Azure CTO: Open Source Is Key to Machine Learning in the Cloud, or on the Edge - The New Stack

In this interview recorded at the Open Source Leadership Summit, Azure CTO Mark Russinovich and The New Stack's founder Alex Williams discussed how Microsoft builds on and contributes to open source for Azure's artificial intelligence (AI) and machine learning. As Russinovich -- who had just given a keynote suggesting that AI owes its current strength to the combination of open source and the cloud -- explained, "Fundamentally a lot of AI, machine learning and analytics is built on top of open source and it's a key part of our strategy to build with and use that open source, as well as to contribute back and to add to open source." Examples of that range from Microsoft contributing its own enhancements and fixes to existing projects like YARN (which is used in Azure Data Lake Analytics), to supporting the R open source community, to working with Facebook and AWS on the ONNX project to exchange models between Caffe, MXNet and CNTK, Microsoft's own deep learning framework -- which is also open source. "CNTK is our own intellectual property; it's a differentiated convolutional neural network framework… that we developed internally for Bring. We use that internally for a lot of our cognitive APIs… and we contributed that to [the] open source [community]," Russinovich explained.