OPA-DPO：多模态大模型幻觉难题的高效解决方案
编者按：在视觉多模态大语言模型的快速发展中，幻觉问题一直是研究者们关注的焦点。模型生成与输入图像不一致甚至虚假的内容，不仅影响用户体验，也阻碍了多模态技术在实际场景中的落地。对此，微软亚洲研究院和香港中文大学的联合研究团队从直接偏好优化（DPO）入手，提出了 On-Policy Alignment (OPA)-DPO 算法，可通过确保训练数据与初始策略（reference policy）的一致性，...
端侧大模型部署新引擎：无需硬件修改，解锁商用DRAM的大模型推理
编者按：随着应用场景的扩展，端侧设备（如手机、电脑、可穿戴设备、机器人等）对大模型高效运行的需求日益增长，但端侧设备对模型运行的计算资源、访存带宽、能耗都有着极其苛刻的要求。存内计算技术有望从根本上解决以上资源问题，它能够将存储单元和计算单元融合，显著减少数据在存储和计算单元间频繁搬运而产生的资源损耗。然而，传统存内计算涉及对硬件架构的改动，不仅技术难度大，且迭代周期长，无法在实际场景中大规模量产...
What AI’s impact on individuals means for the health workforce and industry
| Peter Lee, Ethan Mollick, and Azeem Azhar
Ethan Mollick and Azeem Azhar, thought leaders at the forefront of AI’s influence on work, education, and society, discuss the impact of AI at the individual level and what that means for the healthcare workforce and the organizations and systems…
FrodoKEM: A conservative quantum-safe cryptographic algorithm
| Patrick Longa
The recent advances in quantum computing offer many advantages—but also challenge current cryptographic strategies. Learn how FrodoKEM could help strengthen security, even in a future with powerful quantum computers.
编者按：在产业智能化加速发展的当下，时间序列数据已然成为智能决策系统的关键基石。然而，传统的时间序列生成模型往往难以应对跨领域、跨风格的数据需求，且生成的数据在实际应用中缺乏可控性和实用性。 为解决这些痛点，微软亚洲研究院推出开源框架 TimeCraft，融合多项研究成果，通过跨域泛化、自然语言控制与任务感知等创新技术，助力时间序列生成任务从结构理解到任务对齐的全流程能力建设。TimeCraft...
Abstracts: Zero-shot models in single-cell biology with Alex Lu
| Gretchen Huizinga and Alex Lu
The emergence of foundation models has sparked interest in applications to single-cell biology, but when tested in zero-shot settings, they underperform compared to simpler methods. Alex Lu shares insights on why more research on AI models is needed in biological…
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Healthcare Agent Orchestrator: Multi-agent Framework for Domain-Specific Decision Support
Abstracts: Aurora with Megan Stanley and Wessel Bruinsma
| Amber Tingle, Megan Stanley, and Wessel Bruinsma
A new Nature paper explores Aurora, an AI model that redefines weather prediction with application to other environmental domains such as tropical cyclones. Hear from senior researchers Megan Stanley and Wessel Bruinsma as they share their groundbreaking work.
Collaborators: Healthcare Innovation to Impact
| Matthew Lungren, Jonathan M. Carlson, Smitha Saligrama, Will Guyman, and Cameron Runde
In this discussion, Matthew Lungren, Jonathan Carlson, Smitha Saligrama, Will Guyman, and Cameron Runde explore how teams across Microsoft are working together to generate advanced AI capabilities and solutions for developers and clinicians around the globe.