Microsoft Research Podcast

This episode first aired in November (2017). Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.

In technical terms, computer vision researchers “build algorithms and systems to automatically analyze imagery and extract knowledge from the visual world.” In layman’s terms, they build machines that can see. And that’s exactly what Principal Researcher and Research Manager, Dr. Gang Hua, and Computer Vision Technology team, are doing. Because being able to see is really important for things like the personal robots, self-driving cars, and autonomous drones we’re seeing more and more in our daily lives.

Today, Dr. Hua talks about how the latest advances in AI and machine learning are making big improvements on image recognition, video understanding and even the arts. He also explains the distributed ensemble approach to active learning, where humans and machines work together in the lab to get computer vision systems ready to see and interpret the open world.

When we think of medals, we usually picture them over the pocket of a military hero, not over the pocket protector of a computer scientist. That may be because not many academics end up working with the Department of Defense. But Dr. Chris White, now a Principal Researcher at Microsoft Research, has, and he’s received several awards for his efforts in fighting terrorism and crime with big data, statistics and machine learning.

Today, Dr. White talks about his “problem-first” approach to research, explains the vital importance of making data understandable for everyone, and shares the story of how a one-week detour from academia turned into an extended tour in Afghanistan, a stint at DARPA, and, eventually, a career at Microsoft Research.

In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.

Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

With 7 billion people on the planet, you might be surprised to learn that approximately a billion of those people experience some form of disability. Enter Principal Researcher and Research Manager, Dr. Merrie Ringel Morris, and the Ability Group at Microsoft Research. They’re working to remove accessibility barriers both to and through technology, empowering people with disabilities to better perform their daily tasks.

Today, Dr. Morris gives us some fascinating insights into the world of “ability,” talks about how technology is augmenting not only sensory and motor abilities, but cognitive and social abilities as well, and shares how Microsoft, through its AI for Accessibility initiative, is committed to extending the capabilities and enhancing the quality of life for every person on the planet.