Mastering Retrieval-Augmented Generation (RAG): Boost Your AI's Knowledge & Accuracy πŸ“š

Discover how Retrieval-Augmented Generation (RAG) enhances large language models by integrating trusted knowledge bases, resulting in more accurate and reliable AI outputs. Perfect for AI enthusiasts and developers!

Mastering Retrieval-Augmented Generation (RAG): Boost Your AI's Knowledge & Accuracy πŸ“š
Krish Naik
97.4K views β€’ Aug 31, 2025
Mastering Retrieval-Augmented Generation (RAG): Boost Your AI's Knowledge & Accuracy πŸ“š

About this video

Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response. Large Language Models (LLMs) are trained on vast volumes of data and use billions of parameters to generate original output for tasks like answering questions, translating languages, and completing sentences. RAG extends the already powerful capabilities of LLMs to specific domains or an organization's internal knowledge base, all without the need to retrain the model. It is a cost-effective approach to improving LLM output so it remains relevant, accurate, and useful in various contexts.
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Agentic AI Langgraph Playlist: https://www.youtube.com/watch?v=vVGXPRjtAJE&list=PLZoTAELRMXVPFd7JdvB-rnTb_5V26NYNO
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Views

97.4K

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3.8K

Duration

20:40

Published

Aug 31, 2025

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