I’m in the enviable position of hearing what my research colleagues are working on within my team and in other groups at the company. I’m also regularly reading what other researchers are posting. This gives me a broad perspective about…
In the news | Microsoft Stories
Humans and AI – Juan Lavista Ferres
Meet Juan - When Juan Lavista Ferres was 8 years old, he was given a computer and quickly realized the impact that technology could have on the world. Now, he works on resources to empower others to solve global challenges…
编者按：12月11日，微软亚洲研究院举办了2021理论学术研讨会，邀请了来自学术界和产业界的理论研究专家共同探讨大数据和人工智能技术的理论研究。会议期间，康奈尔大学教授、图灵奖得主 John Hopcroft 博士针对“理论研究”和“科研教育”两个话题，结合自身的感悟，为大家分享了理论研究的意义，为什么基础研究很重要，以及大学教育究竟应该教什么。John Hopcroft 博士指出，我们需要花点时...
In the news | InfoQ
F# 6 Introduces Resumable Code, Improvements to Pattern Matching and Tooling, and More
F# 6 brings a wealth of new features to the language, library, and tooling aimed at improving performance and making it simpler for programmers wishing to switch to it. F# 6 adopts a new foundation for concurrency based on resumable code, which is a high-performance…
At Microsoft, the trustworthiness of A/B test results is essential for data-driven decisions. In earlier parts of our trustworthy experimentation series, we shared patterns and some recommendations to increase trustworthiness in both pre- and during- experiment stages. Now we tackle…
![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…