In the news | NextWeb
Microsoft has unveiled an AI system called Speller100 that corrects spelling in over 100 languages used in search queries on Bing. “We believe Speller100 is the most comprehensive spelling correction system ever made in terms of language coverage and accuracy,”…
| Jingwen Lu, Jidong Long (龙继东), and Rangan Majumder
At Microsoft Bing, our mission is to delight users everywhere with the best search experience. We serve a diverse set of customers all over the planet who issue queries in over 100 languages. In search we’ve found about 15% of…
In the news | Data Release
Announcing a GitHub repo which generates a data cohort for reinforcement learning research on Sepsis. The cohort is produced from the publicly available hospital database, MIMIC III.
In the news | VentureBeat
In a post on its AI research blog, Microsoft today detailed a new language system, Speller100, that the company claims is one of the most comprehensive ever made in terms of linguistic coverage and accuracy. Comprising a number of AI models…
Accelerate development of machine learning applications for engineers and data scientists
From a research point of view, games offer an amazing environment in which to develop new machine learning algorithms and techniques. And we hope, in due course, that those new algorithms will feed back not just into gaming, but into…
In the news | Microsoft on the Issues
As the world reaches the next stage in our collective fight against Covid-19 with the availability of vaccines, we’ve thrown in our support by mobilizing our AI for Health data science team, in collaboration with Dr. Ashish K. Jha at Brown School…
Editor’s note: To promote the implementation of the “AI + industry” concept and support more companies to ride the current wave of digital transformation, Microsoft Research Asia established the Innovation Partnership in 2017. Today, the partnership has expanded to 27…
| Zygmunt Lenyk and Junwon Park
Pretrained vision models accelerate deep learning research and bring down the cost of performing computer vision tasks in production. By pretraining one large vision model to learn general visual representation of images, then transferring the learning across multiple downstream tasks,…