What Is Retrieval-Augmented Generation (RAG)? | Large Language Model | Simplilearn

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In this video, we will explore the groundbreaking concept of Retrieval Augmented Generation (RAG), a revolutionary approach at the forefront of natural language processing (NLP). RAG represents a significant leap forward in text generation methodologies, seamlessly blending retrieval mechanisms with generative models to unlock new possibilities in AI-driven communication. Throughout this session, we will unravel the intricate workings of RAG, diving deep into its architecture, principles, and practical applications. We'll embark on a journey to understand how retrievers, acting as gateways to vast knowledge repositories, empower generative models to produce contextually rich and factually accurate text outputs. Join us as we navigate the landscape of RAG, exploring its potential to revolutionize various NLP tasks, from question answering to content generation. By the end of this video, you'll have a comprehensive understanding of RAG's transformative impact on natural language understanding and generation. So, without further ado, let's dive into the world of Retrieval Augmented Generation.

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