编者按:欢迎阅读“科研上新”栏目!“科研上新”汇聚了微软亚洲研究院最新的创新成果与科研动态。在这里,你可以快速浏览研究院的亮点资讯,保持对前沿领域的敏锐嗅觉,同时也能找到先进实用的开源工具。 本文荣获 PPoPP 2024 唯一最佳论文奖 论文链接:https://dl.acm.org/doi/10.1145/3627535.3638476 (opens in new tab) 项目链接:http...
| Chang Liu and Gretchen Huizinga
Senior Researcher Chang Liu discusses M-OFDFT, a variation of orbital-free density functional theory (OFDFT) that leverages deep learning to help identify molecular properties in a way that minimizes the tradeoff between accuracy and efficiency.
Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Large language models (LLMs) have shown impressive capabilities, yet they still struggle with…
| Anjaly Parayil, Ayush Choure, Fiza Husain, Avi Nayak, Piyali Jana, Rujia Wang, Chetan Bansal, and Saravan Rajmohan
Integrating AI into cloud service monitoring improves incident detection accuracy, reduces unnecessary alerts, and enhances overall system reliability. This helps organizations better align with business goals and increase customer satisfaction.
| Badrish Chandramouli
Garnet is a cache-store system that addresses growing demand for data storage to support interactive web applications and services. Offering several advantages over legacy cache-stores, Garnet is now available as an open-source download.
| Marta Wilczkowiak (SHE/HER), Sean Rintel, and Mar Gonzalez-Franco
As avatar use expands in digital spaces, advances are required to better represent all people. Discover how research into the varying perceptions of facial animation glitches in low versus high realism scenarios supports this goal.
In the news | Microsoft Unlocked
In the past year, JVKE has started a new chapter on his journey: an orchestral journey for “golden hour”. He used Microsoft Research’s AI-powered Project Muzic for tools and inspiration to bring the experience to life.
编者按:近日,微软研究院上线了面向全球研究界的全新线上系列活动 Microsoft Research Forum,旨在共同探讨人工智能时代的最新研究进展、大胆新颖的想法以及全球研究界关注的重要议题。来自微软研究院全球各地的研究人员将分享他们的研究洞见,并与大家进行在线讨论,希望碰撞出更多新的思想火花。 科学研究的突破正在以前所未有的速度影响着现实世界。人工智能的最新研究发展正在重塑人们的生活、工作...
作者:科学智能中心 编者按:为了使电子结构方法突破当前广泛应用的密度泛函理论(KSDFT)所能求解的分子体系规模,微软研究院科学智能中心的研究员们基于人工智能技术和无轨道密度泛函理论(OFDFT)开发了一种新的电子结构计算框架 M-OFDFT。这一框架不仅保持了与 KSDFT 相当的计算精度,而且在计算效率上实现了显著提升,并展现了优异的外推性能,为分子科学研究中诸多计算方法的基础——电子结构方法...