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Project Turing

Making machines literate

新闻与深度文章

Microsoft Research Focus 08 edition, week of January 23
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Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Organizations must digitize various documents, many with charts and images, to manage…

Microsoft Research Focus 03: Week of November 7th, 2022
微软研究院博客

Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Barun Patra, Saksham Singhal, Shaohan Huang, Zewen Chi, Li Dong, Furu Wei,…

新闻报道 | ZDNet

Microsoft is updating its Translator and other Azure AI services with a set of AI models called Z-code, officials announced on March 22. These updates will improve the quality of machine translations, as well as help these services support more…

Collage of four images. 1) a VR haptic pivot device 2) Ashley Lorens of Microsoft Research 3) an image of tractor on a farm 4) image of Race and Technology lecture series speakers.
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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…

Z-Code multilingual model

新闻报道 | Microsoft Translator Blog

Microsoft is on a quest for AI at Scale with high ambition to enable the next generation of AI experiences. The Microsoft Translator ZCode team is working together with Microsoft Project Turing and Microsoft Research Asia to advance language and…

An illustration of how the image text contrastive and translation text contrastive tasks work together to help align the space of images, English text and non-English text. On the left side of the illustration, the three domains—Image Domain, English Domain, and Non-English Domain--are segregated. An arrow labeled “Image-Captions training data” points to another depiction of the three domains where the image domain and the English domain intersect but the non-English domain is still separate and shown in gray to show that it’s not significantly affected. A two headed arrow with the label “Image-Text contrastive loss” is drawn between the image and English domains. Towards the bottom of the image, an arrow labeled “Parallel corpus training data” points to another depiction of the three domains where the English domain and the non-English domain intersect but the image domain is separate and shown in gray to indicate that it is not significantly affected. A two-headed arrow with the label “Translated Text Contrastive loss” is drawn between the English and non-English domains. Finally, a third arrow with the label “Resulting Effect” is drawn to the right of the image which points to a depiction of all three domains intersecting.
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| Saurabh Tiwary

Today, the Microsoft Turing team (opens in new tab) is thrilled to introduce Turing Bletchley, a 2.5-billion parameter Universal Image Language Representation model (T-UILR) that can perform image-language tasks in 94 languages. T-Bletchley has an image encoder and a universal language encoder that vectorize…

Figure 1. Trend of sizes of state-of-the-art NLP models over time
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| Ali Alvi 和 Paresh Kharya

We are excited to introduce the DeepSpeed- and Megatron-powered Megatron-Turing Natural Language Generation model (MT-NLG), the largest and the most powerful monolithic transformer language model trained to date, with 530 billion parameters. It is the result of a research collaboration…

XTREME leaderboard showing T-ULRv5 at the top.
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| Saurabh Tiwary 和 Lidong Zhou

Today, we are excited to announce that with our latest Turing universal language representation model (T-ULRv5), a Microsoft-created model is once again the state of the art and at the top of the Google XTREME public leaderboard. Resulting from a…

a woman sitting at a table with a plate of food
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| Paul Bennett, Chenyan Xiong, 和 Corby Rosset

Have you ever wondered what happens when you ask a search engine to search for something as seemingly simple as “how do you grill salmon”? Have you found yourself entering multiple searches before arriving at a webpage with a satisfying…