Still, it might be interesting information to have access to, as someone running the model? Normally we are reading the output trying to build an intuition for the kinds of patterns it outputs when it's hallucinating vs creating something that happens to align with reality. Adding in this could just help with that even when it isn't always correlated to reality itself.
replyHuge leap there in your conclusion. Looks like you’re hand-waving away the entire phenomenon of emergent properties.
reply> In short: LLM have no concept, or even desire to produce of truth
replyThey do produce true statements most of the time, though.
That's just because true statements are more likely to occur in their training corpus.
replyThe overwhelming majority of true statements isn't in the training corpus due to a combinatorial explosion. What it means that they are more likely to occur there?
replyThe training set is far too small for that to explain it.
replyTry to explain why one shotting works.
Uh, to explain what? You probably read something into what I said while I was being very literal.
replyIf you train an LLM on mostly false statements, it will generate both known and novel falsehoods. Same for truth.
An LLM has no intrinsic concept of true or false, everything is a function of the training set. It just generates statements similar to what it has seen and higher-dimensional analogies of those .