Microsoft Mechanics Podcast Microsoft Mechanics
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Made for tech enthusiasts and IT professionals. Expanded coverage of your favorite technologies across Microsoft; including Office, Azure, Windows and Data Platforms. We'll even bring you broader topics such as device innovation with Surface, machine learning, and predictive analytics.
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Vector Search using 95% Less Compute | DiskANN with Azure Cosmos DB
Ensure high-accuracy, efficient vector search at massive scale with Azure Cosmos DB. Leveraging Microsoft’s DiskANN, more IO traffic moves to disk to maximize storage capacity and enable high-speed similarity searches across all data, reducing memory dependency. This technology, powering global services like Microsoft 365, is now integrated into Azure Cosmos DB, enabling developers to build scalable, high-performance applications with built-in vector search, real-time fraud detection, and robust multi-tenancy support.
Join Kirill Gavrylyuk, VP for Azure Cosmos DB, as he shares how Azure Cosmos DB with DiskANN offers unparalleled speed, efficiency, and accuracy, making it the ideal solution for modern AI-driven applications.
► QUICK LINKS:
00:00 - Latest Cosmos DB optimizations with DiskANN
02:09 - Where DiskANN approach is beneficial
04:07 - Efficient querying
06:02 - DiskANN compared to HNSW
07:41 - Integrate DiskANN into a new or existing app
08:39 - Real-time transactional AI scenario
09:29 - Building a fraud detection sample app
10:59 - Vectorize transactions for anomaly detection
12:49 - Scaling to address high levels of traffic
14:05 - Manage multi-tenancy
15:35 - Wrap up
► Link References
Check out https://aka.ms/DiskANNCosmosDB
Try out apps at https://aka.ms/DiskANNCosmosDBSamples
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New Real-Time Intelligence in Microsoft Fabric | Event-based actions and insights
Quickly spot real-time indicators of issues as they unfold, without the need to poll or manually monitor changes in your data and without writing a single line of code. That’s what the new Real-Time Intelligence service in Microsoft Fabric is all about. It extends Microsoft Fabric to the world of streaming data across your IoT and operational systems. Whether you are a data analyst or business user, you can easily explore high-granularity, high-volume data and spot issues before they impact your business. And as a Data engineer, you can more easily track system level changes across your data estate to manage and improve your pipelines.
Courtney Berg, from the Microsoft Fabric product team, joins Jeremy Chapman to explore all of the updates, explain how Real-Time Intelligence adds to what was possible with Data Activator and Microsoft Synapse Real-Time Analytics and demonstrates how this would work to derive insights and take actions automatically in a scenario with multiple live data streams across different data types.
► QUICK LINKS:
00:00 - Real-Time Intelligence
00:54 - How it’s different
02:07 - Eventstream and Real-Time Hub
03:27 - Synapse Real-Time Analytics
04:03 - See it in action
05:25 - Use Copilot to stay updated
06:28 - Filter data and set up alerts
08:25 - Sophisticated Logic and Data Integration
09:48 - Data integration to Real-Time Hub
11:23 - Workflow automation
12:18 - System events
13:30 - Additional areas of use for Real-Time Intelligence
14:02 - Wrap up
► Link References
Check out Real-Time Intelligence at https://aka.ms/RealTimeIntelligence
For all things Microsoft Fabric, go to https://microsoft.com/fabric
► 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
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Extend Copilot for Sales with custom data and insights from your own apps
Optimize the sales process by integrating internal and external data with Copilot for Sales. Create enriched email summaries, customized meeting prep documents, and actionable meeting recaps to improve customer interactions. Copilot uses AI to generate insights and suggest actions based on comprehensive data, ensuring sales teams have all the necessary information at their fingertips. Create custom AI experiences using Copilot Studio with zero code. By adding Copilot extensions, users can connect to external data sources and build tailored AI skills.
Eric Boocock, Copilot for Sales Principal Program Manager, shares how Copilot for Sales works and how to build Copilot extensions to connect with other systems for personalized experiences.
► QUICK LINKS:
00:00 - Copilot for Sales
00:36 - Baseline experiences
02:13 - Bring in external data
03:26 - Use Copilot to respond to emails
03:54 - Meeting prep and meeting recap
04:52 - Security and Responsible AI
06:27 - Copilot extensions
09:09 - Publish Copilot extensions
09:40 - Wrap up
► Link References
Check out https://aka.ms/CopilotforSalesExtensibility
Stay updated on monthly releases at https://aka.ms/CopilotforSalesUpdates
► 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
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Build your own copilot! New Microsoft Copilot extensions
Now you can build your own highly specialized copilot using Microsoft Copilot Studio or Visual Studio Code. See how you can tailor Copilot for Microsoft 365 experiences to focus on specific tasks and use external data integration through Copilot extensions. Enhance productivity by leveraging large language models and Microsoft Graph for personalized responses. With plugins and connectors, extend Copilot's capabilities to streamline tasks and automate actions, all while maintaining context and boosting efficiency.
Abram Jackson, Principal Product Manager for Microsoft 365 shows how you can get started building Copilot extensions.
► QUICK LINKS:
00:00 - Copilot extensions
01:08 - Types of Copilot extensions
01:59 - Microsoft Graph connectors
03:20 - Plugins
04:14 - Specialized copilot
04:54 - Multiple customized copilots working together
05:42 - How to build Copilot extensions
06:45 - Plug into data-external or inside of Microsoft 365
07:31 - IDE/Visual Studio Code
08:57 - Wrap up
► Link References
To get started, check out https://copilotstudio.microsoft.com
► 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
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What runs GPT-4o and Microsoft Copilot? | Largest AI supercomputer in the cloud | Mark Russinovich
Microsoft has built the world’s largest cloud-based AI supercomputer that is already exponentially bigger than it was just 6 months ago, paving the way for a future with agentic systems.
For example, its AI infrastructure is capable of training and inferencing the most sophisticated large language models at massive scale on Azure. In parallel, Microsoft is also developing some of the most compact small language models with Phi-3, capable of running offline on your mobile phone.
Watch Azure CTO and Microsoft Technical Fellow Mark Russinovich demonstrate this hands-on and go into the mechanics of how Microsoft is able to optimize and deliver performance with its AI infrastructure to run AI workloads of any size efficiently on a global scale.
This includes a look at: how it designs its AI systems to take a modular and scalable approach to running a diverse set of hardware including the latest GPUs from industry leaders as well as Microsoft’s own silicon innovations; the work to develop a common interoperability layer for GPUs and AI accelerators, and its work to develop its own state-of-the-art AI-optimized hardware and software architecture to run its own commercial services like Microsoft Copilot and more.
► QUICK LINKS:
00:00 - AI Supercomputer
01:51 - Azure optimized for inference
02:41 - Small Language Models (SLMs)
03:31 - Phi-3 family of SLMs
05:03 - How to choose between SLM & LLM
06:04 - Large Language Models (LLMs)
07:47 - Our work with Maia
08:52 - Liquid cooled system for AI workloads
09:48 - Sustainability commitments
10:15 - Move between GPUs without rewriting code or building custom kernels. 11:22 - Run the same underlying models and code on Maia silicon
12:30 - Swap LLMs or specialized models with others
13:38 - Fine-tune an LLM
14:15 - Wrap up
► 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
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PostgreSQL for your AI app's backend | Azure Database for PostgreSQL Flexible Server
Use Postgres as a managed service on Azure. As you build generative AI apps, explore advantages of Azure Database for Postgres Flexible Server such as integration with Azure AI services, as well as extensibility and compatibility, integrated enterprise capabilities to protect data, and controls for managing business continuity.
Charles Feddersen, product team lead for Postgres on Azure, joins host Jeremy Chapman to share how Flexible Server is a complete Postgres platform for enterprise and developers.
► QUICK LINKS:
00:00 - Azure Database for PostgreSQL Flexible Server
00:51 - Microsoft and Postgres
01:40 - Open-source Postgres
03:18 - Vector embeddings for data
04:32 - How it works with an app
06:59 - Azure AI Vision
08:14 - Azure AI extension using PostgreSQL
09:37 - Text generation using Azure AI extension
10:30 - High availability and disaster recovery
12:45 - Wrap up
► Link References
Get started with the Azure Database for Postgres flexible server at https://aka.ms/postgresql
Stay current with all the updates at https://aka.ms/AzurePostgresBlog
► 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:
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#PostgreSQL #OpenSource #Azure #Database