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.
(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.
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.