this post was submitted on 16 Sep 2024
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the luddites were happy to use the new tech, but not for less pay and worse working conditions, so they trashed the machines - and history has sadly looked down on them ever since.
https://www.smithsonianmag.com/history/what-the-luddites-really-fought-against-264412/
They are mostly known for having smashed machines and been terrified of technology. That's where the parallel here lies, and what the term has come to mean. Whether they had good reasons back then is irrelevant, the anti-ai bunch don't have now.
I drew out the luddite parallel deliberately: artists likely do not mind AI tools if they are credited and compensated for their work, but they receive no residuals nor credit whenever their work is used so using the tools amount to their theft.
No it doesn't. It's not theft by any reasonable definition of the word. No images are stored, no artwork is used directly to create other artwork. It';s just not, that's not how latent diffusion works. That's one of most commonly repeated pieces of bullshit which has been refuted so often you would have thought it'd have got through a few of your thick skulls by now.
(thanks for the insult, stay classy) so the network training stage was pulled out of thin air then? Huh, I didn't know these models could self-bootstrap themselves out of nothing.
I guess inverting models to do a tracing attack is impossible. Huh.
The insult is justified because you are spouting bollocks. Again. You CANNOT pull any of the training images out of a latent diffusion model, it is simply impossible because they are NOT THERE and if someone says they did they are either lying or spent a fuck of a lot of time and energy on making it look like they did. Either way they are trying to con you. Also the training thing - it's no different to art inspiring human artists except the neural network in the computer is a lot simpler. It's a new medium being used by humans, by artists, to create art. That's all it is.
I don't have the time or energy to explain any more of this to you. Again. Learn how something works before you comment again. Or just shut the fuck up for good. That works too.
(nice ad hominem) Christ. When you reduce a high dimensional object into an embedded space, yes you keep only the first N features, but those N features are the most variable, and the loadings they contain can be used to map back to (a very good) approximation of the source images. It's akin to reverse engineering a very lossy compression to something that (very strongly) resembles the source image (otherwise feature extraction wouldn't be useful), and it's entirely doable.
So you can't pull an image out as it went in? Because it's not stored there? Yeah that's what I FUCKING SAID! Stop spreading bullshit. Just stop it.
(Ah, the joyful tantrum). Educate yourself on how a simple JPEG works and exactly how little features are needed to produce an image that is almost indistinguishable from the source.