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> Once there are millions of images, you end up with just tiny blobs of pixels being copied from many different images. This is not how these neural nets work.

> Once there are millions of images, you end up with just tiny blobs of pixels being copied from many different images. This is not how these neural nets work. They don't copy pixels from anywhere. They learn features. The features represented internally are generally not easy to interpret to humans, but for sake of illustration, there could be an artificial neuron that fires when a subject should have blue eyes. Having a lot of blue eyes in the training data would help this neuron learn better when to fire (based on the values of other neurons, which may in turn represent other features). For example, it may learn to place more importance on an input that represents pale skin or Nordic origin. It can learn concepts like cars have wheels, and wheels are round, etc. And then when you ask it to draw a car, it composes one from the concepts it learned. Some parts of the network will deal with the fine details that more directly influence pixels, but these aren't copying pixels from any image either. They're weighing a bunch of factors (eg is this pixel part of the iris and did the network decide to make a person with blue eyes?) and choosing pixel colors based on those factors.

optymizer 3y ago
Thank you for the explanation. Let me explain my position in similar terms. I'm not replicating an image, I'm "using my brain to build a network of neurons that map electrical impulses from the optical nerve excited by wavelengths projected onto my retina in order to send other electrical signals to actuator tissues". The complexity of the process is irrelevant imo. We can treat it as a black box and look at the inputs and outputs. If the images in the database didn't exist, it wouldn't know what to draw, and those images are copyrighted. Everyone's welcome to take a camera, run around the world and label every object for the neural net to learn, like a human does, but model authors didn't do that because using copyrighted images for free is much easier.
- nearbuy 3y ago
  You're right that if you're replicating an existing copyright image, the process doesn't matter. Legally, if you lived in a cave your whole life and never saw any art and by amazing coincidence you just happened to paint and sell the exact same painting as some other artist, you'd be violating their copyright. Independent creation doesn't protect you. On the other hand, under current copyright law, if Stable Diffusion generates an original image that doesn't look like a copy of any existing image, it's clear the new image doesn't violate any artist's copyright. The debate is whether you can use copyright images/text to train an AI. Stable Diffusion is of course trained on millions of photos of the real world, in addition to images made by artists. Of course, humans artists also see and digest both the real world and images by other artists and both influence their output. That's why you get trends like impressionism.

optymizer 3y ago

Thank you for the explanation. Let me explain my position in similar terms. I'm not replicating an image, I'm "using my brain to build a network of neurons that map electrical impulses from the optical nerve excited by wavelengths projected onto my retina in order to send other electrical signals to actuator tissues". The complexity of the process is irrelevant imo. We can treat it as a black box and look at the inputs and outputs. If the images in the database didn't exist, it wouldn't know what to draw, and those images are copyrighted. Everyone's welcome to take a camera, run around the world and label every object for the neural net to learn, like a human does, but model authors didn't do that because using copyrighted images for free is much easier.

nearbuy 3y ago
You're right that if you're replicating an existing copyright image, the process doesn't matter. Legally, if you lived in a cave your whole life and never saw any art and by amazing coincidence you just happened to paint and sell the exact same painting as some other artist, you'd be violating their copyright. Independent creation doesn't protect you. On the other hand, under current copyright law, if Stable Diffusion generates an original image that doesn't look like a copy of any existing image, it's clear the new image doesn't violate any artist's copyright. The debate is whether you can use copyright images/text to train an AI. Stable Diffusion is of course trained on millions of photos of the real world, in addition to images made by artists. Of course, humans artists also see and digest both the real world and images by other artists and both influence their output. That's why you get trends like impressionism.