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How machine learning ate Microsoft

Mary Branscombe | Feb. 23, 2015
Yesterday's announcement of Azure Machine Learning offers the latest sign of Microsoft's deep machine learning expertise -- now available to developers everywhere.

This week, Microsoft added a new machine algorithm used by Bing Ads that can handle very large amounts of data. "We can learn at a terabyte-sized data set," boasts Sirosh. "I don't know if any cloud service allows you to learn in terabyte sizes today other than Azure ML." That's useful for big data, where you might have to look at a huge data set to find the signals that tell you something.

Microsoft has a range of services that work together for big data scenarios. You can load data into HD Insight, Microsoft's Hadoop cloud service, or pull in data from websites and sensors with Event Hubs, then process that stream of data with Azure Stream Analytics or with Apache Storm, which Azure now supports.

"From that you can call the machine learning APIs to detect anomalies or fraud," explains Sirosh. "You can take enormous amounts of data using, say, HD Insight and use that distilled with Azure ML to learn models that can be deployed in an application. But big learning is a lot more than that. Say fraud is high in certain postal codes and not in others. There are millions of postal codes in the world. These techniques allow you to take these patterns into account; you're able to use very fine-grained information and be very precise about it."

Sirosh clearly believes his platform will accelerate machine learning adoption. "Today businesses hire data scientists and they painfully custom build their own machine learning apps. With a platform like Azure ML it becomes so easy to create custom apps ... Only when you have a special set of needs will you need to set up a team of data scientists to build and API for you."

Walk into a Chili's restaurants and you might find a tablet on each table for ordering food, watching videos, paying the bill, and giving feedback. The system, built by Ziosk, uses HD Insight to track how customers use the tablets in 1,400 restaurants -- and Azure ML to customize what offers and content they see. It can even change the interface on the tablet, based on how they use it.

Sirosh thinks everyone should be building that kind of system. "This is the birth of the intelligent cloud in many ways. Any application you build, you should now consider using the data generated from the app, or any other data you have, to create a better customer experience, to create efficiencies you wouldn't have otherwise tapped into."

Microsoft's big machine learning future
CEO Satya Nadella called out machine learning -- and the big data that powers it -- as a key development in his memo to Microsoft last July. "Billions of sensors, screens, and devices -- in conference rooms, living rooms, cities, cars, phones, PCs -- are forming a vast network and streams of data that simply disappear into the background of our lives. This computing power will digitize nearly everything around us and will derive insights from all of the data being generated by interactions among people and between people and machines. We are moving from a world where computing power was scarce to a place where it now is almost limitless, and where the true scarce commodity is increasingly human attention."


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