Avsnitt

  • Redefine personal and business computing by combining powerful AI capabilities with cutting-edge hardware using Copilot+ PCs. Whether you're developing apps that harness the full potential of the NPU or taking advantage of AI experiences like Windows Studio Effects, Copilot+ PCs offer a platform that is both robust and efficient.

    Vivek Pradeep, Vice President and Distinguished Engineer at Microsoft, joins Jeremy Chapman to share how Copilot+ PCs provide the tools you need to innovate with confidence. Trust in the highest level of device security, thanks to features like Windows Hello biometric authentication and the Microsoft Pluton security processor. With new hardware options like the OLED touchscreen and Flex Keyboard, you can customize your workspace to match your workflow, all while enjoying enhanced battery life and performance.

    ► QUICK LINKS:
    00:00 - Build next-gen AI apps for Copilot+ PC
    00:44 - Personalized experience with Copilot+ PCs
    02:28 - Windows Studio Effects
    04:47 - AI in Paint using Cocreator
    06:37
    - Local AI translates speech
    07:30 - Lower power consumption
    08:14 - Update and deploy models
    09:43 - Build apps with local AI on Copilot+ PC
    11:31 - Updates to Surface Copilot+ PC devices
    12:56 - Secured-core PC
    13:42 - What to expect next
    14:33 - Wrap up

    ► Link References

    Check out Surface updates at https://surface.com/business

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  • New Windows 365 GPU-enabled Cloud PCs can help maximize productivity for anyone in graphics-intensive fields such as graphic design, video editing, 3D modeling, and data visualization. With Windows 365, you can stream your Windows experience from the Microsoft cloud to any device and benefit security, increase connection speeds, and reduced latency.

    ► QUICK LINKS:
    00:00 - Cloud PC in Windows 365 can be GPU-enabled
    00:28 - Run compute-intensive apps
    00:50 - Run demanding workloads
    01:37 - Fast data transfer with reduced latency
    02:19 - Windows 365 GPU options
    03:30 - Shared utilization
    03:50 - Data remains separate
    04:13 - Windows 365 new watermark support
    04:28 - Windows 365 management
    05:01 - Wrap up

    ► Link References

    Get started at https://windows365.com

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  • Microsoft Fabric seamlessly integrates with generative AI to enhance data-driven decision-making across your organization. It unifies data management and analysis, allowing for real-time insights and actions.

    With Real Time Intelligence, keeping grounding data for large language models (LLMs) up-to-date is simplified. This ensures that generative AI responses are based on the most current information, enhancing the relevance and accuracy of outputs. Microsoft Fabric also infuses generative AI experiences throughout its platform, with tools like Copilot in Fabric and Azure AI Studio enabling easy connection of unified data to sophisticated AI models.

    ► QUICK LINKS:
    00:00
    - Unify data with Microsoft Fabric
    00:35 - Unified data storage & real-time analysis
    01:08 - Security with Microsoft Purview
    01:25 - Real-Time Intelligence
    02:05 - Integration with Azure AI Studio

    ► Link References

    This is Part 3 of 3 in our series on leveraging generative AI. Watch our playlist at https://aka.ms/GenAIwithAzureDBs

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  • See how you can use your SQL data as a robust backend for AI applications with semantic search and retrieval augmented generation. Azure SQL Database along with any SQL servers you connect to Azure integrate seamlessly with Azure AI Search and the Azure OpenAI Service, enabling natural language search capabilities within your SQL data.

    Use this approach to enhance e-commerce platforms, financial data analysis, or CRM systems while using SQL's granular access management controls to ensure that data searches and generated responses are limited to specific user permissions.

    ► QUICK LINKS:
    00:00
    - Generative AI for your SQL workloads
    00:33 - Retrieval Augmented Generation
    01:00 - Granular access management
    01:15 - Enable natural language search
    01:54 - Connect vectorized SQL data
    02:20 - Test generative AI responses
    02:41
    - Wrap up

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  • Get a unified solution for secure access management, identity verification, and Zero Trust security for cloud and on-premises resources. The new Microsoft Entra suite integrates five capabilities: Private Access, Internet Access, ID Protection, ID Governance, and Face Check as part of Verified ID Premium, included with Microsoft Entra Suite. With these capabilities, you can streamline user onboarding, enhance security with automated workflows, and protect against threats using Conditional Access policies. See how to reduce security gaps, block lateral attacks, and replace legacy VPNs, ensuring efficient and secure access to necessary resources.

    Jarred Boone, Identity Security Senior Product Manager, shares how to experience advanced security and management with Microsoft Entra Suite.

    ► QUICK LINKS:
    00:00 - Unified solution with Microsoft Entra Suite
    00:38
    - Microsoft Entra Private Access
    01:39 - Microsoft Entra Internet Access
    02:42 - Microsoft Entra ID Protection
    03:31 - Microsoft Entra ID Governance
    04:18 - Face Check in Verified ID Premium, included with Microsoft Entra Suite
    04:52
    - How core capabilities work with onboarding process
    06:08 - Protect access to resources
    07:22 - Control access to internet endpoints
    08:05 - Establish policies to dynamically adjust
    08:45 - Wrap up

    ► Link References

    Try it out at https://entra.microsoft.com

    Watch our related deep dives at https://aka.ms/EntraSuitePlaylist

    Check out https://aka.ms/EntraSuiteDocs



    ► Unfamiliar with Microsoft Mechanics?

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  • Leverage Azure Cosmos DB for generative AI workloads for automatic scalability, low latency, and global distribution to handle massive data volumes and real-time processing. With support for versatile data models and built-in vector indexing, it efficiently retrieves natural language queries, making it ideal for grounding large language models. Seamlessly integrate with Azure OpenAI Studio for API-level access to GPT models and access a comprehensive gallery of open-source tools and frameworks in Azure AI Studio to enhance your AI applications.

    ► QUICK LINKS:
    00:00 - Azure Cosmos DB for generative AI workloads
    00:18 - Versatile Data Models
    00:39 - Scalability and performance
    01:19 - Global distribution
    01:31 - Vector indexing and search
    02:07 - Grounding LLMs
    02:30 - Wrap up

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  • Check out new AI integrations for your Azure SQL databases. With Retrieval Augmented Generation, you can bridge structured data with generative AI, enhancing natural language queries across applications. With advanced vector-based semantic search, discover precise insights tailored to your data, while Copilot in Azure streamlines troubleshooting and T-SQL query authoring. Optimize workflows, personalize responses, and unlock new levels of efficiency in SQL-driven AI applications.

    Accelerate performance troubleshooting and complex query authoring tasks with Copilot in Azure. Quickly diagnose database issues and receive expert recommendations for optimization, ensuring optimal performance and reliability. Seamlessly traverse hierarchies within tables and generate intricate queries with ease, saving time and resources.

    Bob Ward, Azure Principal Architect, shows how to unleash the full potential of your SQL data, driving innovation and intelligence across your applications.

    ► QUICK LINKS:
    00:00 - AI and Azure SQL
    01:40 - Using T-SQL for search
    02:30 - Using Azure AI Search
    03:17 - Vector embeddings and skillsets
    04:08 - Connect your SQL data to an AI app
    05:44 - Test it in Azure OpenAI Studio playground
    07:22 - Combine native JSON data type in SQL
    08:30 - Hybrid search
    09:56 - Copilot in Azure: Performance troubleshooting
    11:11 - Copilot in Azure: Query authoring
    12:24 - Permissions
    12:40
    - Wrap up

    ► Link References

    For building AI apps, check out https://aka.ms/sqlai

    Try out new copilot experiences at https://aka.ms/sqlcopilot

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  • Bring your MySQL workloads to run on Azure. Azure Database for MySQL - Flexible Server offers a powerful, fully managed solution for MySQL workloads, providing unique platform-level optimizations that significantly enhance connection scaling and cost performance. Ensure high efficiency and reduced latency for mission-critical applications for up to twice the performance of other offerings. The integration with Azure OpenAI Service and Azure AI Search further extends its capabilities, enabling intelligent vector-based search and generative AI responses for more accurate and relevant user queries.

    Join Parikshit Savjani, Azure Database for MySQL Principal Group PM, shares how Azure Database for MySQL - Flexible Server transforms traditional MySQL applications into high-performance, intelligent systems by combining the scalability and security of Azure with advanced AI-driven insights.

    ► QUICK LINKS:
    00:00 - Run MySQL on Azure
    00:56 - Run your LAMP stack on Azure
    01:24 - Accelerated Logs capability
    03:02 - Vector-based search and generative AI
    04:02 - Leverage Azure AI Search & Azure OpenAI services
    04:29
    - Establish database connection
    05:52 - Build vector index
    07:04 - Create an Indexer
    07:32 - Semantic Search
    07:54
    - Test it in the Azure AI playground
    08:49 - Wrap up

    ► Link References

    Check out https://aka.ms/mysql-resources

    Join the community for Azure Database for MySQL at https://aka.ms/mysql-contributors

    ► Unfamiliar with Microsoft Mechanics?

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  • Use your files, emails, chats and meeting information automatically or with direct references using Copilot prompts in Microsoft 365 apps. You don't need to copy information then paste it into a browser tool or upload work files and images into other generative AI experiences. Instead, directly from Teams, Word, PowerPoint and other Microsoft 365 apps, you can leverage not only your opened file, email, chat or meeting, but also other work data that you have permissions to in SharePoint and OneDrive. Copilot retrieves and synthesizes information across emails, chats, and files, so you can generate presentations, respond to emails, and catch up on meetings. The Copilot process also follows your organization's policies for data protection and compliance, eliminating the need and added risk of bringing your work data to those tools.

    Mary David Pasch, Principal Product Manager from the Copilot Platform team, joins Jeremy Chapman to share how Copilot enhances collaboration and efficiency, making complex tasks like document creation and information retrieval effortless and secure.

    ► QUICK LINKS:
    00:00 - Leverage your work data with Copilot
    00:51 - How Copilot augments your prompts
    02:22 - Automatically works across your files
    03:03 - Meeting recaps with Copilot in Teams
    03:59 - Meeting summaries with Copilot in Teams
    04:57 - Incorporate specific info from work data
    06:53
    - Convert written docs to PowerPoint presentations
    09:07 - Recommended prompts
    10:29 - Standalone Copilot chat experience
    12:11 - Stay within your Microsoft 365 data security boundary
    12:39 - Wrap up

    ► Link References

    For more go to Copilot Lab at https://copilot.cloud.microsoft

    Watch our full series on Microsoft Mechanics at https://aka.ms/M365CopilotMechanics

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  • Improve search capabilities for your PostgreSQL-backed applications using vector search and embeddings generated in under 10 milliseconds without sending data outside your PostgreSQL instance. Integrate real-time translation, sentiment analysis, and advanced AI functionalities securely within your database environment with Azure Local AI and Azure AI Service. Combine the Azure Local AI extension with the Azure AI extension to maximize the potential of AI-driven features in your applications, such as semantic search and real-time data translation, all while maintaining data security and efficiency.

    Joshua Johnson, Principal Technical PM for Azure Database for PostgreSQL, demonstrates how you can reduce latency and ensure predictable performance by running locally deployed models, making it ideal for highly transactional applications.

    ► QUICK LINKS:
    00:00 - Improve search for PostgreSQL
    01:21 - Increased speed
    02:47 - Plain text descriptive query
    03:20 - Improve search results
    04:57
    - Semantic search with vector embeddings
    06:10 - Test it out
    06:41 - Azure local AI extension with Azure AI Service
    07:39 - Wrap up

    ► Link References

    Check out our previous episode on Azure AI extension at https://aka.ms/PGAIMechanics

    Get started with Azure Database for PostgreSQL - Flexible Server at https://aka.ms/postgresql

    To stay current with all the updates, check out our blog at https://aka.ms/azurepostgresblog

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  • 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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  • 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

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  • 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

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  • 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

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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

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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

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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

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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?

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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

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  • Roll out Microsoft Copilot for Microsoft 365 at scale in three quick steps. See the methods for each to efficiently enable Copilot services:

    Optimize Search with data controls in place to limit exposure of information in search. Update Your Apps—both on desktop and mobile—so they are ready for integrated Copilot experiences. Grant Access to Copilot services quickly to large groups in your organization via Microsoft Entra controls.

    We're also introducing a new capability with Restricted SharePoint Search, which enables SharePoint administrators to define the sites where every user in the organization is allowed to files and data using search, without impacting access to sites and files for people working in sites, which are not allowed for everyone to search.

    With Copilot for Microsoft 365 services in place, track adoption and impact, and see how different groups in your organization are benefitting from Copilot services with the Microsoft Copilot Dashboard powered by Viva Insights. Now, even if you don't currently own Viva Insights, there is an offer for Microsoft Copilot customers to get these services included with your Copilot subscription: https://www.microsoft.com/en-us/microsoft-365/blog/2024/04/11/enabling-your-ai-transformation-journey-with-microsoft-viva/

    ► QUICK LINKS:
    00:00 - Steps to deploy Copilot for Microsoft 365
    01:01 - How to quickly optimize search
    02:24 - How to set up Restricted SharePoint Search
    03:23 - Update Microsoft 365 apps on managed devices
    05:34
    - Grant access to Copilot services
    06:20 - Copilot Dashboard included with any Microsoft 365 subscription
    07:00 - Copilot Dashboard powered by Viva Insights subscription
    08:38 - Wrap Up

    ► Link References:

    Get started at https://aka.ms/DeployCopilotforM365

    Watch how to get ready for Copilot at https://aka.ms/CopilotSecurityMechanics

    For more resources go to https://adoption.microsoft.com/copilot

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