Machine learning is the next big technological phenomenon, Microsoft engineering exec says

,Technology Reporter- Boston Business Journal
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Machine learning will become commonplace within 10 years, said Debi Mishra, principal engineering manager at Microsoft’s New England Research and Development Center in Cambridge.

Machine learning is the type of technology that makes it possible for users of websites ranging from Netflix to Amazon to receive personalized music, movie and clothing recommendations.

Soon, machine learning will become a mainstream technology used by businesses and individuals to predict scenarios and make strategic decisions, said Debi Mishra, principal engineering manager at Microsoft’s New England Research and Development Center in Cambridge.

“It’s an extremely happening area,” he said in a recent interview. “If you fast forward five or 10 years, its applications are going to be mind-boggling.”

Machine learning as an area of research has been around since the 1970s but has boomed recently because of the massive amounts of data being generated by technological devices on a day-to-day basis, he said.

“What has changed significantly in the last 10 years is a tremendous amount of data is in digital form,” he said. “The kinds of devices we have are sensing locations, temperature, velocity and movement.”

These devices are producing “organic” data, meaning data that’s not being entered into a machine by a human being.

There are many applications where machine learning is used now. It’s the technology that powers the results returned to individuals through search engines like Google and Bing based on a user’s previous search history and current location.

But soon, machine learning will be used in many other ways, Mishra said. For example, a grocery store could use machine learning to determine how many bottles of ketchup could be sold each week to better plan inventory.

A small business could use machine learning to reward customers that are likely to be repeat customers; and a Web service could use the technology to predict which customers are likely to end subscriptions so the company can reach out to them proactively, Mishra said.

First, though, the world needs more data scientists to create machine learning applications, he said.

According to a study by McKinsey & Co., the United States faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.

Ultimately, the evolution of machine learning technology will be akin to the evolution of databases, he said. About 25 years ago, people felt that databases would only be necessary for a handful of people in industries such as banking. Now, Microsoft’s SQL Server database management system is a business division that represents $5 billion in annual revenue, Mishra said.

“I think the same thing will happen to machine learning,” he said. “It will become very commonplace.”