It comes about from machine learning algorithms that could pick up on patterns from a small number of examples. Few shot means only a handful of examples to recognize something. One shot means only a single example. And zero shot means no examples. Of course, you have to indicate what you want somehow, but in the case of an LLM that's the prompt. Once LLMs were trained for instruction following, you didn't have to give any examples, you could just give a prompt describing what you want, and that was a zero-shot.
I'm complaining about the LLM field co-opting a term that was already used in daily vernacular. Imagine if people in the LLM field made it so that saying the LLM made a "final answer" means that it got stuck in a loop. Now, whenever someone says an LLM gave a "final answer" we have to divine if they meant it is in a loop or gave the right answer after working through a few intermittent ones by itself.
Choosing to call it "X-shot" was a dumb move. And now we're stuck with it. No two ways about it.
Have you tried applying L'Hôpital's Rule?
Minus one shotting: you have to make one attempt for there to have been no attempt, and two attempts for there to have been one attempt.
- Wayne Gretzky
- altmanaltmanZero shot: Knowing you had a shot but choosing not to.
Minus one shot: Not even realizing there was a shot.