In the news | AAMC
Microsoft exec and Learn Serve Lead 2024 speaker James Weinstein, DO, says the technology could eventually expand access and quality, but privacy concerns remain. While artificial intelligence (AI) tools are drawing attention for their potential to improve doctor-patient dynamics —…
In the news | Royal Society of Medicine
Christopher Bishop, Technical Fellow and Director of Microsoft Research AI for Science, discusses how the deep learning technology that underpins the AI revolution is advancing at an extraordinary pace, with many of the most exciting and impactful applications of this…
编者按:人工智能基础模型正在加速科学发现的进程,尤其,经过多领域数据训练的基础模型,更能在跨领域的任务中展现出色的性能。微软研究院科学智能中心已利用基础模型打造了一系列强大的科学发现模型,包括:革新天气与污染预测的 Aurora 模型、专注于新材料发现与设计的 MatterGen、可预测新材料行为和属性的 MatterSim,以及可自动设计候选药物的 TamGen 模型等。基础模型的应用不仅提高了...
In the news | Microsoft Customer Stories
Developing high-quality medicine is a resource-intensive endeavor that requires collaboration across Novo Nordisk. Novo Nordisk aimed to scale a pipeline of drug discovery, development, and data science capabilities with AI and machine learning. In partnership with Microsoft Research, the teams built…
In the news | Industry Healthcare
Simplifying secure decision tree training; Improving accuracy of audio content detection; A novel neurosymbolic system for converting text to tables; New video series: AI for Business Transformation; TEE security protections for container workloads.
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。 2024年的ECCV(European Conference on Computer Vision)于10月4日在意大利米兰落下帷幕。作为计算机视觉领域的重要国际会议之一,微软亚洲研究院有多篇论文入选。本期的...
By Yadong Lu, Senior Researcher; Jianwei Yang, Principal Researcher; Yelong Shen, Principal Research Manager; Ahmed Awadallah, Partner Research Manager Recent advancements in large vision-language models (VLMs), such as GPT-4V and GPT-4o, have demonstrated considerable promise in driving intelligent agent systems…
Awards | American Physical Society
The AI for Science partner research manager received this distinction for the development of machine learning methods for advancing the physical sciences, in particular for the many-body sampling problem and the electronic structure problem.