Best practices for GenAI vector data queries

Discover techniques for improving application performance and delivering relevant AI-driven insights

Webinar Scaling generative AI applications with foundational models (FMs) often presents challenges, particularly when working with vector data.

To help businesses learn how to navigate these complexities, AWS is hosting a webinar led by Jonathan Katz, Principal Product Manager for Amazon RDS, on November 13th at 8am PT/11am ET.

Katz will explore how Amazon Aurora PostgreSQL, in combination with the Amazon Bedrock RAG (Retrieval Augmented Generation) capabilities, can streamline the process of querying vector data. This event will cover best practices for optimizing SQL queries, tuning parameters, and using vector-optimized indexing to accelerate AI/ML performance. Attendees will learn how to store and retrieve vector data efficiently, without writing custom code.

For businesses looking to leverage private data stored in Amazon Aurora, these techniques might prove crucial for improving performance and delivering relevant AI-driven insights.

Register for the webinar today to gain insights that will optimize your AI applications and improve user experience.

Sponsored by AWS.