A common misconception about large language models like ChatGPT and its older brethren GPT3 and GPT2 is that they are some kind of “super Googles,” or digital versions of a reference librarian, looking up answers to questions from some infinitely large library of facts, or smooshing together pastiches of stories and characters.

They don’t do any of that – at least, they were not explicitly designed to.

A language model like ChatGPT, which is more formally known as a “generative pretrained transformer” (that’s what the G, P and T stand for), takes in the current conversation, forms a probability for all of the words in its vocabulary given that conversation, and then ch...