AI, Machine Learning and Data Science Announcements from Microsoft Ignite

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Microsoft Ignite, Microsoft's annual developer conference, wrapped up last week and many of the big announcements focused on artificial intelligence and machine learning. The keynote presentation from Microsoft's Cloud AI lead Eric Boyd showcases the major developments, or you can check out his accompanying blog post for a written summary. 

In this post, I'll dive down into the details of the specific announcements and provide links to the associated recorded presentations from Ignite and other technical documents.

Tools for AI developers

Azure Machine Learning Service (Azure ML) adds several new capabilities. These include a new Python package that developers can use to prepare data for analysis, automate machine learning and deep learning model training, track model performance under various conditions, and automate the model selection process (see below). It supports a variety of execution environments, from local desktops to GPU clusters, and deploy trained models with containers or even high-performance FPGA chips.  (The desktop “Workbench” client, previously in preview, is no longer required and has been deprecated.) Watch the Ignite presentation AI with Azure Machine Learning services: Simplifying the data science process for an overview and demo.

Automated Machine Learning, a new Azure ML service in preview, automates the selection of machine learning algorithms (and associated parameters and hyperparameters) to optimize predictive performance. This blog post provides the technical details, and another blog post describes some practical applications. A Microsoft Research paper describes the probabilistic matrix factorization technique behind the optimization. This Ignite presentation provides further details and includes a demo.  

Visual Studio Code Tools for AI has been updated to provide a convenient interface to Azure ML for users of the popular open-source editor.

SQL Server 2019 is now in public preview, with many improvements shown in this Ignite keynote. Updates include Spark support, and added Linux support for in-database R and Python (watch this Ignite presentation for details).

Azure Databricks is now supported in more regions, offers GPU support for deep learning, and Databricks Delta is now available (in preview) for transactional data capabilities.

Customized AI

Microsoft Bot Framework SDK v4 is now available. The Ignite presentation “Creating Enterprise-Scale Intelligent Agents and Bots” provides an overview and several examples.

Cortana Skills Kit for Enterprise, a development platform based on Azure Bot Service and Language Understanding is now in private preview.  

Pre-trained AI

Speech Service in Azure Cognitive Services is now generally available, and includes a new neural text-to-speech capability for humanlike synthesized speech. This Ignite presentation provides an overview.

This Ignite presentation provides an overview of Cognitive Services with some demos with applications of the pre-trained AI capabilities for computer vision, speech, search and more.


AI for Humanitarian Action announced. With this new AI for Good program, MIcrosoft will dedicate $40m over five years to deploy AI technologies to assist with disaster recovery; the needs of children, refugees and displaced people; and human rights. A short video summarizes the initiative.

And that's just the highlights — for example, I haven't included the many AI capabilities added to products like Windows and Office. (However I can't resist mentioning the new Insert Data from Picture feature in Excel, which I'm sure I'll be making a lot of use of.) For more from Ignite, take a look at Buck Woody's index of presentations at Ignite, with highlights of videos focused on AI, machine learning, and data science.

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