Microsoft Research Podcast

If you’ve recently found it more difficult to focus your attention for a lengthy stretch of time in order to get a complex task done… or worse, found it difficult even to find a lengthy stretch of time in which to try, you’re not alone. And actually, you’re in luck. Dr. Shamsi Iqbal, a senior researcher in the Information and Data Sciences group at Microsoft Research, wants to help you manage your attention better and be more productive at the same time. And she’s using technology to do it!

On today’s podcast, Dr. Iqbal tells us about her work in the field of micro-productivity, a line of research that takes aim at the short spurts of time she calls micro-moments that we otherwise might have considered too short to get anything useful done. She also explains why distraction can be good for us and gives us some advice on how to make the most of our cognitive resources, whether by setting aside time to tackle big tasks in the traditional way or by breaking them down into micro-tasks… and “outsourcing” them to ourselves!

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.

Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.

On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

When was the last time you had a meaningful conversation with your computer… and felt like it truly understood you? Well, if Dr. Xuedong Huang, a Microsoft Technical Fellow and head of Microsoft’s Speech and Language group, is successful, you will. And if his track record holds true, it’ll be sooner than you think!

On today’s podcast, Dr. Huang talks about his role as Microsoft’s Chief Speech Scientist, gives us some inside details on the latest milestones in speech and language technology, and explains how mastering speech recognition, translation and conversation will move machines further along the path from “perceptive AI” to “cognitive AI” and that much closer to truly human intelligence.

Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.

Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

If you want to know what’s going on in the world of human computer interaction research, or what’s new at the CHI Conference on Human Factors in Computing Systems, you should hang out with Dr. Ken Hinckley, a principal researcher and research manager in the EPIC group at Microsoft Research, and Dr. Merrie Ringel Morris, a principal researcher and research manager in the Ability group. Both are prolific HCI researchers who are seeking, from different angles, to augment the capability of technologies and improve the experiences people have with them.

On today’s podcast, we get to hang out with both Dr. Hinckley and Dr. Morris as they talk about life at the intersection of hardware, software and human potential, discuss how computers can enhance human lives, especially in some of the most marginalized populations, and share their unique approaches to designing and building technologies that really work for people and for society.

In the world of relational databases, structured query language, or SQL, has long been King of the Queries, primarily because of its ubiquity and unparalleled performance. But many users prefer a mix of imperative programming, along with declarative SQL, because its user-defined functions (or UDFs) allow for good software engineering practices like modularity, readability and re-usability. Sadly, these benefits have traditionally come with a huge performance penalty, rendering them impractical in most situations. That bothered Dr. Karthik Ramachandra, a Senior Applied Scientist at Microsoft Research India, so he’s spent a great deal of his career working on improving an imperative complement to SQL in database systems.

Today, Dr. Ramachandra gives us an overview of the historic trade-offs between declarative and imperative programming paradigms, tells us some fantastic stories, including The Tale of Two Engineers and The UDF Story, Parts 1 and 2, and introduces us to Froid – that’s F-R-O-I-D, not the Austrian psychoanalyst – which is an extensible, language-agnostic framework for optimizing imperative functions in databases, offering the benefits of UDFs without sacrificing performance.

We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.

Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

Dr. Marc Pollefeys is a Professor of Computer Science at ETH Zurich, a Partner Director of Science for Microsoft, and the Director of a new Microsoft Mixed Reality and AI lab in Switzerland. He’s a leader in the field of computer vision research, but it’s hard to pin down whether his work is really about the future of computer vision, or about a vision of future computers. Arguably, it’s both!

On today’s podcast, Dr. Pollefeys brings us up to speed on the latest in computer vision research, including his innovative work with Azure Spatial Anchors, tells us how devices like Kinect and HoloLens may have cut their teeth in gaming, but turned out to be game changers for both research and industrial applications, and explains how, while it’s still early days now, in the future, you’re much more likely to put your computer on your head than on your desk or your lap.

Ann Paradiso is an interaction designer and the Principal User Experience Designer for the NExT Enable group at Microsoft Research. She’s also the epitome of a phrase she often uses to describe other people: a force of nature. Together with a diverse array of team members and collaborators, many of whom have ALS or other conditions that affect mobility and speech, Ann works on new interaction paradigms for assistive technologies hoping to make a more bespoke approach to technology solutions accessible, at scale, to the people who need it most.

On today’s podcast, Ann tells us all about life in the extreme constraint design lane, explains what a PALS is, and tells us some incredibly entertaining stories about how the eye tracking technology behind the Eye Controlled Wheelchair and the Hands-Free Music Project has made its way from Microsoft’s campus to some surprising events around the country, including South by Southwest and Mardi Gras.