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.
In this talk, we’ll learn how to leverage its powerful vector similarity search capabilities within Greenplum and harness its potential in combination with OpenAl models and finally discover how this integration can revolutionize the development of Image Search applications and domain-specific Chatbots.