Vector Databases in RAG - Day 2

Vector databases store data as numerical vectors optimized for similarity searches, enabling large language models (LLMs) to retrieve contextually relevant information from private datasets like PDFs. This matters because vector databases allow LLMs to understand and respond accurately to queries based on the semantic meaning of data rather than exact matches, enhancing the effectiveness of retrieval-augmented generation systems.

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