Name: Operationalizing Vector Databases on Postgres
Start: 2024-04-30T18:00:00-07:00
End: 2024-04-30T21:00:00-07:00
Location: Computer History Museum

**Come join us for an evening of Postgres and AI at the Computer History Museum with food and beverages sponsored by Tembo!**

**Abstract**

Developers are increasingly generating embeddings from their operational data using Postgres, facilitated by tools like Pgvector which enable searching these embeddings. However, the challenge of building AI applications extends beyond storing and searching embeddings; there is a significant effort involved in generating and maintaining these embeddings to create a fully functional AI application.

In this talk, we will discuss the comprehensive workflow required to operationalize AI applications on Postgres. We'll explore the process beyond storing and searching embeddings, discussing advanced topics such as retrieval augmented generation and vector search. Additionally, we will address the nuances of updating embeddings as the source data evolves and lessons learned in building machine learning feature stores, highlighting how these lessons apply to developing AI applications.

Mason Sharp

Silicon Valley Postgres

PostgresWorld

Command Prompt

Redgate

Technology

Open Source

Database Professionals

Software Development

PostgreSQL

Business Intelligence

Web Development

Hadoop

Big Data

Data Analytics

Predictive Analytics

Computer Programming

Data Science

Adam is a founding engineer at [Tembo.io](http://tembo.io/) and leads the Tembo Stacks project with deep interest in running machine learning workloads on Postgres. As a part of his work, he works with and has authored a number of Postgres extensions like pgmq, pg_later and pg_vectorize. Previously, he worked as a machine learning engineer at Shipt and C.H. Robinson. Adam is also a US Army Intelligence veteran.

Silicon Valley Postgres

Operationalizing Vector Databases on Postgres

Silicon Valley Postgres

Details

Sponsors

Members are also interested in