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  

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  

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 […]

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  

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 […]

[MUSIC FADES]  I’m your guest host, Lindsay Kalter. Today I’m talking to Microsoft Principal Research Manager Tian Xie and Microsoft Principal Researcher Ziheng Lu. Tian is doing fascinating work with MatterGen, an AI tool for generating new materials guided by specific design requirements. Ziheng is one of the visionaries behind MatterSim, which puts those new materials to the test through advanced simulations. Together, they’re redefining what’s possible in materials science. Tian and Ziheng, welcome to the podcast.  TIAN XIE: Very […]

Materials innovation is one of the key drivers of major technological breakthroughs. The discovery of lithium cobalt oxide in the 1980s laid the groundwork for today’s lithium-ion battery technology. It now powers modern mobile phones and electric cars, impacting the daily lives of billions of people. Materials innovation is also required for designing more efficient solar cells, cheaper batteries for grid-level energy storage,  

Over the past year, our work on AutoGen has highlighted the transformative potential of agentic AI and multi-agent applications. Today, we are excited to announce AutoGen v0.4, a significant milestone informed by insights from our community of users and developers. This update represents a complete redesign of the AutoGen library, developed to improve code quality, robustness, generality,