We don't have to prove you wrong, you have to make a case for your position. Your statement was vague and handwavy and could be countered with another vague statement such as "They will add a feature that allows the LLM to better detect hallucinations".

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rmunn 6 hours ago | parent [-]

I phrased it that way because I couldn't remember the term "model collapse" at the time. But that's what I meant: that making the LLMs self-train will lead to model collapse.

There; now the statement is far less vague and handwavy, because I'm making a specific claim that is, AFAIK, well-understood.

Also, you seem to have misunderstood me a little. I didn't mean "prove me wrong", I meant "If I'm missing something, please tell me about it." More of a conversational request than staking a claim in an argument. Many people at HN seem to like to take argumentative, debate-competition stances — but I usually prefer more "Hey, let's discuss this interesting idea, point out mistakes each other is making, and learn together" kind of interactions. That's what I was asking for.

	▲	phoghed 2 hours ago \| parent \| next [-]
		You couldn’t remember the term model collapse because people quit saying it shortly after it was invented in 2023, because it was just cope by people praying for that outcome. Internet will have LLM output, therefore models will train on that output, then kaput. And what happenend next? Models trained on model output on purpose and just keep getting better.
	▲	glimshe 5 hours ago \| parent \| prev [-]
		Fair enough. Well, I guess the answer isn't too different. I believe model collapse is a limitation of the current AI tech but maybe not the future ones. You can see humanity as a huge model that trains itself. What is novel about AI is that we built a machine with some intelligence traits that is free of biological constraints. If we can emulate the aggregate intelligence of a civilization inside a machine, it could improve itself forever but at a much faster pace.