Microsoft Research Podcast

This episode originally aired in May, 2019.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.

Dr. Sébastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.

Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.

This episode first aired in November, 2018.

Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.

Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.

https://www.microsoft.com/research

With all the buzz surrounding AI, it can be tempting to envision it as a stand-alone entity that optimizes for accuracy and displaces human capabilities. But Dr. Besmira Nushi, a senior researcher in the Adaptive Systems and Interaction group at Microsoft Research, envisions AI as a cooperative entity that enhances human capabilities and optimizes for team performance.

On today’s podcast, Dr. Nushi talks about what it takes to develop collaborative AI systems and unpacks the unique challenges machine learning engineers face in their version of the software development cycle. She also reveals why understanding the “terrain of failure” can help researchers develop AI systems that perform as well in the real world as they do in the lab.

https://www.microsoft.com/research

Deep learning methodologies like supervised learning have been very successful in training machines to make predictions about the world. But because they’re so dependent upon large amounts of human-annotated data, they’ve been difficult to scale. Dr. Phil Bachman, a researcher at MSR Montreal, would like to change that, and he’s working to train machines to collect, sort and label their own data, so people don’t have to.

Today, Dr. Bachman gives us an overview of the machine learning landscape and tells us why it’s been so difficult to sort through noise and get to useful information. He also talks about his ongoing work on Deep InfoMax, a novel approach to self-supervised learning, and reveals what a conversation about ML classification problems has to do with Harrison Ford’s face.

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There’s a lot of excitement around self-driving cars, delivery drones, and other intelligent, autonomous systems, but before they can be deployed at scale, they need to be both reliable and safe. That’s why Gurdeep Pall, CVP of Business AI at Microsoft, and Dr. Ashish Kapoor, who leads research in Aerial Informatics and Robotics, are using a simulated environment called AirSim to reduce the time, cost and risk of the testing necessary to get autonomous agents ready for the open world.

Today, Gurdeep and Ashish discuss life at the intersection of machine learning, simulation and autonomous systems, and talk about the challenges we face as we transition from a world of automation to a world of autonomy. They also tell us about Game of Drones, an exciting new drone racing competition where the goal is to imbue flying robots with human-level perception and decision making skills… on the fly.

https://www.microsoft.com/research

Dr. Sumit Gulwani is a programmer’s programmer. Literally. A Partner Research Manager in the Program Synthesis, or PROSE, group at Microsoft Research, Dr. Gulwani is a leading researcher in program synthesis and the inventor of many intent-understanding, programming-by-example and programming-by-natural language technologies – aka, the automation of “what I meant to do and wanted to do, but my computer wouldn’t let me” tasks.

Today, Dr. Gulwani gives us an overview of the exciting “now” and promising future of program synthesis; reveals some fascinating new applications and technical advances; tells us the story behind the creation of Excel’s popular Flash Fill feature (and how a Flash Fill Fail elicited a viral tweet that paved the way for new domain investments); and shares a heartwarming story of how human empathy facilitated an “ah-ha math moment” in the life of a child, and what that might mean to computer scientists, educators and even tech companies in the future.

https://www.microsoft.com/research

Computer programming has often been perceived as the exclusive domain of computer scientists and software engineers. But that’s changing, thanks to the work of people like Dr. Thomas Ball, a Partner Researcher in the RiSE group at Microsoft Research, and Dr. Teddy Seyed, a post-doctoral researcher in the same group. Their goal is to make programming accessible to non-programmers in places like the classroom, the workshop… and even the runway!

On today’s podcast, Tom and Teddy talk about physical computing through platforms like MakeCode, a simplified programming environment that makes it easier for young people – and other computer science neophytes – to start coding with programmable microcontrollers. They also tell us all about Project Brookdale, where they did a collaborative fashion show that gave emerging designers the tools to embed technology in their garments and produce wearables you’d actually want to be seen in!

https://www.microsoft.com/research

Remember when a hard drive that could hold a terabyte of data was a big deal? Well, we’re now in an era where peta-, exa- and even zetta-bytes are the bytes of the day, and it turns out it’s hard to fit that many zeroes on a hard drive. That’s where Dr. Ant Rowstron, Deputy Lab Director of Microsoft Research Cambridge, and Mark Russinovich, Chief Technical Officer of Azure, come in. Their respective teams are working on paradigm-breaking solutions to give us phenomenal storage power in an itty-bitty living space.

Today, Ant and Mark discuss their roles in the development of new optical technologies, like Project Silica, for cloud-scale storage demands, and talk about the Optics for the Cloud Research Alliance, an exciting new collaboration between academic researchers and MSR. They also explain how just the right mix of innovation and engineering can make the cloud more powerful and less expensive to use and, at the same time, deliver “forever” storage that’s both dishwasher and microwave safe!

https://www.microsoft.com/research

Jenny Sabin is an architectural designer, a professor, a studio principal and MSR’s current Artist in Residence. Asta Roseway is a principal research designer, a “fusionist” and the co-founder of the Artist in Residence program at Microsoft Research. The two, along with a stellar multi-disciplinary team, recently completed the installation of Ada, the first interactive architectural pavilion powered by AI, in the heart of the Microsoft Research building in Redmond.

On today’s podcast, Jenny and Asta talk about life at the intersection of art and science; tell us why the Artist in Residence program pushes the boundaries of technology in unexpected ways; and reveal their vision of the future of bio-inspired, human-centered, AI-infused architecture.

https://www.microsoft.com/research