this post was submitted on 21 Jan 2024
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[–] pavnilschanda@lemmy.world 45 points 10 months ago (10 children)

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?

[–] Even_Adder@lemmy.dbzer0.com 42 points 10 months ago* (last edited 10 months ago) (7 children)

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.

[–] sukhmel@programming.dev 5 points 10 months ago

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.

This would be truly ironic

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