Awards | ACM
Wei Chen and Benjamin G. Zorn named 2024 ACM Fellows
Wei Chen and Benjamin G. Zorn are among the 55 new ACM Fellows for their contributions to computing that are transforming science and society.
MatterGen：基于生成式AI的材料设计新范式
编者按：近日，微软研究院科学智能中心提出了一种创新的生成式 AI 材料设计工具 MatterGen, 突破了传统材料筛选方法的局限，能够在更广泛的材料空间中进行高效探索，并根据应用需求直接生成新材料。该模型可以针对材料的特殊几何结构进行优化，在化学成分、物理属性等多方面生成稳定的新型材料，开启了基于生成式 AI 辅助材料设计的新范式，并将对电池、磁铁等领域的创新产生深远影响。 材料创新是推动重大技...
In the news | KING5.com
Microsoft’s ‘AI for Good’ program offers $5 million in grants for Washington innovators
Microsoft announced a groundbreaking initiative Wednesday morning to use artificial intelligence to tackle some of the world’s biggest challenges. The program, worth over $5 million, focuses on Washington state scientists and innovators. It is open to individuals or groups working…
Research Focus: Week of January 13, 2025
In this edition: Privacy enhancements for multiparty deep learning; using smaller, open-source models to provide relevance judgments; new tool uses AI, data to automate innovation and development; Yasuyuki Matsushita named IEEE 2025 Computer Society Fellow.
编者按：近年来，人工智能在语言处理、视觉生成等领域的表现令人惊叹，但在复杂的数学推理任务上仍面临挑战。微软亚洲研究院推出的新算法 rStar-Math，通过引入类似人类系统的慢思考和推理思维，显著提升了小语言模型（SLMs）的数学推理能力。rStar-Math 打破了“只有大模型才有高性能”的固有观念，证明了小语言模型经巧妙设计，同样能实现卓越的推理效果，甚至在部分奥数级别的挑战中超越了现有大语言...
AI meets materials discovery
| 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: AI for materials discovery with Tian Xie and Ziheng Lu
| Lindsay Kalter, Ziheng Lu, and 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.
MatterGen: A new paradigm of materials design with generative AI
| Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Ryota Tomioka, and 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.
如何利用文本提示高效生成高质量、个性化的长视频？
编者按：在人工智能领域，尤其是“文本-视频”（Text-to-Video, T2V）模型的研究中，如何高效生成具有丰富动态和时间一致性的长视频一直是一个挑战。尽管 Transformer 架构和扩散模型在视频生成方面取得了显著进展，但在高分辨率视频的训练成本、基于文本条件的去噪过程的复杂性、长视频生成中的一致性问题等方面仍存在重大挑战。对此，微软亚洲研究院提出了 ARLON 框架，旨在通过结合自回...