AI赋能天气：微软研究院发布首个大规模大气基础模型Aurora
编者按：气候变化日益加剧，高温、洪水、干旱，频率和强度不断增加的全球极端天气给整个人类社会都带来了难以估计的影响。这给现有的天气预测模型提出了更高的要求——这些模型要更准确地预测极端天气变化，为政府、企业和公众提供更可靠的信息，以便做出及时的准备和响应。为了应对这一挑战，微软研究院开发了首个大规模大气基础模型 Aurora，其超高的预测准确率、效率及计算速度，实现了目前最先进天气预测系统性能的显著...
Born in the research lab a decade ago, SWAN continues to accelerate networking in the Microsoft Cloud
| Victor Bahl
Software-driven wide area network (SWAN) enables central management and control of network infrastructure to improve reliability and efficiency. A Microsoft researcher describes its journey from a research idea to a foundational system for Microsoft Azure.
In the news | Microsoft News Center
Why AI sometimes gets it wrong — and big strides to address it
Around the time GPT-4 was making headlines for acing standardized tests, Microsoft researchers and collaborators were putting other AI models through a different type of test — one designed to make the models fabricate information.
In the news | Axios Science
1 big thing: Cutting through the BS of AI
A new algorithm, along with a dose of humility, might help generative AI mitigate one of its persistent problems: confident but inaccurate answers. Why it matters: AI errors are especially risky if people overly rely on chatbots and other tools…
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。 本周，人工智能领域最具学术影响力的顶级会议之一，CVPR 大会在美国西雅图举办。因此，这期的“科研上新”为大家带来了四篇微软亚洲研究院入选 CVPR 2024 的精选论文解读，涉及领域涵盖新视角图像合成、3D...
Synergizing habits and goals with variational Bayes: A new framework for biological and artificial embodied agents
| Dongqi Han
The Bayesian behavior framework synergizes habits and goals through variational Bayesian methods, offering new insights on sensorimotor behavior and comprehension of actions.
MicroCode: Portable programming for the BBC micro:bit
| Eric Anderson, Thomas Ball, Peli de Halleux, James Devine, and Michal Moskal
MicroCode offers an affordable way to program the BBC micro:bit without needing an internet connection, fostering exploratory learning.
Awards | Computing Research Association
Martez Mott receives CRA-WP Skip Ellis Early Career Award
Mott focuses on designing, building, and evaluating novel intelligent interactive technologies that are guided by scientific understandings of people’s experiences with computers and information.
Author: Chang Xu Diffusion probabilistic models have the capacity to generate high-fidelity samples for generative time series forecasting. However, they also present issues of instability due to their stochastic nature. In order to tackle this challenge, researchers from Microsoft Research…