![An illustration of the KEAR architecture represented by five panels side by side. The first contains an input question—“What is a treat that your dog will enjoy?”—and the answer choices “salad,” “petted,” “affection,” “bone,” and “lots of attention.” The second panel has three boxes, each representing retrieval from a specific knowledge source. A box labeled “Knowledge Graph” has a silhouette of a dog and underneath it and labeled “desires” a silhouette of a dog being petted; a heart representing “affection”; a bone; and clapping hands representing “lots of attention.” A box labeled “relevant questions” has the question “What do dogs like to eat?” and the accompanying answer “Bones.” A boxed labeled “dictionary” contains the definition of “bone”: “a composite material making up the skeleton of most vertebrates.” The third panel, labeled “concatenation with input,” contains the input question followed by “Dog, desires, bone. Dog, desires, lots of attention” followed by the relevant question and finally the dictionary definition of bone. In between each is a separation token [SEP]. The fourth panel is labeled “language model” and contains a quote box labeled “language services,” a cube labeled “model,” and left and right braces punctuation within a circle labeled “language understanding.” The fifth panel is labeled “output” and includes silhouettes of each of the five answer choices. The silhouette of the bone is highlighted in blue, representing the appropriate response.](https://www.microsoft.com/en-us/research/wp-content/uploads/2021/12/1400x788_Common_Sense_still_no_logo-1-480x280.jpg){kind=logo}
Azure AI milestone: Microsoft KEAR surpasses human performance on CommonsenseQA benchmark
| Yichong Xu, Chenguang Zhu, Shuohang Wang, Michael Zeng, and Xuedong Huang
KEAR (Knowledgeable External Attention for commonsense Reasoning)—along with recent milestones in computer vision and neural text-to-speech—is part of a larger Azure AI (opens in new tab) mission to provide relevant, meaningful AI solutions and services that work better for people because they better capture…
Ada Dialogue | 微软亚洲研究院研究员为你讲述科研方法论！
编者按：在科研道路上，你一定感受过 deadline 带来的压力，也经历过论文被拒、实验效果未达到预期的低谷。那么如何更合理地规划科研时间？如何调整心态？如何锁定研究方向？如何提高论文写作技能？快来查收这份由微软亚洲研究院刘蓓研究员给出的科研方法论！ 本文内容是刘蓓在微软亚洲研究院第五期 Ada Dialogue 中的分享。通过面对面的问答，刘蓓深入而细致地为实习生们分享了自己在科研路上的经验与心...
Authors: Tommy Guy, Sally Kellaway, Zachary Cook, Julie Koesmarno Microsoft Dynamics 365 Customer Insights accelerates time to value with Machine Learning-based predictions covering Product recommendations, Churn risk, Sentiment analysis and Customer lifetime value scenarios. These features were developed using vast…
Azure AI milestone: New Neural Text-to-Speech models more closely mirror natural speech
| Sheng Zhao
Neural Text-to-Speech—along with recent milestones in computer vision and question answering—is part of a larger Azure AI (opens in new tab) mission to provide relevant, meaningful AI solutions and services that work better for people because they better capture how…
Microsoft Dynamics 365 Customer Insights accelerates time to value with Machine Learning-based predictions covering Product recommendations, Churn risk, Sentiment analysis and Customer lifetime value scenarios. These features were developed using vast data sets and advanced analytics to provide a comprehensive…
PyMarlin is a lightweight PyTorch extension library for agile experimentation. This article examines how PyMarlin works, how it supports extensibility, and next steps needed to advance its functionality further.
秦涛：以独立、深度的视角看世界，做有意义、创新的研究
编者按：NeurIPS 2021大会刚刚结束。在今年的大会上，微软亚洲研究院共有22篇论文入选，而其中的8篇都有微软亚洲研究院首席研究员秦涛的参与。自加入微软亚洲研究院以来，秦涛已在 NeurIPS、ICML、ICLR、IJCAI、AAAI、CVRP 等业界顶级期刊、会议上发表了100余篇论文，他所带领的团队也在2018年将中-英机器翻译提升至人类专业水平，在2019年国际机器翻译大赛上获得8项冠...
Research at Microsoft 2021: Collaborating for real-world change
Over the past 30 years, Microsoft Research has undergone a shift in how it approaches innovation, broadening its mission to include not only advancing the state of computing but also using technology to tackle some of the world’s most pressing…
In the news | Microsoft Research Blog
Research at Microsoft 2021: Collaborating for real-world change
Our work was highlighted in the annual "Research at Microsoft 2021" newsletter: "As ML techniques and approaches advance, so does the potential for applications to empower individuals in the workplace and beyond does, too. Research teams are leveraging few-shot learning…