Advancing transparency: Updates on responsible AI research
| Mihaela Vorvoreanu and Kathy Walker
Editor’s note: All papers referenced here represent collaborations throughout Microsoft and across academia and industry that include authors who contribute to Aether, the Microsoft internal advisory body for AI ethics and effects in engineering and research. A surge of generative…
Research Focus: Week of January 8, 2024
| Zinan Lin, Jinyu Li, Bhaskar Mitra, Siân Lindley, Liang Wang, Nan Yang, and Furu Wei
Mixture-of-linear-experts for long-term time series forecasting; Weakly-supervised streaming multilingual speech model with truly zero-shot capability; KBFormer: Diffusion model for structured entity completion; Identifying risks of AI-mediated data access:
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。 论文链接：https://arxiv.org/abs/2312.08901 (opens in new tab) 项目链接（将于近日上线）：https://github.com/microsoft/CoT-I...
Splitwise improves GPU usage by splitting LLM inference phases
| Esha Choukse, Chaojie Zhang, Íñigo Goiri, Aashaka Shah, Saeed Maleki, Rodrigo Fonseca, and Ricardo Bianchini
Expanded LLM use creates new demands on cloud GPU capacity. Splitwise presents an efficient solution by separating the two essential phases of LLM inference, achieving higher throughput within a limited power budget.
In the news | The Sequence
My Five Favorite AI Papers of 2023
Today marks the final issue of 2023, and I want to start by expressing my gratitude for your support. The Sequence has grown organically to over 165,000 subscribers this year. Thank you all for your continued support. Today's edition will…
Research at Microsoft 2023: A year of groundbreaking AI advances and discoveries
AI saw unparalleled growth in 2023, reaching millions daily. This progress owes much to the extensive work of Microsoft researchers and collaborators. In this review, learn about the advances in 2023, which set the stage for further progress in 2024.
Research Focus: Week of December 18, 2023
In this issue of Research Focus: Optimized exit-augmented models for scalable efficient inference; NeurIPS LLM Efficiency Challenge; LLM-empowered automated data exploration; Boosting cloud efficiency with data-driven decision-making and optimization.
In the news | LinkedIn Article
Transforming Breast Cancer Detection with AI
The stark reality that one in eight women in the United States will develop breast cancer in their lifetime underscores a pressing need for change. Each year, breast cancer claims the lives of approximately 42,000 women—our mothers, sisters, daughters, colleagues,…
当AI遇见大脑：电脑与人脑协同“进化”
作者：李东胜 比尔·盖茨曾坦言，他最害怕的事情之一就是他的大脑停止工作，这也说出了很多人的心声。大脑是人类生命的核心，智慧之源，我们的肢体运动、思想、情感、记忆、创造力等都依赖于大脑的神奇活动。 然而，人类脑健康的现状并不乐观。根据《柳叶刀》杂志2016年发布的全球疾病负担研究（Global Burden of Disease Study，GBD）显示，1997年至2016年，每年有900万人死于...