Take advantage of Azure Cosmos DB for your AI-driven applications. Seamlessly integrate with large language models like ChatGPT, for real-time operational efficiency and limitless scalability. With its built-in vector search engine and multi-model support, Azure Cosmos DB for MongoDB vCore optimizes for just-in-time data retrieval, so you can build cutting-edge solutions at any scale.

Kirill Gavrylyuk, General Manager for the Azure Cosmos DB team, joins Jeremy Chapman to share how you can increase performance and cost-effectiveness, whether managing millions of users globally or building smaller-scale apps.

► QUICK LINKS:

00:00 - Get your database ready for AI with Azure Cosmos DB 02:33 - Solve for real-time data access requirements 03:39 - Automatic scaling 05:35 - How Azure CosmosDB works for copilot-style apps 06:38 - App using vectorized data 07:24 - Jupyter notebook demo 09:19 - Vector indexing and search in Cosmos DB 10:14 - Building a small copilot-style app 12:10 - Run smaller apps serverless 12:35 - Set maximum throughput thresholds 13:39 - Auto scale using Cosmos DB 14:38 - Wrap Up

► Link References:

See how Cosmos DB vector search capabilities work at https://aka.ms/CosmosVector

Get a free trial at https://aka.ms/trycosmosdb

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