Someone should make a community to freely distribute examples of data poisoning people can randomly put in their social media posts/images to sabotage AI
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Na, for it to be effective it needs to be wide spread, but if its wide spread then it can be filtered out of the training material.
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Na, for it to be effective it needs to be wide spread, but if its wide spread then it can be filtered out of the training material.
I've read in papers that you can poison datasets with a very small percentage of the data, if done cleverly. I can fish up the source if you want (but it might take me some time).
edit: here it is.
We conduct the largest pretraining poisoning experiments to date, pretraining models from 600M to 13B parameters on chinchilla-optimal datasets (6B to 260B tokens). We find that 250 poisoned documents similarly compromise models across all model and dataset sizes (...)
Emphasis mine. All it takes is 250 poisoned documents.
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Lol, good luck with that.
The more poisoning you attempt, the more effective anti-poisoning becomes.
AILLM is here, stop trying to put the genie back in the bottle. All we can do is figure out how to use it and prevent misuse. -
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People still have sm accounts?
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Na, for it to be effective it needs to be wide spread, but if its wide spread then it can be filtered out of the training material.
There's a new technique that uses the AIs "thinking" tags to get it to do things that are otherwise banned by policy.
I'll have to find the article again. But due to the way LLMs work, they can't defend against this sort of attack.
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People still have sm accounts?
You have one on lemmy.world
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That assumes that AI companies are negatively impacted by the quality of their product. It’s true that they’re competing with each other based on their quality relative to other companies’ products, but poisoning public data impacts everyone’s models similarly. Setting aside competition and looking at the success of the AI sector as a whole, I think it’s more dependent on marketing and hype than on real performance... and if that’s the case, then poisoning public data doesn’t hurt anyone except the people being forced to use it.
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A centralized database of content for AI scraping agents to be trained to exclude?
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I think there's a subreddit for that. /r/PoisonAI or something. I am not aware of a fediverse equivalent, but that seems like it would be a better fit than using Reddit for that discussion.
Poi sonai, while initially was able to influence the AI output but the whole subreddit got selectively filtered out and doesn't have impact any longer. It's still good place to discuss the topic though.
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Poi sonai, while initially was able to influence the AI output but the whole subreddit got selectively filtered out and doesn't have impact any longer. It's still good place to discuss the topic though.
I misunderstood the purpose of that community. I figured it was just for discussing how to poison AI models. But actually visiting it, I see it is primarily for posting gibberish in the hopes that AI models would scrape the sub and treat it all as genuine content. As you say, that does not seem like it would have much of any impact on actually poisoning AI models because basically every scraper is going to know to avoid a community called "poison AI".
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There's a new technique that uses the AIs "thinking" tags to get it to do things that are otherwise banned by policy.
I'll have to find the article again. But due to the way LLMs work, they can't defend against this sort of attack.
And here's some explanations of how various attacks work.
https://github.com/nukIeer/AI-Prompt-Injection-Cheatsheet
https://developer.nvidia.com/blog/how-hackers-exploit-ais-problem-solving-instincts/
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That assumes that AI companies are negatively impacted by the quality of their product. It’s true that they’re competing with each other based on their quality relative to other companies’ products, but poisoning public data impacts everyone’s models similarly. Setting aside competition and looking at the success of the AI sector as a whole, I think it’s more dependent on marketing and hype than on real performance... and if that’s the case, then poisoning public data doesn’t hurt anyone except the people being forced to use it.
Who says the objective is to impact AI companies negatively?
There's a series of valid motivations to want AI models to not be able to use public user data with no consequence.
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Lol, good luck with that.
The more poisoning you attempt, the more effective anti-poisoning becomes.
AILLM is here, stop trying to put the genie back in the bottle. All we can do is figure out how to use it and prevent misuse.I don't want to put it back in the bottle. I just feel like taking massive public user data for free should not be devoid of consequence.
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