Microsoft Strikes Back at Amazon with Computer Vision

by Adam Pease

At this week’s Microsoft Build, Microsoft demoed its Azure Applied AI Services offering, which aims to deliver fast, streamlined AI solutions to the enterprise. This move foreshadows several trends that are reshaping the AI sector as providers like Microsoft, and Amazon before it, move towards enterprise-grade, turnkey solutions. In this blog, we review the new Azure services and what it reveals about the future of AI for the enterprise.

Microsoft and Azure Applied AI Services

In the war for cloud platforms, AI has become a weapon. Microsoft has struck back against Amazon’s Rekognition AI platform with its recent Build announcement, which showcased new use cases for Microsoft computer vision. Azure Applied AI Services enables enterprises to purchases specific AI capabilities or applications and deploy them quickly across an organization in days. Its services include from conversational AI, document analysis, metric analysis, computer vision, and more.

Microsoft’s approach to enterprise AI focuses on task-specificity, use cases, and quick business deployment rather than providing a highly open development platform. Its goal is to cut out middleware from the AI development and give enterprises a cheap and easy way to get AI-based solutions out the door.

Azure’s New Computer Vision Services: Why Now?

One prominent feature of the new Azure offering is its support for targeted computer vision use cases. Microsoft’s Azure Video Analyzer uses scene recognition algorithms to parse visual content for information and segment it into meaningful data. This move sets it in competition with Rekognition and similar offerings from providers like Google.

Why is Microsoft choosing now to promote its computer vision solution? As we have written elsewhere, computer vision is coming of age. Computer vision solutions are improving as algorithms become more effective at parsing scenes and data becomes more readily accessible. Microsoft advertises that its solution is applicable to a variety of use cases that range from public health monitoring to retail purchasing analysis.

Enterprises Want AI as a Service

Off-the-shelf tools like Azure Applied AI Services are increasingly in demand as more enterprises realize they want to invest in AI to optimize and augment core business processes. Where AI was once seen as an optional investment, many are now considering it table-stakes for competition in particular industries, and for enterprises that want to rapidly differentiate themselves, a striking application of AI to their use case can be a critical factor.

In general, AI as a service offers advantages to enterprises that do not want to contract an entire team of developers, build a machine learning model, and deploy themselves. AI service providers can handle the entire process, from training a configured model up until deploying that model through cloud enablement.

For this reason, Aragon expects more enterprises that want to explore how AI could drive their growth to make use of service providers like Microsoft that can offer dedicated solutions that are simple to build and deploy.

Bottom Line

The AI market is shifting to provide a services-based model for buyers. This model reveals the salience of emerging technologies like computer vision, which enterprises often want to harvest but lack the internal resources to do so. Azure Applied AI Services and offerings like it demonstrate the growing maturity of AI, and the way that the market is expanding to support a more flexible ecosystem of services.

Editor’s Note: Look out for an upcoming Aragon Research Note that profiles critical trends in computer vision, coming this June.