Microsoft

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Microsoft Build 2023 showcased the latest innovations in code and app development to help empower developers around the world. Some of the key announcements include bringing Bing to ChatGPT, Windows Copilot, a new Copilot Stack with common extensibility, Azure AI Studio, and Microsoft Fabric, a new data analytics platform. Book of News


PowerPoint


This process allows you to leverage AI-generated content (the outline) and automate the initial slide creation. Manual adjustments ensure that the final presentation meets your specific requirements.


While on a group call, I generated a set of talking points to the various issues that we were addressing. Basically, kind of a presentation within the prompts. We were able to turn the presentation into Visual Basic for Applications (VBA) code. I opened up PowerPoint right there, copied the text out of the prompt. In PowerPoint I went to the Tools tab, selected down to Macros, and opened the visual basic editor which is available to everybody. I pasted the VBA code in as a new module and ran the code producing our PowerPoint for our team, right there. The whole thing took five minutes to get a 30-page PowerPoint set up. Now, they're was a lot of manual tweaking to be done afterwards. This is totally non-technical what we're talking about here. | Practical AI (paraphrased)


1. Create a Chat Prompt: 

   - Begin by formulating a chat prompt that outlines the content you want in your presentation. Think of it as a conversation with an AI assistant (like me!). Your prompt should include:
       - Persona: Describe the role or expertise of the speaker (e.g., an expert in Python programming).
       - Goal: Specify the purpose of the presentation (e.g., pitching the benefits of Python over Java).
       - Details: Provide relevant information or talking points (e.g., Python's ease of use, development, and scalability).

   For example:
   ```
   You are an expert in Python programming and system development. Write the outline for a slide deck to pitch the Python ecosystem to a Java veteran. Focus on the benefits of easy-to-use, easy-to-develop, and easy-to-maintain features, especially highlighting Python's support for building scalable systems with REST API integration.
   ```

2. Generate an Outline with ChatGPT: 

   - Use an AI language model (like ChatGPT) to generate an outline based on your prompt. The generated outline will serve as the structure for your presentation. For instance:
       ```
       Slide Deck: Pitching the Python Ecosystem to a Java Veteran
       Slide 1: Introduction
           - Welcome and Introduction
           - Target Audience: Java Veterans
           - Objective: Show how Python can replace Java and offer benefits in ease of use, development, and maintenance, with a focus on building scalable systems with REST API support.
       Slide 2: Overview of Python
           - Brief introduction to Python as a high-level programming language
           - Python's popularity and its extensive ecosystem
       Slide 3: Easy to Use
           - Python's simplicity and readability compared to Java
           - Concise and expressive syntax
           - Reduced boilerplate code
       ```
   - Customize the outline as needed, adding more slides or adjusting content.

3. Convert the Outline to VBA Code: 

   - Now, let's turn this outline into VBA code. Open PowerPoint and access the Visual Basic Editor (VBE):
       - Press Alt+F11 or select Visual Basic Editor from the Tools/Macro menu.
       - Right-click on the Project Panel and choose Insert -> Module.
   - Paste the VBA code generated by ChatGPT into this new module.

4. Run the VBA Macro: 

   - Click the Run button (usually a green triangle icon) in the VBE to execute the VBA code.
   - The code will create the slides based on your outline.

5. Manual Tweaking (if needed): 

   - After running the macro, review the slides. You might need to make manual adjustments:
       - Format text, add images, or adjust layouts.
       - Apply consistent styling (fonts, colors, etc.).
       - Insert additional content or remove placeholders.

6. Save Your PowerPoint Presentation: 

   - Save your presentation in either `.pptm` (macro-enabled) or `.pptx` format.



Copilot for Microsoft 365

"How AI Changed ALL Microsoft Tools Forever". It seems to be a comprehensive guide on how artificial intelligence has influenced various Microsoft tools. The video covers a range of tools including PowerPoint, Excel, OneDrive, Word, Outlook, Teams, Copilot Studio, Whiteboard, and Microsoft 365 Chat. It also provides information on how to get these tools.


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Custom Vision

SQL Server Machine Learning Services


Azure IoT Edge

  • Bringing AI to the Edge | Mircosoft
  • 5 Reasons Why Azure IoT Edge Is Industry's Most Promising Edge Computing Platform | Janakiram & Associates
    • Open sourcing the platform - Azure IoT Edge is available as an open source project on Github. Edge computing use cases are still evolving where customers are expected to use the platform in unique ways. To enable flexibility and openness, Microsoft has opened up the source code of its edge computing platform. Through this, customers will be able to customize their deployments based on Azure IoT Edge. Adding legacy protocols, integrating with existing asset management solutions, interoperability with proprietary communication protocols and data formats becomes possible through the customization of Azure IoT Edge source code. Open sourcing edge is a brilliant move from Microsoft. It only increases the trust and confidence of customers.
    • Containers at the core - Microsoft has adopted Moby, the open source container runtime that powers Docker, as the engine for Azure IoT Edge. This design decision enables developers to package and deploy standard Docker containers as modules on Azure IoT Edge. Similar to UNIX Pipes, the output of one module can be fed as an input to another module creating a logical chain of Docker containers that work in tandem. Microsoft is making some of the Azure services such as Stream Analytics, Functions, and SQL Server as containerized modules for the edge. Each module can be managed and maintained separately without having to deploy the entire application. The container images are stored in the standard registry either in the cloud or within the data center. Customers can build CI/CD pipelines to automatically push the latest version of modules (container images) to multiple edge locations. Microsoft is also exploring the integration of Kubernetes with Azure IoT to orchestrate the distributed edge deployments effectively. Adopting containers for packaging both Azure services and custom logic goes a long way in managing complex, distributed edge deployments.
    • Ecosystem engagement - Azure IoT already has a vibrant ecosystem of OEMs and ODMs which is now getting extended to Azure IoT Edge. The IoT Edge certification program has the capability-based certification concept. Each vendor participating in the certification program is assigned a level to identify the capability. For example, a vendor targeting the core runtime will get level 1 while another vendor with robust security offering is eligible for level 4. This capability-based marketplace enables customers to choose from a broad ecosystem of partners offering edge computing solutions. Microsoft has also integrated Azure IoT Edge with Visual Studio Team System and Visual Studio Code. Developers can use pre-defined templates to start building the modules. With VSTS, customers can implement CI/CD pipelines to manage the complete lifecycle of modules.
    • Security - Azure IoT Edge is a logical extension of Azure IoT platform. It takes advantage of services such as Device Provisioning Service to provision tens of thousands of devices securely. The built-in Security Manager acts as a well-bounded security core for protecting the IoT Edge device and all its components by abstracting the secure silicon hardware. ODMs can choose to harden the platform through Hardware Security Modules (HSM).
    • AI @ Edge - Microsoft has made it easy to run machine learning models at the edge. Each model responsible for inferencing can be packaged and deployed as a standard module. Developers can train their models on Azure through Data Science VMs or Azure ML Studio. Azure IoT Edge also supports running models exported from Azure’s Automated Machine Learning (AML) - AutoML services such as custom vision. Since each model is just a container/module, new models can be quickly pushed to the edge. With Microsoft’s investment in ONNX, ML models built using different frameworks may be exported to a standard format before using them for inference. Azure IoT Edge plays a crucial role in Microsoft’s vision of delivering Intelligent Cloud and Intelligent Edge. Some of the design decisions such as containerized modules, tight integration with HSM, plugins for Visual Studio turn Azure IoT Edge into one of the most comprehensive edge computing platforms in the industry.

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