Retrieval-Augmented Generation

Definition

An AI framework that retrieves facts from an external knowledge base to ground large language models (LLMs) on the most accurate, up-to-date information.

Detailed Explanation

Understanding Retrieval-Augmented Generation is crucial for mastering modern AI. It describes an ai framework that retrieves facts from an external knowledge base to ground large language models (llms) on the most accurate, up-to-date information.

Professionals in the field often use Retrieval-Augmented Generation in conjunction with other technologies to build robust solutions.

Why Retrieval-Augmented Generation Matters

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

In Natural Language Processing, this concept helps bridge the gap between human communication and machine understanding.

Last updated: February 2026