AI Quiz (2/365): AI Embeddings Database
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Vector databases are specialized database systems designed to efficiently store and manage vector embeddings. These embeddings are high-dimensional vectors that represent data in a way that captures its essential aspects, often used in machine learning and AI applications to handle tasks like similarity search and recommendation systems.
Vector databases are particularly useful for applications that need to perform fast and scalable similarity searches over large datasets. For instance, in image or text retrieval systems, vector databases can quickly find items that are similar to a query by measuring the distances between their vector representations.
Popular vector databases as of this writing are: Pinecone, PostgreSQL(pgvector embedding), etc.
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