AI News, What’s New in Azure Machine Learning?

What’s New in Azure Machine Learning?

Matt Winkler delivered a talk at Microsoft Build 2018 explaining what is new in Azure Machine Learning.

You can deploy AI everywhere, to the cloud, on premise, in a remote facility with no internet connectivity, or to edge devices such as tractors, sensors, or cameras.

The new improvements come in several areas: making development easier, single container deployment to make the dev/test loop faster, using the SDK from the Azure Notebook for control, as well as helping people get started solving a particular problem.

To solve these problems, Microsoft has put several items in preview today: Project Brainware hardware accelerated models, Azure ML packages, for vision, text, and forecasting, the ONNX model gallery, an updated SDK to improve Azure notebooks, hyperparameter turning services, the addition of ACI/AKS batch AI compute targets, and IOT deployment enhancements.

This can give you real time AI at cloud scale with industry leading performance at low cost.

The common interchange format ONNX allows you to use the models in various places such as inside an application, or to deploy it to services.

These improvements make it easier to provision compute targets, run training jobs local on the notebook, or a large scale cluster.

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