Introduction to Vector Search on Databricks

Explore the integration of vector search technologies within the Databricks Data Intelligence platform in this 38-minute talk by Akhil Gupta, VP of Engineering for AI Systems at Databricks. Dive into the fundamentals of vector search, including embeddings and nearest neighbor search algorithms, and learn how they enhance search capabilities and retrieval efficiency for AI-powered applications. Discover the architecture behind vector search and its implementation in Databricks for handling large-scale datasets. Gain practical insights through demonstrations on setting up vector search, including indexing and querying processes. Learn optimization techniques, advanced configuration tips, and best practices for improving search performance. Examine real-world case studies that showcase the impact of vector search on business intelligence and data-driven decision-making. By the end of this session, understand how leveraging vector search on Databricks can transform data retrieval processes into more efficient, scalable, and precise operations.

Introduction to Vector Search on Databricks