What is a Vector Database?

 

The meteoric rise in Machine Learning in the last few years has led to increasing use of vector embeddings. They are fundamental to many models and approaches, and are a potent tool for applications such as semantic search, similarity search, and anomaly detection.
The unique nature, growing volume, and rising importance of vector embeddings make it necessary to find new methods of storage and retrieval. We need a new kind of database.

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