloodbourne game cover art marketing material. But, reproducing a specific painting from Rutkowski would be quite a surprise to me.
Here are the examples you requested: https://techcrunch.com/2022/12/13/image-generating-ai-can-co...
Yes the training process looks at pixels, because that’s all it has. That’s the point. Humans don’t look at pixels, they learn ideas. It’s not in the least bit surprising that AI models shown a bunch of examples sometimes replicate their example inputs, examples are all they have, and they are built specifically to reproduce images similar to what they see, I’m not sure why you consider that idea “loaded”.
Read the paper. What I found is that a random sampling of the database naturally found a small subset of images that are highly duplicated in the database. Researchers we able to derive methods to produce results that give strong impressions of images such as: a map of the United States, Van Gogh's Starry Night, and the cover of Bloodborne :P with some models and not at all with others. The researchers caution against extrapolating from their results.
> We speculate that replication behavior in Stable Diffusion arises from a complex interaction of factors, which include that it is text (rather than class) conditioned, it has a highly skewed distribution of image repetitions in the training set, and the number of gradient updates during training is large enough to overfit on a subset of the data.
Is this sarcasm? The history of art is full of artists who created their own, signature, unique and original styles. Take, I don't know, Vincent Van Gogh, for an example, who had a very distinctive style, so distinctive that he didn't even start a school of art probably because it would have been too blatant to copy him. There was nobody before him who painted like him. Who did he "copy" then?
Hell, when humans first made art, back in the time we lived in caves, their art styles, which are still absolutely unique, had nothing to copy from, simply because there weren't any artists before them (by definition: "when humans first made art").
So, yes, humans learn how to create art from each other, but they also created the whole idea of art entirely on their own, and they can take what they have learned form others and turn it into something completely new, never before seen.
Now, you show me an original art style created by an "AI". Show me AI art that isn't only borrowing and copying, but goes beyond that, like human artists can.