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What is the database behind ChatGPT?

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Manage episode 404882490 series 1320201
Content provided by Jeremy Chapman and Microsoft Mechanics. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jeremy Chapman and Microsoft Mechanics or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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

► Unfamiliar with Microsoft Mechanics?

As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft.

• Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries

• Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog

• Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast

► Keep getting this insider knowledge, join us on social:

• Follow us on Twitter: https://twitter.com/MSFTMechanics

• Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/

• Enjoy us on Instagram: https://www.instagram.com/msftmechanics/

• Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

  continue reading

240 episodes

Artwork
iconShare
 
Manage episode 404882490 series 1320201
Content provided by Jeremy Chapman and Microsoft Mechanics. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jeremy Chapman and Microsoft Mechanics or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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

► Unfamiliar with Microsoft Mechanics?

As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft.

• Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries

• Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog

• Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast

► Keep getting this insider knowledge, join us on social:

• Follow us on Twitter: https://twitter.com/MSFTMechanics

• Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/

• Enjoy us on Instagram: https://www.instagram.com/msftmechanics/

• Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

  continue reading

240 episodes

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