E3: Build AI apps with Azure SQL Database Hyperscale

Bob and Anna demo how to build AI-style retrieval features on Azure SQL Database Hyperscale using vector embeddings and vector indexes, focusing on practical developer capabilities for semantic search and retrieval scenarios.

Overview

The video demonstrates using Azure SQL Database Hyperscale to support AI application patterns that rely on semantic search and retrieval.

What the session covers

• AI in Azure SQL (intro)
• AI and analytics integrations
• Developer capabilities and tools
• Database engine features relevant to AI-style workloads
• A hands-on demo using vector embeddings and vector indexes
• Key takeaways and a mention of SQL AI certification

Key technical concepts highlighted

• Vector embeddings stored/used for semantic similarity scenarios
• Vector indexes to improve efficiency for semantic search and retrieval
• Semantic search and retrieval patterns for AI apps (retrieval-oriented application design)

Links shared in the video description

• Repo: https://aka.ms/azuresqlfoundations
• Developer guide: https://aka.ms/SQLDBdevguide
• Free trial: https://aka.ms/freesqldb