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How Microsoft plans to address AI and machine learning challenges

Steven Max Patterson | March 30, 2017
Peter Lee, Microsoft’s research vice president, answers hard questions about artificial intelligence and machine learning.

Lee wants to invest in a portfolio of vertical industry opportunities like UMPC Enterprises. He is willing to bring the right partners’ engineers into Microsoft’s labs to work shoulder to shoulder with Microsoft researchers to create original models that, once prove, could be stamped out in volume and sold to an entire vertical industry that Lee hopes will use Microsoft’s ML specialized cloud hardware to train and run the models.

Though Lee may have a preference for Microsoft’s open source Cognitive Tool Kit, he isn’t opposed to Google’s TensorFlow or Facebook’s Caffe 2 libraries if they are a better fit. That’s because success is measured based on the impact on Microsoft’s cloud business in the post-Ballmer, open-Microsoft cloud era. 

Tier 2 models will remain a research topic for Microsoft to watch and measure progress towards reaching the long-term goal of AGI.

Perhaps in the next five years, more computer science students will learn AI and ML and expand the expert pool. Or the toolchain may mature to enable lesser-skilled developers to build new models. In the meantime, the limited pool of experts will be leveraged to deliver the greatest impact.

 

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