General AI
RAG: Enhancing AI with External Information Retrieval
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Why it matters
- →RAG allows AI to access and utilize up-to-date information.
- →It reduces the risk of AI generating unsupported or incorrect answers.
- →Enhances AI's ability to handle specialized queries by integrating external data.
Retrieval-Augmented Generation (RAG) is a method that enables AI systems to answer questions using information not included in their original training data. By retrieving relevant data from external sources like documents, databases, or knowledge bases, RAG provides this information as context to the AI model. This approach helps AI systems incorporate specialized or current information, reducing the likelihood of unsupported or fabricated answers.
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