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Articles

读书日书单 | 在阅读中探寻科技与人文的融合之道 

April 21, 2025

作者:谢幸 编者按:从“推荐系统”的责任性研究,到社会责任人工智能(Societal AI),微软亚洲研究院全球研究合伙人谢幸的研究常常跨越学科边界,在人文科学中寻找答案。在今年的世界读书日,谢幸带来了一份聚焦技术与人文相互启发的书单,帮助我们从更广阔的视角审视科技的发展及其对社会的影响。这些作品中,不乏先行者关于技术如何影响人类社会的深刻洞见,提醒我们在机器智能飞速发展的今天,保持敬畏之心与责任...

A digital illustration of a person with a contemplative expression, resting their chin on their hand. The top of the person's head is open, revealing a white bird standing inside. The seagull is holding a worm in its beak, feeding the baby birds. The background is blue, and the words "TOOLS FOR THOUGHT" are written across the image in white letters.
Microsoft Research Blog

The Future of AI in Knowledge Work: Tools for Thought at CHI 2025 

April 18, 2025 | Sean Rintel, Leon Reicherts, Lev Tankelevitch, Advait Sarkar, Pratik Ghosh, and Richard Banks

Join us at CHI 2025 to explore how AI systems can be used as Tools for Thought as we reimage AI’s role in human thinking. Learn about new research, prototypes, and a workshop on designing AI that supports critical thinking,…

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Articles

PEACE project unlocks AI applications in geology using GeoMap 

April 18, 2025

When earthquakes hit, they often come with little warning. Each year, about 500,000 earthquakes ripple through the Earth—some are felt, many aren’t, but all are part of a complex and dynamic system that geologists are trying to understand. Earthquakes are…

AI Revolution podcast | Episode 3 - Are patients using generative AI for their own healthcare? | outline illustration of Christina Farr, Peter Lee, and Dave deBronkart
Microsoft Research Podcast

Empowering patients and healthcare consumers in the age of generative AI 

April 17, 2025 | Peter Lee, Dave deBronkart, and Christina Farr

Evangelist for patient empowerment Dave deBronkart and Manatt Heath’s Christina Farr discuss how generative AI is redefining healthcare by empowering patients, challenging traditional care models, and creating new opportunities for innovation and collaboration.

Lidong Zhou
Articles

硅基世界的“缘分”——系统与人工智能携手进化 

April 17, 2025

作者:周礼栋 编者按:在 NeurIPS 2024 大会上,微软亚洲研究院院长周礼栋博士发表了题为“硅基世界的‘缘分’——系统与人工智能携手进化”的主题演讲。他提出了一个前瞻性的观点:未来人工智能的突破,不仅依赖于模型和算法本身,更有赖于与计算机系统的深度融合。围绕“效率(Efficiency)、可信(Trust)、融合(Infusion)”三大关键词,周礼栋博士阐述了系统与人工智能之间如何实现双...

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Articles

ICLR上新 | 探索大模型优化、信息检索与记忆构建的创新之路 

April 16, 2025

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。 4月24日至4月28日,全球最负盛名的深度学习盛会之一 ICLR 大会将在新加坡举办。我们将通过两期“科研上新”为大家带来多篇微软亚洲研究院入选 ICLR 2025 的精选论文解读。第一期的研究工作将涵盖大模...

In the news | VentureBeat

When AI reasoning goes wrong: Microsoft Research shows more tokens can mean more problems 

April 15, 2025

Large language models (LLMs) are increasingly capable of complex reasoning through “inference-time scaling,” a set of techniques that allocate more computational resources during inference to generate answers. However, a new study from Microsoft Research reveals that the effectiveness of these…

The image features four white icons on a gradient background that transitions from blue on the left to green on the right. The first icon is a network or molecule structure with interconnected nodes. The second icon is a light bulb, symbolizing an idea or innovation. The third icon is a checklist with three items and checkmarks next to each item. The fourth icon consists of two overlapping speech bubbles, representing communication or conversation.
Microsoft Research Blog

Engagement, user expertise, and satisfaction: Key insights from the Semantic Telemetry Project 

April 14, 2025 | Amber Hoak, Scott Counts, Kate Lytvynets, David Tittsworth, Siddharth Suri, Nirupama Chandrasekaran, Ben Cutler, and Weiwei Yang

Semantic Telemetry Project data show that people who use AI for more professional and complex tasks are more likely to keep using the tool and to use it more often. Novice AI users engage in simpler tasks, but their usage…

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Articles

StreamMind:解锁全帧率流媒体视频实时理解新路径 

April 10, 2025

当今基础大模型的能力提升催生了诸多真实世界应用,如智能助手等。这类助手通过智能眼镜等智能设备时刻与用户相伴,持续感知和理解用户所在环境、发生的事件以及用户指令,并据此实时主动地给用户提供帮助。比如导盲助手,在用户要过马路时会输出“稍等现在有车经过”,“现在可以安全通过”等帮助提示。除了依赖大语言模型的世界知识和推理能力,此类智能助手更依赖对持续输入视频流的理解能力,以及可以在相关事件发生时立即发出...

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