title

Microsoft Research Podcast

Gretchen Huizinga, podcast host

38
Followers
50
Plays
Microsoft Research Podcast

Microsoft Research Podcast

Gretchen Huizinga, podcast host

38
Followers
50
Plays
OVERVIEWEPISODESYOU MAY ALSO LIKE

Details

About Us

An ongoing series of conversations bringing you right up to the cutting edge of Microsoft Research.

Latest Episodes

107 - Democratizing data, thinking backwards and setting North Star goals with Dr. Donald Kossmann

Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research’s flagship lab in Redmond, it’s his job to inspire others to think big, too. But don’t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path. On today’s podcast, Dr. Kossmann reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science… with marketing. https://www.microsoft.com/research

33 MINFEB 19
Comments
107 - Democratizing data, thinking backwards and setting North Star goals with Dr. Donald Kossmann

106 - Microsoft Scheduler and dawn of Intelligent PDAs with Dr. Pamela Bhattacharya

In a world where productivity is paramount and only a handful of people have personal assistants, many of us are frustrated by the amount of time we spend in meetings, and worse, the amount time we spend planning, scheduling and rescheduling those meetings! Fortunately, Dr. Pamela Bhattacharya, a Principal Applied Scientist in Microsoft’s Outlook group, wants to turn your email into your own personal assistant. And a smart one at that! Today, Dr. Bhattacharya tells us all about Scheduler, Microsoft’s virtual personal assistant, and how her team is using machine learning to put the “I” in intelligent PDAs. She also talks about how understanding different levels of automation can help us set the right expectations for our experience with AI, and explains how, in the workplace of the future, we might actually achieve more by doing less. https://www.microsoft.com/research

-1 sFEB 12
Comments
106 - Microsoft Scheduler and dawn of Intelligent PDAs with Dr. Pamela Bhattacharya

105 - Responsible AI with Dr. Saleema Amershi

There’s an old adage that says if you fail to plan, you plan to fail. But when it comes to AI, Dr. Saleema Amershi, a principal researcher in the Adaptive Systems and Interaction group at Microsoft Research, contends that if you plan to fail, you’re actually more likely to succeed! She’s an advocate of calling failure what it is, getting ahead of it in the AI development cycle and making end-users a part of the process. Today, Dr. Amershi talks about life at the intersection of AI and HCI and does a little AI myth-busting. She also gives us an overview of what – and who – it takes to build responsible AI systems and reveals how a personal desire to make her own life easier may make your life easier too. https://www.microsoft.com/research

-1 sFEB 5
Comments
105 - Responsible AI with Dr. Saleema Amershi

104 - Going deep on deep learning with Dr. Jianfeng Gao

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! https://www.microsoft.com/research

39 MINJAN 29
Comments
104 - Going deep on deep learning with Dr. Jianfeng Gao

103 - Innovating in India with Dr. Sriram Rajamani

Dr. Sriram Rajamani is a Distinguished Scientist and the Managing Director of the Microsoft Research lab in Bangalore. He’s dedicated his career to advancing globally applicable science in the testbed that is India. He is, by any measure, a world-class researcher and leader. He’s also, as you’ll find out shortly, a world-class storyteller! Today, Dr. Rajamani talks about the unique challenges and opportunities of leading MSR’s research efforts in India and what it takes to build a robust research ecosystem in a country of huge disparities. He also dispels some preconceptions about poor and marginalized populations and explains why ‘frugal innovation’ may be one key to solving societal scale problems. https://www.microsoft.com/research

-1 sJAN 22
Comments
103 - Innovating in India with Dr. Sriram Rajamani

078r - Machine teaching with Dr. Patrice Simard

This episode originally aired in May, 2019. 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-...

-1 sJAN 15
Comments
078r - Machine teaching with Dr. Patrice Simard

077r - The productive software engineer with Dr. Tom Zimmermann

This episode originally aired in May, 2019. 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!

-1 sJAN 8
Comments
077r - The productive software engineer with Dr. Tom Zimmermann

075r - Reinforcement learning for the real world with Dr. John Langford and Rafah Hosn

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 “resear...

-1 sJAN 1
Comments
075r - Reinforcement learning for the real world with Dr. John Langford and Rafah Hosn

053r - Chasing convex bodies and other random topics with Dr. Sébastien Bubeck

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. https://www.microsoft.com/research

-1 s2019 DEC 25
Comments
053r - Chasing convex bodies and other random topics with Dr. Sébastien Bubeck

052r - Chris Bishop

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

34 MIN2019 DEC 18
Comments
052r - Chris Bishop

Latest Episodes

107 - Democratizing data, thinking backwards and setting North Star goals with Dr. Donald Kossmann

Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research’s flagship lab in Redmond, it’s his job to inspire others to think big, too. But don’t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path. On today’s podcast, Dr. Kossmann reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science… with marketing. https://www.microsoft.com/research

33 MINFEB 19
Comments
107 - Democratizing data, thinking backwards and setting North Star goals with Dr. Donald Kossmann

106 - Microsoft Scheduler and dawn of Intelligent PDAs with Dr. Pamela Bhattacharya

In a world where productivity is paramount and only a handful of people have personal assistants, many of us are frustrated by the amount of time we spend in meetings, and worse, the amount time we spend planning, scheduling and rescheduling those meetings! Fortunately, Dr. Pamela Bhattacharya, a Principal Applied Scientist in Microsoft’s Outlook group, wants to turn your email into your own personal assistant. And a smart one at that! Today, Dr. Bhattacharya tells us all about Scheduler, Microsoft’s virtual personal assistant, and how her team is using machine learning to put the “I” in intelligent PDAs. She also talks about how understanding different levels of automation can help us set the right expectations for our experience with AI, and explains how, in the workplace of the future, we might actually achieve more by doing less. https://www.microsoft.com/research

-1 sFEB 12
Comments
106 - Microsoft Scheduler and dawn of Intelligent PDAs with Dr. Pamela Bhattacharya

105 - Responsible AI with Dr. Saleema Amershi

There’s an old adage that says if you fail to plan, you plan to fail. But when it comes to AI, Dr. Saleema Amershi, a principal researcher in the Adaptive Systems and Interaction group at Microsoft Research, contends that if you plan to fail, you’re actually more likely to succeed! She’s an advocate of calling failure what it is, getting ahead of it in the AI development cycle and making end-users a part of the process. Today, Dr. Amershi talks about life at the intersection of AI and HCI and does a little AI myth-busting. She also gives us an overview of what – and who – it takes to build responsible AI systems and reveals how a personal desire to make her own life easier may make your life easier too. https://www.microsoft.com/research

-1 sFEB 5
Comments
105 - Responsible AI with Dr. Saleema Amershi

104 - Going deep on deep learning with Dr. Jianfeng Gao

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI. Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way! https://www.microsoft.com/research

39 MINJAN 29
Comments
104 - Going deep on deep learning with Dr. Jianfeng Gao

103 - Innovating in India with Dr. Sriram Rajamani

Dr. Sriram Rajamani is a Distinguished Scientist and the Managing Director of the Microsoft Research lab in Bangalore. He’s dedicated his career to advancing globally applicable science in the testbed that is India. He is, by any measure, a world-class researcher and leader. He’s also, as you’ll find out shortly, a world-class storyteller! Today, Dr. Rajamani talks about the unique challenges and opportunities of leading MSR’s research efforts in India and what it takes to build a robust research ecosystem in a country of huge disparities. He also dispels some preconceptions about poor and marginalized populations and explains why ‘frugal innovation’ may be one key to solving societal scale problems. https://www.microsoft.com/research

-1 sJAN 22
Comments
103 - Innovating in India with Dr. Sriram Rajamani

078r - Machine teaching with Dr. Patrice Simard

This episode originally aired in May, 2019. 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-...

-1 sJAN 15
Comments
078r - Machine teaching with Dr. Patrice Simard

077r - The productive software engineer with Dr. Tom Zimmermann

This episode originally aired in May, 2019. 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!

-1 sJAN 8
Comments
077r - The productive software engineer with Dr. Tom Zimmermann

075r - Reinforcement learning for the real world with Dr. John Langford and Rafah Hosn

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 “resear...

-1 sJAN 1
Comments
075r - Reinforcement learning for the real world with Dr. John Langford and Rafah Hosn

053r - Chasing convex bodies and other random topics with Dr. Sébastien Bubeck

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. https://www.microsoft.com/research

-1 s2019 DEC 25
Comments
053r - Chasing convex bodies and other random topics with Dr. Sébastien Bubeck

052r - Chris Bishop

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

34 MIN2019 DEC 18
Comments
052r - Chris Bishop

More from Gretchen Huizinga, podcast host

Show

Playlists

sound
rilesvn
hmly
Welcome to Himalaya Premium