November 2017
Volume 32 Number 11
[Editor’s Note]
Get Smart
By Michael Desmond | November 2017
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Artificial intelligence (AI). Machine learning (ML). Data science. Terms like these have been cropping up more and more lately in MSDN Magazine, and for good reason. The confluence of cloud computing, Big Data and advances in deep learning algorithms has opened new horizons for developers, as tools emerge to wire up intelligent systems that drive insight, improve decision making and speed execution.
In July, we published a package of four feature articles focused on ML, including Wee Hyong Tok’s “Doing Data Science and AI with SQL Server” (msdn.com/magazine/mt784663) and James McCaffrey’s “Introduction to the Microsoft CNTK v2.0 Library” (msdn.com/magazine/mt784662). Microsoft Cognitive Services has been the subject of exploration, from contributors like Alessandro Del Sole (“Face and Emotion Recognition in Xamarin.Forms with Microsoft Cognitive Services” msdn.com/magazine/mt742868) and in this issue, Ashish Sahu’s “From Text to Targeted Sentiment Analysis with Cognitive Services.”
The amount of activity in the AI/ML space is both impressive and maddening, as evidenced by announcements at the Microsoft Ignite conference in September. Microsoft Azure Machine Learning Studio, released in 2015, has emerged as the go-to tool for rapid development and system interaction via Web services. But the drive for more control over both algorithms and frameworks, combined with limitations in model deployments, prompted Microsoft to release new solutions, like Azure Machine Learning with its Workbench client, Experimentation Service and Model Management Service. At Ignite Microsoft also announced Visual Studio Code Tools for AI alongside updates to Cognitive Services.
The tools are evolving fast, opening powerful new capabilities even as they force developers to retool and retrain on-the-fly. To quote Ron Burgundy in the movie “Anchorman,” after he discovers that his dog Baxter has eaten an entire wheel of cheese: “I’m not even mad. That’s amazing.”
To help readers keep up, MSDN Magazine last month debuted a new column focused on AI and ML, called Artificially Intelligent (msdn.com/magazine/mt826348). The author, Frank La Vigne, has been writing the Modern Apps column focused on Universal Windows Platform (UWP) development, but now shifts his sights to AI. It’s an arena he’s been active in since he attended the Data Science and Machine Learning Summit in 2016 on the Microsoft campus. He came away convinced that Microsoft was “planning to integrate AI into every facet of the company,” and immediately immersed himself in the space.
La Vigne says Microsoft’s AI strategy is shaped by its historical focus on putting powerful tools into the hands of users.
“I think the overall theme of Microsoft’s products through the years has been democratization, whether that’s making developer tools or office productivity tools. The same holds true here, making machine learning and AI more accessible to developers,” La Vigne says, singling out the Cognitive Services support for computer vision and natural language processing.
As for what it takes for developers to thrive in the AI/ML space, La Vigne says it comes down to a commitment to constant learning.
“Microsoft really has to sell developers and data engineers that data science, AI and ML is not some big, scary, hyper-nerd technology. There are corners where that is true, but this field is open to anyone that is willing to learn,” La Vigne says. “In fact, anyone who is already a developer or engineer clearly already has the core capabilities to be successful in this field. All people need to do is level up some of their skills and add new ones.”
Michael Desmond is the Editor-in-Chief of MSDN Magazine.