In the news | KING5.com

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: January 17, 2025
Microsoft Research Blog

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.

Articles

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...

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.
Stories

| 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
Microsoft Research Podcast

| 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.

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.
Microsoft Research Blog

| 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.

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Articles

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...

The v0.4 update introduces a cohesive AutoGen ecosystem that includes the framework, developer tools, and applications. The framework’s layered architecture clearly defines each layer’s functionality. It supports both first-party and third-party applications and extensions.
Microsoft Research Blog

| Adam Fourney, Ahmed Awadallah, Cheng Tan, Erkang (Eric) Zhu, Friederike Niedtner, Gagan Bansal, Jack Gerrits, Jacob Alber, Peter Chang, Rafah Hosn, Ricky Loynd, Saleema Amershi, Victor Dibia, XiaoYun Zhang, Li Jiang, Ryan Sweet, Leonardo Pinheiro, Mohammad Mazraeh, Gerardo Moreno Zizumbo, Kosta Petan, Aamir Jawaid, Reuben Bond, Diego Colombo, and Hussein Mozannar

Announcing AutoGen 0.4, fully reimagined library for building advanced agentic AI systems, developed to improve code quality and robustness. Its asynchronous, event-driven architecture is designed to support dynamic, scalable workflows.

In the news | Tech Community