Hey Friends! In this post I’d like to take a step back from focusing on some of Microsoft’s AI products and low-code AI Copilots. If you’re looking at building your own custom implementations, using AI in your pro-dev projects, and you’re not sure what’s out there to get your hands on, or what you can build into your applications, then you’re in the right place!
In this post, we’ll explore Microsoft’s Azure AI Studio which is an awesome platform that empowers developers of all abilities to innovate with AI and seamlessly explore, build, test and deploy using a range of AI models across different forms of AI, including both Microsoft and OpenAI’s models as well as models from other vendors.
Getting started
So let’s start by simply taking a look at the home page of the Azure AI Studio! This really is a one stop shop to everything you can achieve with AI in Azure. Straight away we get prompts to build various things from low level exercises up to more pro-development and advanced exercises, allowing us to get a feel for what we can achieve with AI on Azure.
Scrolling down we get some more content and prompts to take a look at various models in the AI Studio catalogue covering various vendors such as Microsoft, OpenAI, Meta and more! We also see various ways we can infuse digital solutions and products with AI through generative AI, speech focused AI and vision focused AI!
We then also get content and prompts around something really important being responsible AI! Now not only do we get content here on what responsible AI is, and what we should be doing in this space. But we actually get content and build resources to build responsible AI practices into our applications with moderation techniques and more.
Explore
Within the explore tab in Azure AI Studio we’re able to effectively discover and try out the various AI capabilities and models that exist for us to run from Azure. Whether this be LLM type AI models, or speech, language and vision type models, this is the space for us to start to explore this stuff alongside content safety, and understanding how to prompt these various models and capabilities too!
Build
Now in the build area of AI Studio, we can actually start to build the AI products we want to then utilise in our applications. Here I am building an LLM based chat experience for example, which I can then deploy to create a web app in Azure which will have a UI generated for me to test out my AI product! 🚀
Manage
Finally in Azure AI Studio I can manage the resources I have created in Azure which are powering the AI Studio and the various things I am building. I can also create new resources and see where they’re sitting here. Effectively this lets me manage what I am using in Azure when it comes to all things Azure AI 🤖
