A few years ago, there was a shift in the world of machine learning.
Companies, such as Skytree and Context Relevant, began popping up, promising to make it easier for companies outside of big banks and web giants to run machine learning algorithms and to do it at a scale congruent with the big data promise they were being pitched. Soon, there were many startups promising bigger, faster, easier machine learning. Machine learning became the new black as it became baked into untold software packages and services —machine learning for marketing, machine learning for security, machine learning for operations, and on and on and on.
Eventually, deep learning emerged from the shadows and became a newer, shinier version of machine learning. It, too, was very difficult and required serious expertise to do. Until it didn’t. Now, deep learning is the focus of numerous startups, all promising to make it easy for companies and developers of all stripes to deploy.
But it’s not just startups leading the charge in this democratization of data science — large IT companies are also getting in on the act. In fact, Microsoft now has a corporate vice president of machine learning. His name is Joseph Sirosh, and we spoke with him on this week’s Structure Show podcast. Here are some highlights from that interview, but it’s worth listening to the whole thing for his take on Microsoft’s latest news (including support for R and Pythonin its Azure ML cloud service) and competition in the cloud computing space.
You can also catch Sirosh — and lots of other machine learning and big data experts and executives — at our Structure Data conference next month in New York. We’ll be highlighting the newest techniques in taking advantage of data, and talking to the people building businesses around them and applying them to solve real-world problems.