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A Project to Poison LLM Crawlers
(rnsaffn.com)
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this post was submitted on 13 Jan 2026
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Doesn't work, but I guess if it makes people feel better I suppose they can waste their resources doing this.
Modern LLMs aren't trained on just whatever raw data can be scraped off the web any more. They're trained with synthetic data that's prepared by other LLMs and carefully crafted and curated. Folks are still thinking ChatGPT 3 is state of the art here.
From what I've heard, the influx of AI data is one of the reasons actual human data is becoming increasingly sought after. AI training AI has the potential to become a sort of digital inbreeding that suffers in areas like originality and other ineffable human qualities that AI still hasn't quite mastered.
I've also heard that this particular approach to poisoning AI is newer and thought to be quite effective, though I can't personally speak to its efficacy.
Faults in replication? That can become cancer for humans. AI as well I guess.
Let's say I believe you. If that's the case, why are AI companies still scraping everything?
Raw materials to inform the LLMs constructing the synthetic data, most likely. If you want it to be up to date on the news, you need to give it that news.
The point is not that the scraping doesn't happen, it's that the data is already being highly processed and filtered before it gets to the LLM training step. There's a ton of "poison" in that data naturally already. Early LLMs like GPT-3 just swallowed the poison and muddled on, but researchers have learned how much better LLMs can be when trained on cleaner data and so they already take steps to clean it up.
Do you have any basis for this assumption, FaceDeer?
Based on your pro-AI-leaning comments in this thread, I don't think people should accept defeatist rhetoric at face value.
A basic Google search for "synthetic data llm training" will give you lots of hits describing how the process goes these days.
Take this as "defeatist" if you wish, as I said it doesn't really matter. In the early days of LLMs when ChatGPT first came out the strategy for training these things was to just dump as much raw data onto them as possible and hope quantity allowed the LLM to figure something out from it, but since then it's been learned that quality is better than quantity and so training data is far more carefully curated these days. Not because there's "poison" in it, just because it results in better LLMs. Filtering out poison will happen as a side effect.
It's like trying to contaminate a city's water supply by peeing in the river upstream of the water treatment plant drawing from it. The water treatment plant is already dealing with all sorts of contaminants anyway.