Raw LLM Responses

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I'm an artist and pursuing masters in CS. Just to be clear, I'm on your side, and I stand by most of your points, but I think it's also important to be clear about what data poisoning is: it's a retardant, not a medicine. Training on poisoned dataset is already a research area with concrete results. Already in my university I've seen a paper attempting to do just that (I can't name it lest I dox myself). It's not tested on Nightshade (and I dont have enough knowledge to tell whether it will be effective against it), but the premise is the same: training on poisoned data that looks normal to humans but appears as different objects to a diffusion model. It doesn't even need a clean sample, it claims it's effective even with all poisoned samples. The only surefire way to stop these products from catching on is to make it illegal; AI companies can (and do) stash old data from the web and can simply retrain their models once Nightshade (or older versions of it) becomes ineffective.
youtube Viral AI Reaction 2025-04-03T07:3…
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policynone
Emotionapproval
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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