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 Azure 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 Azure Cosmos DB
14:38 - Wrap Up
► Link References:
See how Cosmos DB vector search capabilities work at aka.ms/CosmosVector
Get a free trial at aka.ms/trycosmosdb
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#AzureCosmosDB #GenerativeAI #VectorSearch #chatgpt #CosmosDB