Microsoft Mechanics Podcast Microsoft Mechanics

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.
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• 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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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
• 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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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
 
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#PostgreSQL #OpenSource #Azure #Database

Prioritize incidents based on data significance, detect insider risks, and adapt protections in real-time with Microsoft Defender XDR and Microsoft Purview. Customize thresholds and risk indicators to detect anomalous behavior and prevent potential breaches with Adaptive Protection. Receive real-time DLP alerts triggered by policy matches, ensuring immediate action to safeguard sensitive data. Gain comprehensive visibility into threats and enforce policies across all devices and applications.
Sravan Kumar Mera, Principal Product Manager for Microsoft Purview shares how to stay ahead of evolving threats and maintain data integrity.
 
► QUICK LINKS: 
00:00 - Prioritize security incidents based on data importance
00:42 - High severity multistage incident
01:29 - DLP alerts
02:24 - Insider risk activity summary
03:30 - Set up data security foundation
04:47 - Adaptive Protection
05:50 - DLP policy & Conditional Access
06:33 - Wrap up
 
► Link References
Get started at https://purview.microsoft.com
Watch our data security playlist at https://aka.ms/datasecuritymechanics
 
► 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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• Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/
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Build low-latency recommendation engines with Azure Cosmos DB and Azure OpenAI Service. Elevate user experience with vector-based semantic search, going beyond traditional keyword limitations to deliver personalized recommendations in real-time. With pre-trained models stored in Azure Cosmos DB, tailor product predictions based on user interactions and preferences. Explore the power of augmented vector search for optimized results prioritized by relevance.
Kirill Gavrylyuk, Azure Cosmos DB General Manager, shows how to build recommendation systems with limitless scalability, leveraging pre-computed vectors and collaborative filtering for next-level, real-time insights.
 
► QUICK LINKS: 
00:00 - Build a low latency recommendation engine
00:59 - Keyword search
01:46 - Vector-based semantic search
02:39 - Vector search built-in to Cosmos DB
03:56 - Model training
05:18 - Code for product predictions
06:02 - Test code for product prediction
06:39 - Augmented vector search
08:23 - Test code for augmented vector search
09:16 - Wrap up
 
► Link References
Walk through an example at https://aka.ms/CosmosDBvectorSample 
Try out Cosmos DB for MongoDB for free at https://aka.ms/TryC4M
 
► 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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Leverage FinOps in Azure to optimize your cloud spend and drive accountability across your organization. With Microsoft Cost Management, gain complete visibility into your cloud costs, track spending by department or project, and forecast future expenses. Utilize management groups, subscriptions, and tags to organize costs and allocate resources efficiently, ensuring alignment with organizational priorities.
Make informed decisions with proactive cost reduction recommendations from Azure Advisor and architectural best practices like Azure Landing Zones. Operationalize FinOps practices with centralized management focus and continuous evaluation through the FinOps Review assessment.
Azure expert, Matt McSpirit, shows how to improve your organization's capability and operational agility with FinOps on Azure.
 
► QUICK LINKS:
00:00 - Improve control on Azure through FinOps
01:01 - Gain visibility and accountability over Cloud spend
02:11 - Track and report spending
03:28- How to track costs
04:14 - Tagging resources
05:57 - Optimized efficiency
07:02 - Maintain FinOps practices
08:05 - Wrap up
 
► Link References
How to implement FinOps on Azure at https://aka.ms/FinOps
Leverage Cloud Adoption Framework guidance at https://aka.ms/C-A-F-Tagging
Click-through demos at https://aka.ms/finops/guides
FinOps Review assessment at https://aka.ms/finops/review
Start using Microsoft Cost Management at https://aka.ms/CostManagement
 
► 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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