If the output can't be trusted, and you use another llm whose output can't be trusted to check the untrusted output of the first llm, then you're back where you started.

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duncangh 2 hours ago | parent | next [-]

Yeah this seems to me similar to how the mortgage backed security risk concentration occurred leading up to the global financial crisis. Whereby the risk from exposure to low grade / risky single mortgages was eliminated via diversification but the diversification was simply packaging all of the risky MBS’s together and in no way diversified or de-risked the entire portfolio

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cromka an hour ago | parent | next [-]

I don't see it. To me it's like having e.g. 3 drunk PhDs arguing between each other to settle on truthful answers to questions.

	▲	DrewADesign 4 minutes ago \| parent [-]
		But PhDs are PhDs because they’d look it up in an authoritative source, or actually find out through research and experimentation. The whole point is that facts aren’t a matter of opinion. The only people that argue over documented, findable facts are idiots that nobody should listen to.

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Terr_ 2 hours ago | parent | prev [-]

I'm hoping that the Big Horrible Realization comes sooner rather than later, when we have less collective damage and pain riding on it. (Plus I'd feel personally vindicated.)

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daishi55 2 hours ago | parent | prev [-]

Not really. Take hallucinations for example. If they are 1 in 100 (actually they are much rarer, but for the sake of argument), then the chances that 2 LLMs or even just 2 runs of the same LLM have the same hallucination is, well, a lot less than 1 in 100.

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Terr_ 2 hours ago | parent | next [-]

That rests on a false-assumption that the errors are statistically independent events, and have nothing to do with the shared nature of the judges.

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daishi55 an hour ago | parent [-]

Are there any reproducible hallucinations on any of the currently available OAI/Anthropic models? I’m not aware of any.

And even if they are related - if Opus 4.8 always has a 1:100 chance of a specific hallucination - then running the same model twice does indeed dramatically reduce the odds of an error in the final output.

	▲	Terr_ an hour ago \| parent [-]
		If simply running things thrice-over was enough to stop "hallucinations" (and not incur other problems) we wouldn't be here talking about it today, it'd have been "solved" months or years ago.

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2 hours ago | parent | prev [-]

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