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this post was submitted on 21 Jan 2024
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Apparently people who specialize in AI/ML have a very hard time trying to replicate the desired results when training models with 'poisoned' data. Is that true?
I've only heard that running images through a VAE just once seems to break the Nightshade effect, but no one's really published anything yet.
You can finetune models on known bad and incoherent images to help it to output better images if the trained embedding is used in the negative prompt. So there's a chance that making a lot of purposefully bad data could actually make models better by helping the model recognize bad output and avoid it.
VAE?
Think they mean a Variational AutoEncoder
Variable. But no running it through that will not break any effect
This would be truly ironic
If users have verry much control and we can coordinate then you could gaslight the AI into a screwed up alternate reality
Until they come with some preprocessing step, or some better feature extractors etc. This is an arms race like there are many of
The thing is data poisoning is a arms race that the Ai side will win with ease. You can either solve it with pre processing or filtering. All it does is make the images look worse. I can't think of a way that you can poison data that doesn't take more effort to unpoison than to poison.