Msn partner hub program Invitation code inquiry
Hi , I don't have access to any publisher of msn partner hub program. But I just wanted to join it at any cost. This is very important for me join it. Please send me an invite code for it. So, I can join it. Or send me the link of any publisher so I can contact him. Please help me out to join this program. It is very essential for life fulfill my life purpose. I will thankful to you. With my best Regards
OneDrive for macOS documentation issue. DefaultFolder plist example is missing array wrapper
Hi everyone, The Microsoft Learn documentation for configuring the OneDrive sync app on macOS currently contains an incorrect plist example for the DefaultFolderLocation setting. Documentation page: https://learn.microsoft.com/en-us/sharepoint/deploy-and-configure-on-macos#defaultfolderlocation In the “DefaultFolderLocation” section, the current plist example shows the DefaultFolder key as a dictionary: <key>DefaultFolder</key> <dict> <key>Path</key> <string>(DefaultFolderPath)</string> <key>TenantId</key> <string>(TenantID)</string> </dict> This format does not work correctly when deployed as a managed preference/configuration profile. The setting starts working when the DefaultFolder dictionary is wrapped in an array, like this: <key>DefaultFolder</key> <array> <dict> <key>Path</key> <string>(DefaultFolderPath)</string> <key>TenantId</key> <string>(TenantID)</string> </dict> </array> Please update the Microsoft Learn documentation to include the array wrapper in the DefaultFolder plist example. The current Microsoft Learn example is confusing because administrators may deploy the documented plist exactly as shown, but the setting does not appear to work correctly until the array wrapper is added.
Passed Microsoft Applied Skills: Developing Agents in Microsoft Foundry
I recently completed the Microsoft Applied Skills: Get Started Developing Agents in Microsoft Foundry credential. It was a great hands-on experience with Azure AI Foundry, including deploying models, building AI agents, using Code Interpreter, and publishing an agent. If you're interested in Azure AI or Generative AI, these official Microsoft resources are a great place to start: 🔹 Microsoft Copilot https://learn.microsoft.com/copilot?wt.mc_id=studentamb_530495 🔹 Azure AI Foundry https://azure.microsoft.com/products/ai-foundry?wt.mc_id=studentamb_530495 🔹 Azure for Students https://azure.microsoft.com/free/students?wt.mc_id=studentamb_530495 🔹 Azure Free Account https://azure.microsoft.com/free?wt.mc_id=studentamb_530495 🔹 Microsoft Learn – Azure AI Training https://learn.microsoft.com/training/azure-ai/?wt.mc_id=studentamb_530495 A small request: I'm currently working toward the Microsoft Learn Student Ambassadors Community Influencer requirements. If any of these resources are relevant to you, I'd genuinely appreciate you taking a look. I hope you discover something useful for your own learning journey as well. Thank you, and happy learning!Disable incessant nagware popups
I don't know about everyone else, but I am sick and tired of the nagware pop ups in Word, Excel, PowerPoint, Outlook, etc. Every single product harasses me with pop ups trying to tell me "hey, did you know this feature was here?", "you can do this if you click that", "let me hold your hand through using products you've used for decades even though you don't want daddy Microslop to do that". This is a prime example. I keep getting the same ones again and again and again and everything I've read indicates they should only appear once. But they don't. They keep coming back like a psychotic stalker ex who wants alimony even though you were never married. How do I get this nagware to stop?!
Help wanted: Refresh articles in Azure Architecture Center (AAC)
I’m the Project Manager for architecture review boards (ARBs) in the Azure Architecture Center (AAC). We’re looking for subject matter experts to help us improve the freshness of the AAC, Cloud Adoption Framework (CAF), and Well-Architected Framework (WAF) repos. This opportunity is currently limited to Microsoft employees only. As an ARB member, your main focus is to review, update, and maintain content to meet quarterly freshness targets. Your involvement directly impacts the quality, relevance, and direction of Azure Patterns & Practices content across AAC, CAF, and WAF. The content in these repos reaches almost 900,000 unique readers per month, so your time investment has a big, global impact. The expected commitment is 4-6 hours per month, including attendance at weekly or bi-weekly sync meetings. Become an ARB member to gain: Increased visibility and credibility as a subject‑matter expert by contributing to Microsoft‑authored guidance used by customers and partners worldwide. Broader internal reach and networking without changing roles or teams. Attribution on Microsoft Learn articles that you own. Opportunity to take on expanded roles over time (for example, owning a set of articles, mentoring contributors, or helping shape ARB direction). We’re recruiting new members across several ARBs. Our highest needs are in the Web ARB, Containers ARB, and Data & Analytics ARB: The Web ARB focuses on modern web application architecture on Azure—App Service and PaaS web apps, APIs and API Management, ingress and networking (Application Gateway, Front Door, DNS), security and identity, and designing for reliability, scalability, and disaster recovery. The Containers ARB focuses on containerized and Kubernetes‑based architectures—AKS design and operations, networking and ingress, security and identity, scalability, and reliability for production container platforms. The Data & Analytics ARB focuses on data platform and analytics architectures—data ingestion and integration, analytics and reporting, streaming and real‑time scenarios, data security and governance, and designing scalable, reliable data solutions on Azure. We’re also looking for people to take ownership of other articles across AAC, CAF, and WAF. These articles span many areas, including application and solution architectures, containers and compute, networking and security, governance and observability, data and integration, and reliability and operational best practices. You don’t need to know everything—deep expertise in one or two areas and an interest in keeping Azure architecture guidance accurate and current is what matters most. Please reply to this post if you’re interested in becoming an ARB member, and I’ll follow up with next steps. If you prefer, you can email me at v-jodimartis@microsoft.com. Thanks! 🙂Demystifying Azure AI Foundry: A Beginner's Guide
Are you ready to dive into the transformative world of Artificial Intelligence but unsure where to start? You landed at the right page. Welcome! Whether you’re just getting started or have a bit of experience under your belt, this read will provide you with the foundational knowledge needed to unlock the potential of Azure AI Foundry. Azure AI Foundry offers a powerful suite of tools and Machine Learning Models. Let’s start harnessing its capabilities as an initial step to create innovative AI solutions that can revolutionize your projects or business. As a Microsoft Technical Trainer, delivering classes on AI and Data for the past several years, I have witnessed the significant impact AI has had across various industries. My objective here is to equip you with the foundational knowledge and confidence necessary to embark on your AI journey. Azure AI Foundry (formerly Azure AI Studio) is a suite of tools that makes artificial intelligence accessible to everyone. It allows users to build, deploy, and manage AI solutions easily. Azure AI Foundry can be leveraged to address real-world business challenges and foster innovation. For instance, Azure AI Foundry can enhance predictive maintenance in manufacturing by analyzing sensor data to foresee equipment failures to minimize downtime and costs. In retail, it can perform customer sentiment analysis across social media, reviews, and surveys, offering insights into customer satisfaction and areas for improvement. For more ways that Azure AI Foundry can help your organization, see customer stories here: Azure AI Foundry - Generative AI Development Hub and here: Need inspirations? Real AI Apps stories by Azure customers to help you get started With Azure AI Foundry, you can explore and develop various AI models and services tailored to your goals. The platform supports scalability, enabling proof of concepts to become full production applications effortlessly. It also has support for continuous monitoring and refinement ensuring long-term success. Here's a brief overview of AI Foundry's main architectural components and their integration. Azure AI Foundry architecture - Azure AI Foundry At the top level, AI Foundry provides access to the following resources: Management Center: Used to manage AI Foundry resources like hubs, projects, connected resources, and deployments. It is a part of the Azure AI Foundry portal that streamlines governance and management activities. In the management center, you can view and manage: Projects and resources Quotas and usage metrics Govern access and permissions For more information see: Management center overview - Azure AI Foundry AI Foundry Hub: The main top-level resource in the AI Foundry portal, offering a centralized method for managing security, connectivity, and computing resources across playgrounds and projects. Once a hub is established, developers can create projects from it and access shared resources like storage accounts, key vaults, databases and others without requiring continuous assistance from an IT administrator. The hub uses the Azure Machine Learning service and this Azure Provider, Microsoft.MachineLearningServices/workspaces and the type is hub. It offers: Security features, including a managed network for projects and model endpoints. Computer resources for development, fine-tuning, open-source, and serverless model deployments. Connections to other Azure services, such as Azure OpenAI and Azure AI Search. An Azure storage account for data and artifacts. AI Foundry Project: A project is part of the hub. Projects help organize work, save state across tools like prompt flow and enable collaboration. You can share files and data source connections within a project. Hubs support multiple projects and users. Projects manage billing, access, and provide data isolation, using dedicated storage containers to securely share files among project members. Once you have a project, you can connect to it from your code. You can explore models and capabilities before creating a project, but once you're ready to build, customize, test, and operationalize, a project is where you'll want to be. The Azure provider for a project is Microsoft.MachineLearningServices/workspaces, and the type is Project. The project offers: Reusable assets like datasets, models, and indexes. A container for uploading data within the hub's storage. Private data access for project members. Model deployments from the catalog and adjusted model endpoints. Connections: AI Foundry hubs and projects use connections to access resources from other services, such as an Azure Storage Account, Azure OpenAI, or other Azure AI services. Once you have setup the Azure Foundry Hub, Project and Connection, its time to start exploring and deploying the models. Model Catalog: Available in Azure AI Foundry portal to discover and use a wide range of models for building generative AI applications. The model catalog features hundreds of models across model providers such as Azure OpenAI Service, Meta, NVIDIA, Hugging Face, DeepSeek, and of course the models trained by Microsoft like Phi. Azure AI Model Catalog – Foundation Models You can search and discover models that meet your needs. The model catalog also offers the model performance benchmark metrics which can be accessed by using Compare Models feature or from the model card Benchmark tab. Models need to be deployed to make them available for receiving inference requests. Azure AI Foundry offers a comprehensive suite of deployment options for those models depending on your needs and model requirements. Prompt Flow: This feature can be used to generate, customize, or run a flow. A flow is an executable instruction set that can implement the AI logic. Flows can be created or run via multiple tools, like a prebuilt canvas, LangChain, etc. Iterations of a flow can be saved as assets; once deployed a flow becomes an API. Prompt flow in Azure AI Foundry portal - Azure AI Foundry A prompt is sent to a model, consisting of the user input, system message, and any examples. User input is text submitted in the chat window. System message is a set of instructions to the model scoping its behaviors and functionality. Evaluators: Helpful tools to assess the frequency and severity of content risks or undesirable behavior in AI responses. Performing iterative, systematic evaluations with the right evaluators can help teams measure and address potential response quality, safety, or security concerns throughout the AI development lifecycle. You can explore Azure AI Foundry benchmarks to evaluate and compare models on publicly available datasets. Deploy: Remember to deploy your model setup. Deployments are hosted within an endpoint and can receive data from clients and send responses back in real-time. You can invoke the endpoint for real-time inference for chat, copilot or another generative AI application. AI Foundry has all the needed capabilities including content filters, Responsible AI factors and Security. More about these aspects in my next article. Playgrounds: Be sure to test your model using the Playgrounds on Azure AI Foundry. The portal offers a chat playground for deploying and interacting with AI chat models, allowing you to refine them before production deployment. Hear and speak with chat models in the Azure AI Foundry portal chat playground - Azure AI Foundry Now that you have the foundational knowledge, I encourage you to begin using Azure AI Foundry by following the resources and guidelines provided. Ready to get started with Azure AI Foundry? Here are some tutorials to guide you: Use the chat playground in Azure AI Foundry portal Tutorial: Deploy an enterprise chat web app in the Azure AI Foundry portal playground Explore, learn, and transform your ideas into reality with Azure AI Foundry. Stay tuned for more! Happy Learning!All-in-One Content Creation with the New Microsoft 365 Dashboard
🎨 Discover the new Microsoft 365 Dashboard creation experience! In this video, I’ll walk you through the redesigned interface that makes it easier than ever to create and manage content—whether it’s images, posters, documents, videos, and more. Microsoft is transforming M365 into a true creative hub, perfect for both personal productivity and professional branding. ✅ Learn how to navigate the new dashboard ✅ Explore templates for visuals, documents, and multimedia ✅ See how AI and design tools integrate into your workflow ✅ Tips to boost your productivity with Microsoft 365 💬 Don’t forget to like, subscribe, and share your thoughts in the comments! 📌 Perfect for creators, marketers, educators, and business users. #Microsoft365 #ContentCreation #ProductivityTools #MicrosoftDashboard #M365Tips #Office365 #WorkSmarter #MicrosoftTemplates #DigitalCreativity #CreateWithMicrosoft
