Few-Shot Learning

Definition

Providing a model with a small number of examples to help it understand the task.

Detailed Explanation

In the world of Training, Few-Shot Learning is defined as providing a model with a small number of examples to help it understand the task.

At its core, Few-Shot Learning solves a specific problem in the AI landscape. Unlike traditional approaches, it leverages advanced algorithms to process data more efficiently.

Why Few-Shot Learning Matters

For developers and data scientists, mastering Few-Shot Learning unlocks new capabilities in model design. It is particularly relevant for optimizing performance and reducing costs.

Last updated: February 2026