The AI Revolution in Medicine, Revisited: An Introduction

Transcript [MUSIC] PETER LEE: This is The AI Revolution in Medicine, Revisited. I’m Peter Lee, president of Microsoft Research, and I’m pretty excited to introduce this series of conversations as part of the Microsoft Research Podcast. About two years ago, with Carey Goldberg and Zak Kohane, we wrote a book, The AI Revolution in Medicine. This was a book that was intended to educate the world of healthcare and the world of medical research about this new thing that was […]

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Advancing biomedical discovery: Overcoming data challenges in precision medicine

Introduction Modern biomedical research is driven by the promise of precision medicine—tailored treatments for individual patients through the integration of diverse, large-scale datasets. Yet, the journey from raw data to actionable insights is fraught with challenges. Our team of researchers at Microsoft Research in the Health Futures group, in collaboration with the Perelman School of Medicine at the University of  

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Exploring the structural changes driving protein function with BioEmu-1

From forming muscle fibers to protecting us from disease, proteins play an essential role in almost all biological processes in humans and other life forms alike. There has been extraordinary progress in recent years toward better understanding protein structures using deep learning, enabling the accurate prediction of protein structures from their amino acid sequences. However, predicting a single protein structure from its amino acid  

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Introducing Muse: Our first generative AI model designed for gameplay ideation

Today, the journal Nature (opens in new tab) is publishing our latest research, which introduces the first World and Human Action Model (WHAM). The WHAM, which we’ve named “Muse,” is a generative AI model of a video game that can generate game visuals, controller actions, or both. The paper in Nature offers a detailed look at Muse, which was developed by the Microsoft Research Game Intelligence (opens  

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Microsoft Research and Physics Wallah team up to enhance AI-based tutoring

In India, limited resources, geographical constraints, and economic factors present barriers to quality education for some students. A shortage of teachers, particularly in remote or low-income areas, makes it harder for students to receive the guidance they need to prepare for highly competitive professional and academic programs. Microsoft Research is developing new algorithms and techniques that are enabling Physics Wallah (opens in new tab), a growing educational company, to make its AI-based tutoring services more accurate and reliable, to better  

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ExACT: Improving AI agents’ decision-making via test-time compute scaling

Autonomous AI agents are transforming the way we approach multi-step decision-making processes, streamlining tasks like web browsing, video editing, and file management. By applying advanced machine learning, they automate workflows, optimize performance, and reduce the need for human input.  However, these systems struggle in complex, dynamic environments. A key challenge lies in balancing exploitation, using known strategies for immediate gains, with exploration, which involves  

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Ideas: Building AI for population-scale systems with Akshay Nambi

AKSHAY NAMBI: Thanks for having me. STETKIEWICZ: I’d like to begin by asking you to tell us your origin story. How did you get started on your path? Was there a big idea or experience that captured your imagination or motivated you to do what you’re doing today? NAMBI: If I look back, my journey into research wasn’t a straight line. It was more about discovering my passion through some unexpected opportunities and also finding purpose along the way. So […]

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Advances to low-bit quantization enable LLMs on edge devices

Large language models (LLMs) are increasingly being deployed on edge devices—hardware that processes data locally near the data source, such as smartphones, laptops, and robots. Running LLMs on these devices supports advanced AI and real-time services, but their massive size, with hundreds of millions of parameters, requires significant memory and computational power, limiting widespread adoption. Low-bit quantization, a technique that compresses models and reduces memory demands, offers a solution by enabling more efficient operation. Recent  

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Ideas: Bug hunting with Shan Lu

SHAN LU: Thank you. HUIZINGA: So I like to start these episodes with what I’ve been calling the “research origin story,” and you have a unique, almost counterintuitive, story about what got you started in the field of systems research. Would you share that story with our listeners? LU: Sure, sure. Yeah. I grew up fascinating that I will become mathematician. I think I was good at math, and at some point, actually, until, I think, I entered college, I […]

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