Microsoft (MSFT 1.82%) and other tech firms are racing to secure a foothold in the burgeoning machine-learning industry that promises to make future predictions possible through the use of big data. Microsoft's platform Azure aims to enable companies to utilize the cloud to build applications at comparatively low costs compared to traditional machine-learning solutions.

According to Microsoft's Corporate VP of Machine Learning, Joseph Sirosh, "Soon, machine learning will help to drastically reduce wait times in emergency rooms, predict disease outbreaks and predict and prevent crime. To realize that future, we need to make machine learning more accessible – to every enterprise and, over time, everyone."

Azure for enterprise costs less
Microsoft's product is built on the machine-learning capabilities of other Microsoft projects like Xbox and Bing. Companies will be able to use predefined templates and workflows to quickly and easily launch predictive applications in a much faster manner than traditional development methods would allow. Customers will even be able to publish APIs and web services on top of the Azure cloud service.

Some of the largest companies already use machine learning to make predictions and optimize their services, detect fraud, and predict consumer demand. But until now, the complexity and cost of developing this sort of software has been prohibitively expensive, and it's remained a niche service.

As Sirosh pointed out, machine learning requires the expertise of data scientists, who are in short supply, as well as expensive commercial software licenses, and training.

That's where Microsoft comes in with Azure -- a platform that offers the benefits of machine learning, but with significantly less complexity.

Tech giants battling it out on the cloud
Microsoft is likely to face fierce competition from tech behemoths IBM (IBM -1.05%) and Google (GOOG 9.96%) (GOOGL 10.22%), however, as each is readying offerings in the sector.

Google is developing its own deep-learning artificial intelligence, which has already proven itself to be almost twice as good as any previous image-recognition software. Google's huge computing infrastructure will give it a strong advantage. Whereas Google will be collecting data via its namesake search engine, YouTube, and a number of its other websites, Microsoft will be competing using the lesser Bing. Google also has a strong incentive to make its AI viable -- Google AdWords, the company's primary revenue stream, will be drastically improved by being able to predict what customers want and when.

IBM is also making moves in a similar direction with its recent launch of a new subsidiary that will aim to commercialize the artificial intelligence technology previously developed for the Watson project, which became famous on the quiz show "Jeopardy" a few years back. The machine arrived at answers by processing terabytes of data. IBM is likely to bring Microsoft the most pain in the machine-learning arena, due to the huge resources it has available and its head start with a software system that has already had a chance to prove itself.

How does Microsoft compare?
How the battle will play out between these firms and others who enter machine learning is not clear. Microsoft is most likely to come up primarily against Google within the consumer market and IBM within the enterprise market. Against IBM, Microsoft is likely to be the top dog in the enterprise market with its already sturdy reputation in businesses everywhere. Google will likely win any contest in the consumer sector due to its strong brand and deployment of Glass and Android – perfect for collecting and utilizing data. Despite this, Microsoft is still a few steps ahead of Google.

The bottom line
Developing machine-learning software will bring technology forward as computers begin to understand our needs. The foundation exists for these products to come to market, but it will likely be at least a few years before consumers see them in their devices. Microsoft remains well-positioned, despite lacking a first-to-market advantage. Given the company's array of products, market penetration, and reputation as a blue chip stock, it's a buy.