Unlocking Data with Generative AI and RAG

Preface

In the rapidly evolving landscape of artificial intelligence (AI), retrieval-augmented generation (RAG) has emerged as a groundbreaking technology that is transforming the way we interact with and leverage AI systems. RAG combines the strengths of information retrieval and generative AI models to create powerful applications that can access and utilize vast amounts of data to generate highly accurate, contextually relevant, and informative responses.

As AI continues to permeate various industries and domains, understanding and mastering RAG has become increasingly crucial for developers, researchers, and businesses alike. RAG enables AI systems to go beyond the limitations of their training data and access up-to-date and domain-specific ...