The efficient simulation of molecules has the potential to change how the world understands biological systems and designs new drugs and biomaterials. Tong Wang discusses AI2BMD, an AI-based system designed to simulate large biomolecules with speed and accuracy.

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Researcher Siddharth Suri and professor David Holtz give a brief history of prompt engineering, discuss the debate behind their recent collaboration, and share what they found from studying how people’s approaches to prompting change as models advance.

Learn more:

• As Generative Models Improve, People Adapt Their Prompts | Publication, July 2024
• AI, Cognition, and the Economy (AICE) | Initiative page

Emre Kiciman shares how some keen observations and a desire to have front-end impact led him to make the jump from systems and networking to computational social science and now causal analysis and large-scale AI—and how systems thinking still impacts his work.

Learn more:

• AI Controller Interface: Generative AI with a lightweight, LLM-integrated VM (blog)
• AICI: Prompts as (Wasm) Programs (GitHub)

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.

https://www.microsoft.com/research

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

Machine learning is a powerful tool that enables conversational agents to provide general question-answer services. But in domains with more specific taxonomies – or simply for requests that are longer and more complicated than “Play Baby Shark” – custom conversational AI has long been the province of large enterprises with big budgets. But not for long, thanks to the work of Dr. Riham Mansour, a Principal Software Engineering Manager for Microsoft’s Language Understanding Service, or LUIS. She and her colleagues are using the emerging science of machine teaching to help domain experts build bespoke AI models with little data and no machine learning expertise.

On today’s podcast, Dr. Mansour gives us a brief history of conversational machines at Microsoft; tells us all about LUIS, one of the first Microsoft products to deploy machine teaching concepts in real world verticals; and explains how an unlikely combination of engineering skills, science skills, entrepreneurial skills – and not taking no for an answer – helped make automated customer engagement and business functions more powerful, more accessible and more intelligent!

https://www.microsoft.com/research

Dr. Craig Costello is in the business of safeguarding your secrets. And he uses math to do it. A researcher in the Security and Cryptography group at Microsoft Research, Dr. Costello is among a formidable group of code makers (aka cryptographers) who make it their life’s work to protect the internet against adversarial code breakers (aka cryptanalysts), both those that exist today in our classical computing world, and those that will exist in a quantum computing future.

On today’s podcast, Dr. Costello gives us a battlefield update in the ongoing crypto wars; talks about different approaches to post quantum cryptography and explains why he believes isogeny-based primitives are among the most promising; and reassures us that, as long as the battle goes on, cryptographers will continue to work very hard on the very hard math they hope will protect us from hackers and attackers, even in the age of quantum computers. https://www.microsoft.com/research

Using technology to help us improve our health is nothing new: a quick web search returns hundreds of apps and devices claiming to help us get fit, quit smoking, master anxiety or just “find our center.” What is new is a serious cohort of researchers exploring how artificial emotional intelligence, or AEI, could help us understand ourselves better and, when used in concert with human caregivers, enhance our well-being. One of those researchers is Jina Suh, a former Xbox developer who got hooked on research and is now an RSDE in the Human Understanding and Empathy group at MSR, as well as a PhD student in computer science at the University of Washington.

On today’s podcast, Jina shares her passion for creating technologies that promote emotional resilience and mental health; gives us an inside look at an innovative research collaboration that aims to improve collaborative care for cancer patients with depression; and tells us an emotional story of how, on the brink of quitting her job, she found inspiration to get back in the game and begin a new career in research for human well-being. https://www.microsoft.com/research

If someone asked you what snow leopards and Vincent Van Gogh have in common, you might think it was the beginning of a joke. It’s not, but if it were, Mark Hamilton, a software engineer in Microsoft’s Cognitive Services group, budding PhD student and frequent Microsoft Research collaborator, would tell you the punchline is machine learning. More specifically, Microsoft Machine Learning for Apache Spark (MMLSpark for short), a powerful yet elastic open source machine learning library that’s finding its way beyond business and into “AI for Good” applications such as the environment and the arts.

Today, Mark talks about his love of mathematics and his desire to solve big, crazy, core knowledge sized problems; tells us all about MMLSpark and how it’s being used by organizations like the Snow Leopard Trust and the Metropolitan Museum of Art; and reveals how the persuasive advice of a really smart big sister helped launch an exciting career in AI research and development.

https://www.microsoft.com/research

A lack of appropriate data, decreased model performance, and other obstacles have made it difficult to expand the input language models can receive. Li Lyna Zhang introduces LongRoPE, a method capable of extending content windows to more than 2 million tokens.

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Dr. Eyal Ofek is a senior researcher at Microsoft Research and his work deals mainly with, well, reality. Augmented and virtual reality, to be precise. A serial entrepreneur before he came to MSR, Dr. Ofek knows a lot about the “long nose of innovation” and what it takes to bring a revolutionary new technology to a world that’s ready for it.

On today’s podcast, Dr. Ofek talks about the unique challenges and opportunities of augmented and virtual reality from both a technical and social perspective; tells us why he believes AR and VR have the potential to be truly revolutionary, particularly for people with disabilities; explains why, while we’re doing pretty well in the virtual worlds of sight and sound, our sense of virtual touch remains a bit more elusive; and reveals how, if he and his colleagues are wildly successful, it won’t be that long before we’re living in a whole new world of extension, expansion, enhancement and equality.https://www.microsoft.com/research

Dr. Susan Dumais knows you have things to do, and if you need help finding stuff to get them done (and you probably do) then her long and illustrious career in search technologies has been worth it. Situated firmly in Louis Pasteur’s quadrant of the research grid (the square where you answer “yes” to both the quest for fundamental understanding and use-based applications) the Microsoft Technical Fellow, and Deputy Lab Director of MSR AI, has made finding information the focus of her career, and has probably made your life a little more productive in the process.

Today, Dr. Dumais tells us how the landscape of information retrieval has evolved over the past twenty years; reminds us that queries don’t fall from the sky but are grounded in the context of real people, real events and real time; talks about her current interest in non-web-based search (or how I can easily put my hands on my own digital belongings) and reveals what apples and Michael Jordan have in common with search research.https://www.microsoft.com/research

In 2018, Microsoft launched the Microsoft AI Residency Program, a year-long, expanded research experience designed to give recent graduates in a variety of fields the opportunity to work alongside prominent researchers at MSR on cutting edge AI technologies to solve real-world problems. Dr. Brian Broll was one of them. A newly minted PhD in Computer Science from Vanderbilt University, Dr. Broll was among the inaugural cohort of AI residents who spent a year working on machine learning in game environments and is on the pod to talk about it!

Today, Dr. Broll gives us an overview of the work he did and the experience he had as a Microsoft AI Resident, talks about his passion for making complex concepts easier and more accessible to novices and young learners, and tells us how growing up on a dairy farm in rural Minnesota helped prepare him for a life in computer science solving some of the toughest problems in AI.

https://www.microsoft.com/research

Dr. Ed Cutrell is a Principal Researcher in the Ability group at Microsoft Research and he’s convinced that great technology should be available to everyone. Working in the fields of Accessibility and Information and Communication Technologies for Development (aka ICT4D), his research has explored computing solutions for people across the resource and ability spectrum, both here and around the world.

Today, Dr. Cutrell gives us an overview of his work in the disability and inclusive design space, explains the vital importance of interdisciplinarity – a fancy way of saying many ways of thinking and many ways of knowing – and tells us how a dumb phone beat a smart tablet in rural India… and what that meant to researchers.

https://www.microsoft.com/research

As computing moves to the cloud, there is an increasing need for privacy in AI. In an ideal world, users would have the ability to compute on encrypted data without sacrificing performance. Enter Dr. Olli Saarikivi, a post-doctoral researcher in the RiSE group at MSR. He, along with a stellar group of cross-disciplinary colleagues, are bridging the gap with CHET, a compiler and runtime for homomorphic evaluation of tensor programs, that keeps data private while making the complexities of homomorphic encryption schemes opaque to users.

On today’s podcast, Dr. Saarikivi tells us all about CHET, gives us an overview of some of his other projects, including Parasail, a novel approach to parallelizing seemingly sequential applications, and tells us how a series of unconventional educational experiences shaped his view of himself, and his career as a researcher. https://www.microsoft.com/research

The ability to read and understand unstructured text, and then answer questions about it, is a common skill among literate humans. But for machines? Not so much. At least not yet! And not if Dr. T.J. Hazen, Senior Principal Research Manager in the Engineering and Applied Research group at MSR Montreal, has a say. He’s spent much of his career working on machine speech and language understanding, and particularly, of late, machine reading comprehension, or MRC.

On today’s podcast, Dr. Hazen talks about why reading comprehension is so hard for machines, gives us an inside look at the technical approaches applied researchers and their engineering colleagues are using to tackle the problem, and shares the story of how an a-ha moment with a Rubik’s Cube inspired a career in computer science and a quest to teach computers to answer complex, text-based questions in the real world.

https://microsoft.com/research

In an era of unprecedented advances in AI and machine learning, current gen systems and networks are being challenged by an unprecedented level of complexity and cost. Fortunately, Dr. Ganesh Ananthanarayanan, a researcher in the Mobility and Networking group at MSR, is up for a challenge. And, it seems, the more computationally intractable the better! A prolific researcher who’s interested in all aspects of systems and networking, he’s on a particular quest to extract value from live video feeds and develop “killer apps” that will have a practical impact on the world.

Today, Dr. Ananthanarayanan tells us all about Video Analytics for Vision Zero (an award-winning “killer app” that aims to reduce traffic-related fatalities to zero), gives us a wide-angle view of his work in geo-distributed data analytics and client-cloud networking, and explains how the duration and difficulty of a Test Cricket match provides an invaluable lesson for success in life and research.

https://www.microsoft.com/research

Dr. Nathalie Riche envisions a future in which all of our data will be accessible, meaningful, compelling and artistic. And as a researcher in human computer interaction and information visualization at Microsoft Research, she’s working on technical tools that will help us wrangle our data, extract knowledge from it, and communicate with it in a memorable, persuasive and aesthetically pleasing way. In other words, she wants our data to be both smart… and beautiful!

Today, Dr. Riche shares her passion for the art of data driven storytelling, reveals the two superpowers of data visualization, gives us an inside look at some innovative projects designed to help us th(ink) with digital ink, and tells the story of how a young woman with an artist’s heart headed into computer science, took a detour to the beach, paid for it with research and ended up with a rewarding career that brings both art and computing together.

https://www.microsoft.com/research

This episode first aired in January, 2018. 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.

https://www.microsoft.com/research

This episode first aired in March, 2018. 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.

https://www.microsoft.com/research

Senior Researcher Arindam Mitra introduces AgentInstruct. Using raw data sources, the automated multi-agent framework can create diverse, high-quality synthetic data at scale for the post-training of small and large language models.

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Dr. Johannes Gehrke is a Microsoft Technical Fellow and head of Architecture and Machine Learning for the Intelligent Communications and Conversations Cloud in Microsoft’s Experiences and Devices division. But lest you think his lofty position makes him in any way superior to you, let me tell you, he knows who works for whom, and he’ll be the first to tell you that you are his boss!

On today’s podcast, Dr. Gehrke frames the new, cloud-powered work world as a fast paced, widely-distributed workplace that demands real-time decision-making and collaboration – and explains how products like Microsoft Teams are meeting those demands – and tells us, both directly and indirectly, about the future of work, which for Microsoft, involves a pivot from an app-centric approach to a people-centric approach where, by using an AI-infused productivity suite coupled with the power of the cloud, we can essentially “hire Microsoft” to help us get our work done.

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 counterintuitive.Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of 4 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.https://microsoft.com/research

This episode first aired in January, 2018. 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.”

https://www.microsoft.com/research

If you’re like me, you’re no longer amazed by how all your technologies can work for you. Rather, you’ve begun to take for granted that they simply should work for you. Instantly. All together. All the time. The fact that you’re not amazed is a testimony to the work that people like Dr. Lidong Zhou, Assistant Managing Director of Microsoft Research Asia, do every day. He oversees some of the cutting-edge systems and networking research that goes on behind the scenes to make sure you’re not amazed when your technologies work together seamlessly but rather, can continue to take it for granted that they will!

Today, Dr. Zhou talks about systems and networking research in an era of unprecedented systems complexity and what happens when old assumptions don’t apply to new systems, explains how projects like CloudBrain are taking aim at real-time troubleshooting to address cloud-scale, network-related problems like “gray failure,” and tells us why he believes now is the most exciting time to be a systems and networking researcher.

Dr. Chris Bishop is a Microsoft Technical Fellow and director of MSR Cambridge, where he oversees an impressive portfolio of research including machine learning, AI, healthcare and gaming. Phil Spencer is the Executive Vice President of Gaming at Microsoft where he oversees everything from the design of the next Xbox console to the creation and release of blockbuster properties like Halo, Gears of War and Forza Motorsport. These two powerhouse executives are pushing the boundaries of creativity, technical innovation and fun across the spectrum of gaming genres and devices for nearly 2 billion gamers around the world.

On today’s podcast, Chris and Phil discuss their respective roles in Microsoft’s gaming ecosystem, revealing a sort of “enrichment pipeline” that flows all the way from researcher to developer to gamer. They also give us an inside look at the close collaboration between the world-class research organization of MSR and the world-class gaming franchise of Xbox, highlighting Microsoft’s unique ability to deliver the tools, talent and resources that fuel innovation and help shape the future of gaming.http://www.microsoft.com/research

You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.

On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.

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.

Printed circuit boards are abundant—in the stuff we use and in landfills. Researcher Jake Smith and professor Aniruddh Vashisth discuss the development of vitrimer-based PCBs that perform comparably to traditional PCBs but have less environmental impact.

Learn more:

• Recyclable vitrimer-based printed circuit boards for sustainable electronics | Nature Sustainability, April 2024
• Microsoft Climate Research Initiative
• Microsoft Research AI for Science
• Storing digital data in synthetic DNA with Dr. Karin Strauss | Microsoft Research Podcast, October 2018

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.

This episode first aired in September, 2018:

You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, Massachusetts, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.

On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning – now a feature of Azure Machine Learning – that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

If you’ve ever played video games, you know that for the most part, they look a lot better than they sound. That’s largely due to the fact that audible sound waves are much longer – and a lot more crafty – than visual light waves, and therefore, much more difficult to replicate in simulated environments. But Dr. Nikunj Raghuvanshi, a Senior Researcher in the Interactive Media Group at Microsoft Research, is working to change that by bringing the quality of game audio up to speed with the quality of game video. He wants you to hear how sound really travels – in rooms, around corners, behind walls, out doors – and he’s using computational physics to do it.

Today, Dr. Raghuvanshi talks about the unique challenges of simulating realistic sound on a budget (both money and CPU), explains how classic ideas in concert hall acoustics need a fresh take for complex games like Gears of War, reveals the computational secret sauce you need to deliver the right sound at the right time, and tells us about Project Triton, an acoustic system that models how real sound waves behave in 3-D game environments to makes us believe with our ears as well as our eyes.

When we think of information processing systems, we often think of computers, but we ourselves are made up of information processing systems – trillions of them – also known as the cells in our bodies. While these cells are robust, they’re also extraordinarily complex and not altogether predictable. Wouldn’t it be great, asks Dr. Andrew Phillips, head of the Biological Computation Group at Microsoft Research in Cambridge, if we could figure out exactly how these building blocks of life work and harness their power with the rigor and predictability of computer science? To answer that, he’s spent a good portion of his career working to develop a system of intelligence that can, literally, program biology.

Today, Dr. Phillips talks about the challenges and rewards inherent in reverse engineering biological systems to see how they perform information processing. He also explains what we can learn from stressed out bacteria, and tells us about Station B, a new end-to-end platform his team is working on that aims to reduce the trial and error nature of lab experiments and help scientists turn biological cells into super-factories that could solve some of the most challenging problems in medicine, agriculture, the environment and more.

This episode first aired in August of 2018.

You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.

Behnaz Arzani loves hard problems and the freedom to explore. That makes research a great fit! She discusses her work in network management, including the potential role of LLMs in the field; the challenges that excite her; and how storytelling changed her life.

Learn more:

• Solving Max-Min Fair Resource Allocations Quickly on Large Graphs | Publication, February 2024
• Finding Adversarial Inputs for Heuristics using Multi-level Optimization | Publication, February 2024
• MetaOpt: Examining, explaining, and improving heuristic performance | Microsoft Research blog, January 2024
• A Holistic View of AI-driven Network Incident Management | Publication, October 2023
• Behnaz Arzani: Painting, storytelling, and other hobbies | Microsoft Research bio page

If you’ve ever wondered why, in the age of the internet, we still don’t hold our elections online, you need to spend more time with Dr. Josh Benaloh, Senior Cryptographer at Microsoft Research in Redmond. Josh knows a lot about elections, and even more about homomorphic encryption, the mathematical foundation behind the end-to-end verifiable election systems that can dramatically improve election integrity today and perhaps move us toward wide-scale online voting in the future.

Today, Dr. Benaloh gives us a brief but fascinating history of elections, explains how the trade-offs among privacy, security and verifiability make the relatively easy math of elections such a hard problem for the internet, and tells the story of how the University of Michigan fight song forced the cancellation of an internet voting pilot.

Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you’d talk to another person. That’s the easy part. The hard part is getting your machine to understand and talk back to you like it’s that other person.

Today, Dr. El Asri talks about the particular challenges she and other scientists face in building sophisticated dialogue systems that lay the foundation for talking machines. She also explains how reinforcement learning, in the form of a text game generator called TextWorld, is helping us get there, and relates a fascinating story from more than fifty years ago that reveals some of the safeguards necessary to ensure that when we design machines specifically to pass the Turing test, we design them in an ethical and responsible way.

If every question in life could be answered by choosing from just a few options, machine learning would be pretty simple, and life for machine learning researchers would be pretty sweet. Unfortunately, in both life and machine learning, things are a bit more complicated. That’s why Dr. Manik Varma, Principal Researcher at MSR India, is developing extreme classification systems to answer multiple-choice questions that have millions of possible options and help people find what they are looking for online more quickly, more accurately and less expensively.

On today’s podcast, Dr. Varma tells us all about extreme classification (including where in the world you might actually run into 10 or 100 million options), reveals how his Parabel and Slice algorithms are making high quality recommendations in milliseconds, and proves, with both his life and his work, that being blind need not be a barrier to extreme accomplishment.