In the news | Forward Future
Future Forward Live – AOC, Part 2
What does an analog optical computer do? Francesca Parmigiani, Principal Research Manager at Microsoft Research Cambridge (@Microsoft), has the answer. “When you start learning a new programming language, you begin with a ‘Hello World.’ For us, that meant recognizing handwritten…
The AI Economy Institute (AIEI) was founded on a bold premise: the future of the economy should be shaped—not simply observed. To realize this vision, we’ve built a think tank with a deliberate rhythm of inquiry, collaboration, publication, and dissemination—turning ideas into impact. …
AIEI’s Inaugural cohort
Microsoft launched the AI Economy Institute (AIEI) in 2025 as a corporate “think tank” to ensure that AI’s rapid advancements translate into broad societal benefits and a people-first economy. The Institute’s strategic rationale is to bridge the gap between technological innovation and…
DocReward：让智能体“写得更专业”的文档奖励模型
编者按：当大模型已能“写对”内容，如何让文档也“好看、易读”成为办公智能体转型的新焦点。微软亚洲研究院携手香港中文大学、中国科学院大学提出了一个专注于评估文档“结构与样式”专业性的奖励模型 DocReward。该模型为智能体生成的文档提供了清晰、可量化的优化信号，使其不仅在内容层面准确可信，更在形式呈现上清晰有序、专业规范，为下一代智能办公智能体的落地奠定了关键基础。 近年来，随着智能体化转型（A...
In the news | IBM Think
Computing with light offers two paths forward for AI
Light is edging into roles once reserved for electricity in computing. As researchers race to ease the growing energy and performance strain that AI puts on data centers, some are experimenting with using photons instead of electrons to process information, an…
Large vision-language models are improving at describing images, yet hallucinations still erode trust by introducing contradictions and fabricated details that limit practical applications. In response, Microsoft Research Asia has developed On-Policy Alignment DPO (OPA-DPO), a new algorithm that aligns expert…
In the news | Github Blog
The road to better completions: Building a faster, smarter GitHub Copilot with a new custom model
Code completion remains the most widely used GitHub Copilot feature, helping millions of developers stay in the flow every day. Our team has continuously iterated on the custom models powering the completions experience in GitHub Copilot driven by developer feedback.…
VL Norm：让强化学习更稳、更快的关键一步
编者按：随着大语言模型（LLMs）推理能力的不断提升，如何在训练过程中保持稳定的优化效率与可验证性，成为强化学习研究的重要方向。由微软亚洲研究院与清华大学联合提出的 VL Norm 方法，针对可验证奖励强化学习（RLVR）中因输出长度波动导致的梯度方差过大问题，给出了理论上无偏且方差最小的解决方案。在多种任务和模型规模上，VL Norm 均显著提升了收敛速度与训练稳定性，展现出了强化学习优化的新范...
Tell me when: Building agents that can wait, monitor, and act
| Hussein Mozannar, Matheus Kunzler Maldaner, Maya Murad, Jingya Chen, Gagan Bansal, Rafah Hosn, and Adam Fourney
SentinelStep enables AI agents to handle monitoring tasks that run for hours or days, like watching for emails or tracking prices. It works by managing when agents should check and their context, avoiding wasted resources and missed updates.