What Is Retrieval Augmented Generation (RAG)?
A technique that supplements a model's prompt with relevant retrieved external data at inference time to improve accuracy and grounding.
Retrieval Augmented Generation (RAG) across 2 exams
Retrieval Augmented Generation (RAG) appears on the following exams. Each defines it in the context candidates are tested on:
- AWS AI Practitioner
- A technique that supplements a model's prompt with relevant retrieved external data at inference time to improve accuracy and grounding.
- AI-901
- A technique that grounds generative model responses by retrieving relevant external data and including it in the prompt context.