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Comment on Dola Decoding by Contrasting Layers Improves Factuality in Large Language Modelsparent

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Orwellian? Maybe, but in the same way we teach our children what is true and how to determine what is true.

We want to raise these pseudo-humans to be useful upstanding members of society. Knowing fact from opinion, knowing right from wrong, knowing what is real and what is imagination, are important for any intelligence. Otherwise our silicon-children will grow up to be dumb, harmful, or both, while being trillions in number.

And that goes back to the question I asked above: are you talking about "what is real" from a philosophical "realism" point of view, or from a philosophical "nominalism" point of view?

Realism posits that objects have intrinsic meaning that we apprehend through attention.

Nominalism posits that we cannot apprehend reality directly, but only through our minds and through language. That we only have a second-order experience of reality. Therefore, all language only has meaning because of consensus, so if we change the consensus of meaning around language, we are actually changing reality because reality is mediated through language.

These are obviously very compressed definitions of these views, but the question remains.

This conversation about AI "hallucinations" seem to point at this question. "We want AI to say true things." True to what? True to reality? Or true to language? When we ask AI a question, AI only knows how to answer the question using grammar that is probabilistically the most likely. That has no tie to "reality", but as soon as you start asking "well then what is reality that we want to map AI to?" the question gets quite slippery.

My contention is that AI, as its responses are curated by people, will only reflect the idiosyncratic worldviews of those doing the pruning.

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