As more businesses develop and deploy AI-driven applications, they face a strategic decision: What vector database do we use?
Here’s why. Vectors, which are unique strings of numbers calculated to represent unstructured data, let companies add context to generic large language models (LLMs). Vectors are critical for uses such as making product recommendations or showing correlations among data or objects. For many businesses, vectors are an entirely new data type to manage. AI development teams must determine the best way to store, administer, and retrieve vector data.
This article by John Foley, editor of the Cloud Database Report, details five advantages of using an integrated vector database for AI development.
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