The advantages of large language models are undeniable due to the capabilities achieved and opportunities ahead. We must also consider the benefits and potential harms coming via uses of these models. In 2021, we founded the Microsoft Turing Academic Program (MS-TAP) that provides academic teams with access to some of the world's largest language models. The program reflects our belief in the importance of having diverse and talented teams...
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Turing Universal Language Representation Model family (T-ULRv6) has achieved the 1st position on both the Google XTREME and GLUE leaderboards, demonstrating that a single multilingual model can achieve state-of-the-art capabilities in both English and Multilingual understanding tasks. Multilingual technology is not only a technical challenge but also a social responsibility. Therefore, we are committed to democratizing AI by...
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The Microsoft Turing team has a new addition to its family of image and language models. The Turing Image Super Resolution model (T-ISR) uses deep learning to deliver the magical “enhance” to any image in the world. It is already being used today to improve the quality of the aerial view in Bing Maps around the globe and is also rolling out in Microsoft Edge to bring its powers to the entire web. See examples of the model in action...
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Rank Multimodal (RankMM) The RankMM model effectively combines the search paradigms of a text query, page context, and images to aid image and video retrieval. RankMM models are Visual Language (VL) models which take page context into account to improve image and video retrieval performance in a web-scale search engine.
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Enhancing image quality is a critical but challenging computer vision task. We've released a new AI-based model for improving the quality of images on Microsoft Bing. Not only are the Bing image search results relevant, but they are also beautiful and high-resolution. Our new V3 model outperformed the V2 model by 36% in terms of click-through rate, demonstrating that users find visually appealing images in search results more interesting and...
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Intelligent question-answering is one of the most useful and delightful features of search. As a user, you ask a question (e.g., “what are the benefits of eating apricots”) and can get the answer directly (e.g., info about health and nutrition benefits of apricots) at the top of the page without further need to search for relevant content by yourself. Recently, Bing expanded its intelligent question-answering feature to more than 100...
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Bing users around the globe perform hundreds of millions of search queries every day. These queries are diverse in many ways, from the intent the users are seeking to fulfill, to the languages and regions where these queries are issued. To handle such a dynamic range of usage, AI models in Bing must continuously evolve and therefore Bing is the prime example of Microsoft AI at Scale. This blog post introduces recent updates to Bing that are making...
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Today we share more about continued evolution of Bing Image Search towards a more intelligent search engine through multi-granularity matches, improved understanding of user queries, images and webpages, as well as the relationships between them.
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This post describes the various machine learning techniques used in GIF search by Bing. To provide the best GIF search experience Bing employs techniques such as sentiment analysis, OCR, and even pose modeling of subjects appearing in GIF flicks to reflect subtle intent variations of your queries. Read on to find out more about how we made it work.
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