Photocopy of a photocopy.
It’s always been obvious that this was the inevitable result of them poisoning the Internet (their own source of information for training) with their garbage.
finitebanjo@lemmy.world 23 hours ago
I can tell you exactly why. Feedback loop.
AI produces content, samples that content, approximates that content. The result is more and more levels removed from the original, more and more noise created.
I guarantee OpenAI knows about this, they used to publish studies on it.
leftzero@lemmynsfw.com 15 hours ago
Zos_Kia@lemmynsfw.com 8 hours ago
That is, almost certainly, not the reason. What you’re describing is “model collapse”, a situation which can be triggered in certain extreme laboratory conditions, and only in small models. It may be possible on larger models such as OpenAI’s flagships, but has never been observed or even proved to be feasible. In fact there probably isn’t enough synthetic (ai-generated) data in the world to do that.
If i were to guess why hallucinations are on the rise, i’d say it’s more probably because the new models are fine-tuned for “vibes”, “empathy”, “emotional quotient” and other unquantifiables. This naturally exacerbates their tendency for bullshit.
This is very apparent when you compare ChatGPT (fine-tuned to be a nice and agreeable chat bot) with Claude (fine-tuned to be a performant task executor). You almost never see hallucinations from Claude, it is perfectly able to just respond with “i don’t know”, where ChatGPT would spout 5 paragraphs of imaginary knowledge.
finitebanjo@lemmy.world 1 hour ago
I think comparing a small model’s collapse to a large model’s corruption is a bit of a fallacy. What proof do you have that the two behave the same in response to poisoned data?