"The problem with LLMs is that you eventually run out of other people's work to steal"
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"The problem with LLMs is that you eventually run out of other people's work to steal"
@pikesley see recursive pollution and model collapse. Eg https://berryvilleiml.com/2026/01/10/recursive-pollution-and-model-collapse-are-not-the-same/
But also see this paper arguing that collapse does not happen if you accumulate training data rather than replace old data with new data; instead, it converges towards a limited level of errors.
https://arxiv.org/pdf/2404.01413 -
This has breached containment spectacularly and I'm now having it explained back to me
@pikesley yes, it's also known as the "training data harvester" dark pattern.
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Using LLMs is the intellectual equivalent of sawing the branch you're sitting on.
@FediThing @pikesley I use the expression "poisoning the well of knowledge".
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This has breached containment spectacularly and I'm now having it explained back to me
Attracting a lot of r/iamverysmart types who clearly do not know the context of the quote
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Attracting a lot of r/iamverysmart types who clearly do not know the context of the quote
@pikesley I live in fear of the day that I miss some context, or reply to something where I didn't actually know the context and make myself look like an arse. How do these people sleep at night?!
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@pikesley [John Peel voice]: Coming up, it's Slop Ouroboros playing live in the studio. You won't find their new EP The RAM Wafers Are All Mine in shops anywhere...
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This has breached containment spectacularly and I'm now having it explained back to me
@pikesley AIsplaining?
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@pikesley [John Peel voice]: Coming up, it's Slop Ouroboros playing live in the studio. You won't find their new EP The RAM Wafers Are All Mine in shops anywhere...
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"The problem with LLMs is that you eventually run out of other people's work to steal"
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J Jürgen Hubert shared this topic
