Building Al-Powered Search Apps on Greenplum with pgvector
In the past year, embeddings have gained significant traction as a powerful technique in the fields of Machine Learning and Generative-Al. These embeddings serve as vector representations of data points, capturing their essential characteristics and features.
However, as the demand for efficient semantic search at a large scale increases, there arises a need for a robust platform capable of storing embeddings and enabling seamless search capabilities. Greenplum, a cutting- edge data warehousing solution now equipped with the performance-oriented pgvector. As an open-source extension for PostgreSQL, pgvector empowers customers to store ML embeddings, construct Al applications, and execute high-performing similarity searches.
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