人工智能赋能燃煤电厂转型，低成本实现深度脱碳
近年来，全球变暖趋势愈发明显，极端气候事件频繁发生，给人类社会和生态环境带来了巨大冲击。在众多导致全球变暖的因素中，碳排放是关键，其中燃煤电厂又是碳排放的“重灾区”。因此，全球各地“煤炭退出”的呼声日渐高涨，燃煤电厂加速关停的压力不断增加。尽管人们普遍意识到煤炭退出的重要性，但实现这一目标仍面临较大的困难和挑战。 为了寻找更加稳妥且低成本的转型路径，煤电行业亟需探索多种减排方式，而非只有“退役”这...
| Peter Lee
Join Microsoft's Peter Lee on a journey to discover how AI is impacting healthcare and what it means for the future of medicine.
The reality of generative AI in the clinic
| Peter Lee, Dr. Sara Murray, and Dr. Christopher Longhurst
UC San Diego Health’s Dr. Christopher Longhurst and UC San Francisco Health’s Dr. Sara Murray explore how generative AI is changing patient care, clinical workflows, and decision-making and how they envision the technology impacting the future of healthcare.
NatureLM：驱动科学发现与创新的跨领域AI大模型
自然科学作为人类探索自然现象与开发利用自然资源的基石，构建了一个庞大而复杂的知识体系，其研究范畴横跨物理、化学、生物以及材料科学等多个重要领域。在长期的发展进程中，各领域逐渐形成了自身独特的数据表达方式、研究方法和理论体系。然而，相对独立的知识体系虽然在一定程度上便于学科内部的理解与交流，但在无形中成为了阻碍学科间交叉研究的壁垒。 从基因功能的深入探究到新材料的创新设计，前沿的创新成果往往依赖于不...
In the news | New York Times
Here’s What the Rise of Clean Energy Looks Like From Space
A constellation of satellites orbiting 250 miles above Earth's surface shows how solar and wind have taken off in recent years.
In the news | LinkedIn Article
Global Renewables Watch: A New Era of Energy Insights
In 2022, we set out to help answer a question we heard time and time again: how much renewable energy does the world have? Joining with The Nature Conservancy and Planet , Microsoft’s AI for Good Lab announced the launch…
Claimify: Extracting high-quality claims from language model outputs
| Dasha Metropolitansky
Claimify, created by Microsoft Research, is a novel LLM-based claim-extraction method that outperforms prior solutions to produce more accurate, comprehensive, and substantiated claims from LLM outputs.
Metasurface: Unlocking the future of wireless sensing and communication
| Lili Qiu and Hao Pan
Metasurfaces explore engineered 2D materials that manipulate electromagnetic and mechanical waves, offering advances in wireless tech. They can power indoor GPS, extend 5G/6G coverage, and enable wireless sensing and imaging.
Introducing KBLaM: Bringing plug-and-play external knowledge to LLMs
| Taketomo Isazawa, Xi Wang, Liana Mikaelyan, Mathew Salvaris, and James Hensman
Introducing KBLaM, an approach that encodes and stores structured knowledge within an LLM itself. By integrating knowledge without retraining, it offers a scalable alternative to traditional methods.