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Retrieved on: 2024-12-31 00:01:18
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Summary
The article explains Retrieval-Augmented Generation (RAG) in AI, highlighting its role in improving large language models by integrating external data sources for more accurate and relevant outputs. It stresses RAG's importance in NLP and AI development, touching on how it involves machine learning techniques like vector databases and ranking for enhanced information retrieval, all while connecting to tags such as generative AI and prompt engineering.
Article found on: techbullion.com
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