In this article from VentureBeat, read about Scott Guthrie’s excitement about ONNX.

“Even today with the ONNX workloads for AI, the compelling part is you can now build custom models or use our models, again using TensorFlow, PyTorch, Keras, whatever framework you want, and then know that you can hardware-accelerate it whether it’s on the latest Nvidia GPU, whether it’s on the new AMD GPUs, whether it’s on Intel FPGA, whether it’s on someone else’s FPGA or new silicon we might release in the future. That to me is more compelling than ‘do we have a better instruction set at the hardware level’ and generally what I find resonates best with customers.”

Ahead of the Build 2019 developer summit this week, Microsoft reiterates its commitment to machine learning developer productivity.

“Furthering our commitment to building the most productive AI platform, we’re delivering key new innovations in Azure Machine Learning that simplify the process of building, training, and deployment of machine learning models at scale,” wrote Microsoft cloud and AI group executive vice president Scott Guthrie in a blog post. “Today we’re delivering innovative Azure services for developers to build the next generation of apps. With 95% of Fortune 500 customers running on Azure, these innovations can have far-reaching impact.”