Microsoft Research Podcast

When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming. Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your Wi-Fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions. Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.

Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers. Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.  

  There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it. Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.

  Artificial intelligence has captured our imagination and made many things we would have thought impossible only a few years ago seem commonplace today. But AI has also raised some challenging issues for society writ large. Enter Dr. Kate Crawford, a principal researcher at the New York City lab of Microsoft Research. Dr. Crawford, along with an illustrious group of colleagues in computer science, engineering, social science, business and law, has dedicated her research to addressing the social implications of AI, including big topics like bias, labor and automation, rights and liberties, and ethics and governance. Today, Dr. Crawford talks about both the promises and the problems of AI; why— when it comes to data – bigger isn’t necessarily better; and how – even in an era of increasingly complex technological advances – we can adopt AI design principles that empower people to shape their technical tools in ways they’d like to use them most.

  With all the sensational headlines about artificial intelligence, it’s reassuring to know that some of the world’s most brilliant minds are developing AI systems for entirely practical reasons. One of those minds belongs to Dr. Antonio Criminisi, a Principal Researcher at Microsoft Research in Cambridge, England. And one of those reasons is to help medical professionals provide better healthcare to their patients.Today, Dr. Criminisi talks about Project InnerEye, an innovative machine learning tool that helps radiologists identify and analyze 3-D images of cancerous tumors. He also gives us some insight into his work on deep neural decision forests and tells us how gaming algorithms made their way into medical technology, moving from gamer to patient, and turning outside-in imaging… inside-out.  

  If you’ve ever wondered if you could find the perfect combination of computer scientist… and Macgyver, look no further than Dr. Peli de Halleux, principal Research Software Design Engineer at Microsoft Research. A key member of the MSR RiSE team, Peli is part of the MakeCode initiative that brings physical computing to classrooms around the country and around the world. Today, Peli talks about the Maker Movement in K-12 education, the hard work that goes on behind the scenes to deliver a “seamless” user experience for both kids and teachers, and how to get children excited about coding through hands on experience in early computer science education.

Big data is a big deal, and if you follow the popular technical press, you’ll have heard all the metaphors: data is the new oil, the new bacon, the new currency, the new electricity. It’s even been called the new black. While data may not actually be any of these things, we can say this: in today’s networked world, data is increasingly valuable and it is essential to research, both basic and applied. Today, we welcome a special guest to the podcast. Dr. Igor Perisic is the Vice President of Engineering and Chief Data Officer at LinkedIn, the social network for business and employment. Today, Dr. Perisic talks about the key attributes of a data scientist, how AI and machine learning are helping personalize member experiences, why we should all be big open source fans, and how LinkedIn is partnering with other researchers through their innovative Economic Graph program to create economic opportunity for every member of the global workforce. All this and much more on this episode of the Microsoft Research Podcast.

Every day, computers take on more and more of our daily tasks. Fill in a few cells on your spreadsheet? It’ll fill in the rest. Ask your car for directions? It’ll get you there. Anymore, we can program computers to do almost anything. But what about programming computers to… program computers? That’s a task that Dr. Rishabh Singh, and the team in the Cognition group at Microsoft Research, are tackling with Neural Program Synthesis, also known as artificial programming. Today, Dr. Singh explains how deep neural networks are already training computers to do things like take classes and grade assignments, shares how programmers can perform complicated, high-level debugging through the delightfully named process of neural fuzzing, and lays out his vision to democratize computer programming in the brave new world of Software 2.0.

  As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it. Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”

  If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC - group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality. Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.

  When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.       Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.

In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is a… programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

In a wide-ranging interview, veteran Microsoft Researcher, Dr. Steven Drucker talks about his work in data visualization, the importance of clear communication in a world of complex algorithms and big data, and the long, slow work of big breakthroughs. He also offers some pro-tips to aspiring researchers, and tells us why stand-up comedy is an important skill for computer scientists.

On today’s episode, neuroscientist and virtual reality researcher, Dr. Mar Gonzalez Franco, talks about her work in VR, explains how avatars can help increase our empathy and reduce our biases via role play, and addresses the misconceptions that exist between the immersive experiences of virtual reality and psychedelic drugs.