Vector Search enhances machine learning models by allowing similarity comparisons of embeddings, which are mathematical representations of high dimensional data.
As a capability of Astra DB, Vector Search supports various Large Language Models (LLM). Since these LLMs are stateless, they rely on a vector database like Astra DB to store their embeddings. You can expedite your vector-based similarity searches by using Serverless Cassandra with Vector Search, making it easier to develop your LLM-powered applications.
Here are some of the top reasons to use our vector search:
Discover connections by comparing similarities within vast collections of documents
Match product recommendations, find similar images, and more
Seamless integration with LLMs
Scale effortlessly to handle large volumes of embeddings