[THEME MUSIC FADES] What I read there at the top is a passage from Chapter 2 of the book, which captures part of what we’re going to cover in this episode.  In our book, we predicted how AI would be leveraged in the clinic. Some of those predictions, I felt, were slam dunks, for example, AI being used to listen to doctor-patient conversations and write clinical notes. There were already early products coming out in the world not using generative […]

While large language models (LLMs) are capable of synthesizing vast amounts of information, they sometimes produce inaccurate or unsubstantiated content. To mitigate this risk, tools like Azure AI’s Groundedness Detection (opens in new tab) can be used to verify LLM outputs.  A common strategy for fact-checking LLM-generated texts –  

Large language models (LLMs) have demonstrated remarkable capabilities in reasoning, language understanding, and even creative tasks. Yet, a key challenge persists:  

AI tools are proving useful across a range of applications, from helping to drive the new era of business transformation to helping artists craft songs. But which applications are providing the most value to users? We’ll dig into that question in a series of blog posts that introduce the Semantic Telemetry project at Microsoft Research. In this initial post, we will introduce a new data science approach that we will use to analyze topics and task complexity of Copilot in […]

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 […]

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  

Imagine an AI system capable of guiding a robot to manipulate physical objects as effortlessly as it navigates software menus. Such seamless integration of digital and physical  

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  

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  

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