Earlier quoted context omitted.
You had the right understanding in your first comment, but what was missing was the fine tuning. You are right that there aren't many documents on the web that are structured that way, so the raw model wouldn't be very effective on predicting the next token. But since we know that it will complete a command when structured it cleverly, all we had to do to fine tune it is synthesize (generate) a bazillion examples of…
You’ve expressed this very well - Thank you. I get that the fine tuning is done over documents which are generated to encourage the dialog format. What I’m intrigued by is the way prompters choose to frame those documents. Because that is a choice . It’s a manufactured training set. Using the ‘you are an ai chatbot’ style of prompting, in all the samples we generate and give to the model, text attributed to {:system}…
I think it’s a little game or reward for the writers at some level. As in, “I am teaching this artificial entity by talking to it as if is it a human” vs “I am writing general rules in some markup dialect for a computer program”.
Anthropomorphizing leads to emotional involvement, attachment, heightened attention and effort put into the interaction from both the writers and users.