Retrieval Augmented Generation (RAG) In Generative AI
SKU: M2170
4 Lesson
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4 Hours
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Retrieval Augmented Generation (RAG) in Generative AI is an approach that combines large language models with external data retrieval systems to improve response accuracy and relevance. It enables AI systems to fetch real time or domain specific information and generate context aware outputs, supporting applications such as chatbots, knowledge assistants, document search and enterprise AI solutions.
