ChatGPT Is Great – We’re Just Using It Wrong

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 chooses one of them as the likely next word. Then it does that again, and again, and again, until it stops.