Intrepid Ignite 2019 attendees navigated over 1500 sessions and a mind-numbing number of announcements as Microsoft flexed the full breadth of its technological capabilities in Orlando, Fla. last week. The show saw progress across cloud and edge computing, security and management, software development and modern workplace to name a few. And while announcements in these areas garnered much of the limelight, a crucial area that received less notice was AI.
Let's explore the moves and discuss what they mean for Microsoft and the nascent enterprise AI market moving forward.
The Big Headlines Out of Microsoft Ignite
First, a quick recap of some key announcements and areas that took most of the attention this year.
Azure Arc was Ignite’s most eye-catching announcement. It revealed Microsoft is now doubling down on hybrid and multi-cloud management, representing the biggest shift yet in Azure’s strategic evolution. Azure Arc follows similar investments made by Google Cloud with Anthos and IBM Red Hat over the past 18 months. It is an indicator that the competition in cloud computing is shifting to the control plane. It will be fascinating to see if AWS follows suit with an update to Outposts next month at re:Invent.
Power Platform, the citizen developer tool, also received a ton of focus from Microsoft this year. The low-code, no-code platform has grown to become one of Redmond’s most important strategic assets. Ignite not only showed how Power Platform is helping Microsoft reach new enterprise developers, but is helping enhance the customization and stickiness of its SaaS products such as Teams and Dynamics as well. It will be a vital weapon against Salesforce, SAP, Google G-Suite and Slack in the future.
And as expected, Microsoft 365 was dominant as well, with Teams in particular generating over 50 breakout sessions alone at the event. The arrival of Project Cortex and Microsoft End Point Manager into Microsoft 365 are examples of how it is progressing from the commercial bundle it was upon its 2017 launch to a more cohesive platform.
Related Article: Microsoft Project Cortex Ushers in the Age of Topic Computing
What You May Have Missed From Ignite's AI Announcements
Against this backdrop of critical areas, it is unsurprising why AI felt like it took a bit of a backseat this year. But that doesn’t mean Microsoft’s AI updates were any less important.
Big Data and Analytics: Azure Synapse Analytics
One of the main blockers of AI in enterprises at the moment is data quality. Satya Nadella's keynote featured the launch of Azure Synapse Analytics, a new big data analytics service, which combines cloud-based serverless computing resources with on premises infrastructure for a unified experience across data ingestion, prep and management. In a breakout session, corporate vice president of Azure Data, Rohan Kumar stated the solution was a staggering 75 times faster than Google’s BigQuery service and three times faster than Amazon’s Red Shift. The solution also integrates with Azure Machine Learning.
The performance and trust in AI depends entirely on the quality of the data tools and practices that companies feed into it. The new service is an important move that should become a crucial focal point for Microsoft's AI initiatives over the next 12 months.
AI and Industrial Robotics with Autonomous Systems
Another important area was the expansion of Microsoft’s preview program for Autonomous Systems, Redmond’s incubation project for its machine teaching and reinforcement learning solutions aimed at mechanical and chemical engineers who build industrial systems and robotics.
Based on the Bonsai acquisition last year, the autonomous systems platform helps engineers build intelligent machines that go beyond basic automation to be able sense, learn and respond to changes in their environments through AI. For example, researchers at Carnegie Mellon University used the platform to train perception and object detection models deployed on robots used to tackle search and rescue operations in mines. At the event, Microsoft demonstrated the technology with an air hockey playing robot at the Autonomous Systems booth which you can see in action below.
Microsoft also announced several partnerships in this area including ones with MathWorks, AnyLogic and CGTech, whose simulators are used by engineers worldwide. Other partnerships with solution providers Fresh Consulting, Neal Analytics, and enterprise drone software maker 3-D Robotics were also announced.
Autonomous systems is a fascinating part of Microsoft’s business that is worth watching. Along with the traditional developers, data scientists and business users who have been the man focus of cloud vendors, engineers will be important users of AI tools in the future. When combined with its hybrid cloud, edge and IoT offerings, the platform is part of a bigger play which could make Microsoft more relevant in industrial environments, plant operations and in operations technology in the future. This is a large, untapped opportunity for Microsoft down the road.
But Microsoft is not alone in eyeing the potential of this area. AWS is using the warehouse operations of its retail arm to incubate its AI for industrial environments. Last year’s launch of AWS RoboMaker for example illustrates the company's intent here. Additionally, Google’s DeepMind is concentrating research into this field.
As the worlds of industrial robotics and AI collide over the coming years, it will be interesting to see which cloud vendor will best marry the IT and OT environments.
Azure Machine Learning Goes Deeper into Responsible AI
The biggest area of development however was in Azure Machine Learning (Azure ML), which received a number of updates, most notable of which were in the area of responsible AI.
One of the main reasons why AI hasn’t yet shifted out of the labs and into everyday workplace life is because companies need more support with its governance. Many firms I speak to need better answers to important questions before they fully operationalize the technology, such as: “How do I design ethical applications for my business? How do I avoid bias in my data? How can I ensure the models I build are explainable and interpretable to third parties including business users, not just my developer or data science teams? How can I guarantee that algorithms I deploy respect privacy and are secure and compliant for the industry I operate in?”
Aimed at tackling these challenges, Microsoft announced a set of new governance features in its lifecycle management platform MLOps in Azure ML. These included role-based access controls, virtual network security, dataset and model traceability and auditing, data drift monitoring and above all, new solutions for interpretability and bias detection.
Microsoft stated it would integrate its open source tool for model explainability, “Interpret ML,” into Azure ML and showcased several new dashboards for model interpretability that are now in the platform. Finally, it announced “Fairlearn,” a new toolkit for bias detection and mitigation in GitHub, which, through a set of visualizations, helps uncover insights into fairness in model predictions.
Responsible AI and governance have become the most important topics in the AI market in 2019. According to my firm, CCS Insight's 2019 survey of senior IT decision-makers, for example, the level of transparency of how systems work and are trained and the ability of AI systems to ensure data security and privacy are now the two most important requirements when investing in AI and machine learning technology, cited by almost 50% of respondents. The survey also found that 43% of respondents list tools that support AI operations and lifecycle management as being the biggest current gap in the market for suppliers of AI platforms.
Microsoft’s push into these key arenas is ahead of several of its main competitors at the moment, but it must work harder to raise awareness of these capabilities if it is to lead the market in trusted AI.
Related Article: From the Lab to Real Life: Operationalizing AI and Data Analytics
Microsoft's Flywheel Is Gathering Momentum
Ignite showcased the enviable "flywheel" effect occurring across Microsoft at the moment, as its tightly aligned cloud infrastructure, security and applications businesses continue to accelerate.
At the center of this flywheel is AI. And although it may not have garnered as many of the headlines this year, altogether, Microsoft’s progress in data analytics, autonomous systems and responsible AI represent some of the event’s dark horse announcements in my view.
Microsoft is making ground against the competition, having reported in its first quarter earnings last month that 20,000 customers are now using Azure AI, including over 85% of the Fortune 100. This marked the first time the company shared its AI customer numbers.
At this point Microsoft needs to shout louder about its achievements — before the competition closes the gaps.