Microsoft Research
AI for Science
News & features
Abstracts: November 14, 2024
| Bonnie Kruft and Tong Wang
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.
In the news | Microsoft
AFMR was recognized in the Microsoft Annual Report 2024
Through our Accelerating Foundation Models Research program, we’ve made grants to hundreds of projects in AI safety and alignment research, AI-driven scientific discovery, and beneficial applications of AI. And we launched our Global Perspectives Responsible AI Fellowship program, designed to…
In the news | Royal Society of Medicine
Christopher Bishop: 2024 Ellison Cliffe Lecture
Christopher Bishop, Technical Fellow and Director of Microsoft Research AI for Science, discusses how the deep learning technology that underpins the AI revolution is advancing at an extraordinary pace, with many of the most exciting and impactful applications of this…
Awards | American Physical Society
Frank Noé, American Physical Society Fellow
The AI for Science partner research manager received this distinction for the development of machine learning methods for advancing the physical sciences, in particular for the many-body sampling problem and the electronic structure problem.
Microsoft Research Forum Episode 4: The future of multimodal models, a new “small” language model, and other AI updates
Explore multimodal & small language models, plus advanced benchmarks for AI evaluation. Microsoft researchers are working on breakthroughs in weather prediction, materials design, even a new kind of computer for AI inference and hard optimization problems.
This talk discusses Aurora, a cutting-edge foundation model that offers a new approach to weather forecasting that could transform our ability to predict and mitigate the impacts of extreme events, air pollution, and the changing climate.
Research Focus: Week of July 15, 2024
Advancing time series analysis with multi-granularity guided diffusion model; An algorithm-system co-design for fast, scalable MoE inference; What makes a search metric successful in large-scale settings; learning to solve PDEs without simulated data.
Collaborators: Sustainable electronics with Jake Smith and Aniruddh Vashisth
| Gretchen Huizinga, Jake Smith, and Aniruddh Vashisth
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.
Microsoft Research Forum Episode 3: Globally inclusive and equitable AI, new use cases for AI, and more
“We’re at the very early stage of generative AI and the impacts it will have on work. This is a fast-moving field, and there’s an immense opportunity to take control of the agenda and build truly globally equitable AI systems”,…