Coming to grips with machine learning needn't require vast amounts of labeled data, a team of data scientists, and a lot of compute time. The state of the art in modern artificial intelligence has reached a point where there are now models that are sufficiently general purpose (within their own domains, of course) that they can be dropped into your applications without additional training and customization. We've seen some of this with the evolution from Project Adam to Azure Cognitive Services. Now Microsoft is taking the next step, using that foundation to deliver a set of machine learning models that provide assistance with common tasks: Azure Applied AI Services. We've already seen some of this with the Power Platform's new document automation tool in Power Automate.

Each year, Microsoft Build is like Christmas for developers, especially those focused on the Microsoft stack. It's when they make the most exciting announcements, release the best new software, and start to solidify the roadmap of innovation for the next year. While we don't get to enjoy the conference in person this year, we do get the same great collection of announcements. This year's highlight for engineers and developers interested in machine learning is the Azure Applied AI Services. Microsoft has been Democratizing AI since 2016. Applied AI Services takes this ideal another step forward. Microsoft has already made machine learning accessible to developers through their outstanding Cognitive Services, and this offering will make certain scenarios even more accessible.

As organizations assess safely reopening and continue navigating unexpected shifts in the world, getting insights to respond in an agile and conscientious manner is vital. Developers and data scientists of all skill levels are inventing with Microsoft Azure AI's powerful and responsible tools to meet these challenges. To help organizations operate safely in today's environment, we are introducing a new spatial analysis capability in the Computer Vision Azure Cognitive Service. Its advanced AI models aggregate insights from multiple cameras to count the number of people in the room, measure the distance between individuals, and monitor wait and dwell times. Organizations can now apply this technology to use their space in a safe, optimal way.