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Microsoft Research
AI for Science

新闻与深度文章

The image shows eight different 3D models of protein structures. Each model is color-coded with various segments in blue, green, orange, and other colors to highlight different parts of the protein.
微软研究院博客

| Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Victor García Satorras, Osama Abdin, Bas Veeling, Ryota Tomioka, 和 Frank Noé

Meet BioEmu-1 from Microsoft Research. This deep learning model can generate thousands of protein structures per hour, unlocking new possibilities for protein scientists and drug discovery and research.

A grid of colorful, abstract shapes on a black background. Each cell in the grid features a unique three-dimensional geometric pattern, showcasing a variety of colors including green, red, blue, and purple.
故事

| Tian Xie

Researchers pull back the curtain on MatterGen and MatterSim, the cutting-edge tools reshaping how we design and innovate advanced materials. Explore the journey from concept to creation driving these AI-powered technologies.

Ideas podcast | illustration of Tian Xie and Ziheng Lu
微软研究院播客

| Lindsay Kalter, Ziheng Lu, 和 Tian Xie

How do you generate and test materials that don’t exist yet? Researchers Tian Xie and Ziheng Lu share the story behind MatterGen and MatterSim, AI tools poised to transform materials discovery and help drive advances in energy, manufacturing, and sustainability.

A grid of colorful, abstract shapes on a black background. Each cell in the grid features a unique three-dimensional geometric pattern, showcasing a variety of colors including green, red, blue, and purple.
微软研究院博客

| Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Ryota Tomioka, 和 Tian Xie

Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments.

Research Focus: Week of December 16, 2024
微软研究院博客

NeoMem: hardware/software co-design for CXL-native memory tiering; Chimera: accurate retrosynthesis prediction by ensembling models with diverse inductive biases; GA4GH task execution API enables multicloud task execution.

Illustrated headshots of Chris Bishop and Eliza Strickland
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| Christopher Bishop 和 Eliza Strickland

From the Microsoft Booth at NeurIPS 2024, Microsoft Research AI for Science Director Chris Bishop discusses how AI is changing approaches to scientific advancement—from drug discovery to weather forecasting—and the profound impact it can have on the world.

故事

We’re excited to be a part of #NeurIPS2024! Explore the future of AI with over 100 groundbreaking papers, including oral and spotlight sessions, on reinforcement learning, advanced language model training, and multilingual, culturally inclusive benchmarks.

新闻报道 | The Seattle Times

Microsoft unveiled Aurora in June, an AI model that draws on atmospheric data. The company said in a blog post introducing the model that a team of researchers developed it to forecast in the most challenging conditions, for regions without…

Outlined illustrations of Tong Wang and Bonnie Kruft for the Microsoft Research Podcast, Abstracts series.
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| Bonnie Kruft 和 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.