<ul><li>Retrieval Augmented Generation (RAG) is a concept that involves creating a specialized database for AI to generate output from a carefully curated dataset.</li><li>RAG aims to reduce AI 'hallucinations' and increase the reliability of Generative AI.</li><li>By utilizing RAG, companies can optimize productivity by building chatbots that respond based on specific data sources like HR documents or standard operating procedures.</li><li>While RAG reduces 'hallucinations,' it may also contribute to polarization by providing personalized and potentially biased information to users.</li></ul>

Generative AI + RAG Could Boost Productivity and Political Polarization

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