微软亚洲研究院推出AI编译器界“工业重金属四部曲”
编者按：编译器在传统计算科学中一直是一个重要的研究课题。在人工智能技术快速发展和广泛应用的今天，人工智能模型需要部署在多样化的计算机硬件架构上。同时，训练和部署大型人工智能模型时又对硬件性能有着更高的要求，有时还需根据硬件定制化代码。这些都对人工智能时代的编译器提出了新的更高的要求。 为了适应迅速发展的人工智能模型和加速硬件的需求，微软亚洲研究院以设计和构建具有高度灵活性、高效性、可扩展的 AI...
Microsoft at ICALP 2023: Deploying cloud capacity robustly against power failures
| Konstantina Mellou, Marco Molinaro, and Rudy Zhou
Efficiency is vital in the face of escalating demand for cloud resources. And efficient power management strategies address the bottleneck of power availability in datacenters. Learn how we optimize power allocation to support sustainable resource usage.
In the news | Nature
AI tools are designing entirely new proteins that could transform medicine
Digital art techniques can now devise custom, working biomolecules on demand. Read about recent advances in protein design, including MSR’s research into protein structure generation via folding diffusion.
Renovating computer systems securely and progressively with APRON
| Sangho Lee
This research paper was accepted by 2023 USENIX Annual Technical Conference (ATC) (opens in new tab), which is dedicated to advancing the field of systems research. Whether they’re personal computers or cloud instances, it’s crucial to ensure that the computer…
Awards | USENIX OSDI
Daniel Berger receives OSDI 2023 Best Paper Award
Daniel Berger's paper, Enso: A Streaming Interface for NIC-Application Communication, was selected as a best paper by the OSDI'23 organizers for its quality and potential impact. Enso was also awarded for its open source artifacts.
作者：科学智能中心 编者按：近年来，深度学习技术在分子微观结构预测中取得了巨大的进展。然而，分子的宏观属性和功能往往取决于分子结构在平衡态下的分布，仅了解分子的微观结构还远远不够。在传统的统计力学中，分子动力学模拟或增强采样等是获得平衡分布中采样的常用方法，但这些方法昂贵又耗时。 针对这个长期且艰巨的挑战，微软研究院发布了可用于预测分子结构平衡分布的深度学习框架 Distributional Gr...
Research Focus: Week of July 3, 2023
In this issue: A new study looks at engineers’ views on hybrid work; prompt engineering adds context and specificity to generative AI models; Overwatch learns code edit patterns to aid developers; a Qlib update addresses financial market challenges.
Distributional Graphormer: Toward equilibrium distribution prediction for molecular systems
| Shuxin Zheng, Chang Liu, Yu Shi, Ziheng Lu, Fusong Ju, Jianwei Zhu, Hongxia Hao, Peiran Jin, Frank Noé, Haiguang Liu, and 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.
In the news | Yahoo! News
Breast cancer detection, language learning, sustainability: Can AI help humanity?
While some believe AI could steal jobs or even destroy humanity, others think the technology could improve quality of life for people across the planet.