Zero-Shot

Overview

Zero-shot means asking a model to do something it was not trained on and giving it no examples - only a description of the task. It solves the problem that every supervised approach needs labelled data for each new task, which does not scale to tasks nobody has collected data for. It exists as the capability that made general-purpose models useful, and as the upper bound that few-shot prompting is measured against.

Technology Graph

How Zero-Shot connects to the rest of the stack.

Alternatives

• Few-Shot Learning technique

  An alternative to Zero-Shot · source

Comparisons

Side-by-side breakdowns with the alternatives above.

• Few-Shot Learning vs Zero-Shot