The use of categorical data and metadata in search operations allows for limiting search results to specific categories such as projects or genres. This approach extends beyond simple examples like project-based searches to more complex applications. Leveraging metadata enables restricting search results based on criteria like time span or specific categories, enhancing the search logic. Namespaces play a crucial role in multi-tenant scenarios, particularly in multi-tenant RAG operations, where customers managing multiple clients benefit from this feature.
Daniel & Chris explore the advantages of vector databases with Roie Schwaber-Cohen of Pinecone. Roie starts with a very lucid explanation of why you need a vector database in your machine learning pipeline, and then goes on to discuss Pinecone’s vector database, designed to facilitate efficient storage, retrieval, and management of vector data.
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