Earlier this month I attended “Innovate with Azure Day Norway” at Microsoft’s office in Oslo. This was a thorough all-day session from Microsoft to explore how artificial intelligence can underpin business innovation, contributing to growth, security and scalability. It was also a nice opportunity to network and get to know new people.
These are some key takeaways from the topics that was covered:
Migrate to be AI-ready
The place to start to get your organization AI ready, is to migrate your infrastructure to the cloud. The computing power required by AI is far more demanding than workloads from the past. You will need your data and apps to scale dynamically - and you will also want your data to be as close to the AI services as possible.
To learn more about migrating to the cloud and how to become AI-ready, you will find more information in “Migrate to Innvate: Be AI-ready, secure, and optimize operations” on Microsoft Learn
Accelerate Developer Productivity with AI
Microsoft Dev Box provides preconfigured workstations that are cloud based. They are ready to start coding and can be managed and are secure. When developers need a new dev box, it can be deployed from a Dev Portal.
GitHub Copilot can be used to boost Developer Productivity. It is powered by AI, and can be used directly in both Visual Studio Code and Visual Studio.
With GitHub Copilot for GitHub.com, developers can also use GitHub Copilot Chat to ask questions inside GitHub.com. You can ask general questions about development, but you can also ask questions about the code inside a repository. For instance for finding errors in the code, or get to get an explanation of what the code does.
Other use cases for GitHub Copilot Chat for GitHub.com is to find diffs in Pull Requests.
Innovate with Azure AI Platform
With Azure, you will find all the latest open-source and foundation models in the same place. For example Azure OpenAI, Hugging Face, Meta and Nvidia models. Unified APIs provide the opportunity to swap models during different stages of your projects. They can be tested and evaluated using small data sets to find the models that fit your project best using Azure AI Studio
Transform Data Value Creation for the AI Era
Data is the fuel and oxygen in AI transformation. To get AI ready you will need to overcome some barriers:
- What data do you have
- How accessible is your data
- How can you apply AI to modeling
- How can you scale the AI and machine learning models
- How do you empower data professionals to build custom models.
Some options to overcome these barriers are Microsoft Fabric and Microsoft Purview. With Microsoft Fabric you can reshape how you access, manage and act on data and insights. With Fabric, you can connect different data sources and analytics services. To keep the data safe and protected, Microsoft Purview is a good option. It provides a comprehensive set of solutions for governance, protection and management.
To test Microsoft Fabric, you can try it out with a trial version at https://aka.ms/try-fabric
More information about the Microsoft Intelligent Data Platform is also available at https://aka.ms/MIDP-web
You can also learn more at Microsoft Learn with the Transform Data Value Creation for the AI Era collection
Build and Modernize AI Apps
To get started on building intelligent apps, you will need to identify use cases that align with your business outcomes. Your can also modernize your existing apps and platform operations.
Some use cases for intelligent apps are:
- Leveraging AI to present personalized content, products and services to users.
- Automate creation of web and mobile content.
- Chat interfaces for customers to resolve issues quicker and route the cases to the correct employees.
- Using AI for fraud detection, analyzing user behavior and transaction patterns.
Azure provides a set of services to build and modernize intelligent apps:
Examples
Container services:
- Azure Kubernetes Service
- Azure Container Services
- Azure Red Hat OpenShift
Platform as a Service:
- Azure App Service
API services:
- Azure API Management
- Azure API Center
Integration and Serverless services
- Azure Functions
- Azure Logic Apps
- Azure Service Bus
Data storage:
- Azure SQL Database
- Azure Cosmos DB
- Microsoft Fabric
GenAI experiences:
- Model Catalog with benchmarking
- Azure AI Search for seamless grounding of data
- Azure AI Content Safety to protect against for instance prompt injections and jailbreaks
- Azure AI Studio to streamline the development process