Microsoft Research
AI for Science
新闻与深度文章
Abstracts: December 12, 2023
| Gretchen Huizinga, Tao Qin, 和 Lijun Wu
Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements. In this episode, Senior Principal Research Manager…
We’re proud to have 100+ accepted papers At NeurIPS 2023, plus 18 workshops. Several submissions were chosen as oral presentations and spotlight posters, reflecting groundbreaking concepts, methods, or applications. Here’s an overview of those submissions.
新闻报道 | IEEE
Karin Strauss, 2024 IEEE Fellow
Congratulations to Karin Strauss, Senior Principal Research Manager in AI4Science, who was recently named as a 2024 IEEE Fellow!
Accelerate Foundation Models Research: Supporting a global academic research ecosystem for AI
A diverse research ecosystem is essential to realizing the promise of AI. Accelerate Foundation Models Research aims to expand access to powerful models, engaging academics outside of computer science to pursue a broad range of important opportunities.
新闻报道 | Metaverse Post
Microsoft’s DeepSpeed4Science Advances AI in Scientific Research
Microsoft recently launched DeepSpeed4Science initiative to apply deep learning in natural sciences, including drug development and renewable energy. DeepSpeed, an open-source AI framework, aims to accelerate and scale up deep learning processes.
Microsoft has introduced the DeepSpeed4Science initiative through its DeepSpeed team. The initiative focuses on the application of deep learning in the natural sciences, targeting areas such as drug development and renewable energy. The DeepSpeed system, an open-source AI framework from…
| Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Martin Cai, 和 Yuxiong He
Editor’s note, Sept. 28, 2023 – The founding collaborators list was updated to correct omissions and the scientific foundation model graph was updated to correct information. In the next decade, deep learning may revolutionize the natural sciences, enhancing our capacity to…
| Shuxin Zheng, Chang Liu, Yu Shi, Ziheng Lu, Fusong Ju, Jianwei Zhu, Hongxia Hao, Peiran Jin, Frank Noé, Haiguang Liu, 和 Tie-Yan Liu
Distributional Graphormer, Microsoft’s new deep learning framework for predicting the equilibrium distribution of molecular structures, can generate realistic and diverse molecular structures with high efficiency and low cost.
新闻报道 | Microsoft News Centre UK
How AI is helping to shrink waiting times for NHS cancer patients
The National Health Service at Addenbrooke’s Hospital in Cambridge is now able to plan radiotherapy treatments faster than in the past, thanks to AI advances that are cutting wait times. As the NHS approaches its 75th birthday, it continues to…