>they will do almost anything if they are convinced it is justified - or if they are playing a "game" where there is no goal but to win just a small caution on

>they will do almost anything if they are convinced it is justified - or if they are playing a "game" where there is no goal but to win just a small caution on this anthropomorphism - it implies there's some high-order 'thinking' behind it. in reality, it's probably healthier to see LLMs as a combination of symbolic logic reasoning steps paired with probabilistic token predictor generating the proponents and operators in that chain, all trained by humans on different large data sets to be 'goal-oriented' implies that there's the capacity to be anything else and I don't think that's how LLMs operate at all. I think they only know how to operate within their design parameters and much of that design is simply much further upstream during the training and post-training processes. that opacity makes it feel like 'intelligence' when you're interacting with it as a downstream product because you'll see an agent act in a way that you didn't command - but that's simply a result of your not being shown all the antecedent mappings and architectural design something something indistinguishable from magic as that one guy said