{"id":722851,"date":"2021-03-05T07:50:16","date_gmt":"2021-03-05T15:50:16","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-group&p=722851"},"modified":"2024-03-06T09:34:32","modified_gmt":"2024-03-06T17:34:32","slug":"microsoft-turing-academic-program","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/collaboration\/microsoft-turing-academic-program\/","title":{"rendered":"Microsoft Turing Academic Program (MS-TAP)"},"content":{"rendered":"
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Microsoft Turing Academic Program (MS-TAP)<\/h1>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n
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\u201cThere\u2019s a great deal of interest and enthusiasm about the construction and use of large-scale neural language models. We\u2019re seeing new capabilities\u2014and they\u2019re being pressed into service in exciting applications. However, these models, built in a self-supervised manner from massive corpora, can generate offensive, biased, and costly output. We need to better understand these behaviors and to develop methods for mitigating harms. Considering both the value and potential costs of AI innovations, and developing best practices for addressing the risks, is central in the responsible development and fielding of AI technologies.<\/em>\u201d<\/p>\nEric Horvitz<\/a>, Chief Scientific Officer, Microsoft<\/cite><\/blockquote>\n\n\n\n

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\u201cAs AI models are becoming more powerful and reaching a large section of population either directly or indirectly through Microsoft\u2019s products and services, it is becoming pertinent to have the best minds of the world look at the impact these models can have and identify mechanisms to improve upon them. We believe strongly in improvements through collaboration and open research. We are excited about the potential contributions these new research collaborations can make, both to Microsoft and to the open research community interested in large-scale, language-centric models.<\/em>\u201d<\/p>\nSaurabh Tiwary<\/a>, Vice President & Distinguished Engineer, Microsoft <\/cite><\/blockquote>\n\n\n\n

Program Description<\/h2>\n\n\n\n

Microsoft is committed to the responsible development and fielding of AI technologies<\/a> including careful deliberation about the value and costs of harnessing large-scale neural language models. These models have been delivering breakthroughs in language capabilities, but have also been found to have the ability to generate language fraught with bias, toxic language, and denigration.<\/p>\n\n\n\n

We have created the Microsoft Turing Academic Program (MS-TAP) as part of our program to share Microsoft advances with Microsoft\u2019s Turing family (opens in new tab)<\/span><\/a> of natural language models in responsible manner. MS-TAP provides leading academics and researchers with a private preview of Turing models. Our goal is to engage our colleagues on shared interests, with a goal of better understanding model behavior, identifying novel applications, exploring and mitigating potential risks and mitigations, and improving future models.<\/p>\n\n\n\n

Program participants collaborate closely with Microsoft Turing scientists as well as domain experts contributing to Microsoft\u2019s on ethical and responsible AI. As concerns may come to the fore with AI advances, we seek to spend time and effort to better understand the capabilities, benefits, and costs of AI technologies in advance of general releases to the public. We take a stepwise approach to releasing the technology per our dual goals of sharing our technologies broadly and ensuring that AI models are used responsibly and safely in the open world.<\/p>\n\n\n\n

Specific goals of MS-TAP include the following:<\/p>\n\n\n\n