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Point taken, I was possibly overly curt in my response, leading to it being ambiguous, both re when the loss function is being minimised and that it is a stocha
by greggoB 13d ago
Point taken, I was possibly overly curt in my response, leading to it being ambiguous, both re when the loss function is being minimised and that it is a stochastic process.
So to OPs question: I guess LLMs do have an "idea" of what is best (conditioned on minimising a loss function during training), however they may not always output that (because stochasticity), which maybe represents a degree of uncertainty in that "idea"?
- eru 13d agoMy point is that when you asked them to 'judge' two texts, they are just going to output the tokens that have the highest probability (or a sample from that distribution). But depending on their training data, these tokens might say 'correct horse battery staple', and not necessarily 'text A is better' or 'text B is better'. Even if text A would have been more likely to be produced by the LLM.