{"id":1054512,"date":"2024-07-12T13:31:48","date_gmt":"2024-07-12T20:31:48","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2025-12-08T17:07:54","modified_gmt":"2025-12-09T01:07:54","slug":"ai-for-domains-aid","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/ai-for-domains-aid\/","title":{"rendered":"AI for Domains (AID)"},"content":{"rendered":"
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AI for Domains (AID)<\/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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Our mission<\/h2>\n<\/div><\/div>\n\n\n\n
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The M365 Research organization’s AI for Domains (AID) team is an applied research group focused on leveraging cutting-edge research to extend the capabilities, efficiency, reliability, and reduce risks associated with Copilot. We prioritize user privacy and confidentiality while unlocking the potential of enterprise data for domain-specific AI applications.<\/p>\n<\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n\n\n\n

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Our research<\/h2>\n<\/div><\/div>\n\n\n\n
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Customization and Domain-Tailoring<\/strong><\/p>\n<\/div>\n\n\n\n

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Enhance AI models’ relevance and utility across diverse domains by tailoring them to understand and interpret domain-specific data and challenges. This involves developing methodologies to customize LLMs with persona-specific knowledge, enabling them to deliver insights tailored to the unique contexts and requirements of different domains.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Trustworthy Grounding<\/strong><\/p>\n<\/div>\n\n\n\n

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Emphasizes the importance of basing AI decisions on reliable, factual information sourced from verifiable and authoritative databases, industry standards, and scientific research. This research area aims to improve the trustworthiness and credibility of AI-generated content, reducing biases and inaccuracies.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Privacy<\/strong><\/p>\n<\/div>\n\n\n\n

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Addresses the challenges of adhering to complex and ever-changing global regulations concerning data privacy, security, and ethical AI use. This research area ensures that domain-adapted models are not only compliant but also designed with the foresight to adapt to future regulatory changes.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n\n\n\n

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Projects<\/h2>\n<\/div><\/div>\n\n\n\n
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Latest news<\/h2>\n<\/div><\/div>\n\n\n\n
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Work with us<\/h2>\n<\/div><\/div>\n\n\n\n
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See all open positions<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"featured_media":1054521,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_group_start":"","footnotes":""},"research-area":[13556],"msr-group-type":[243694],"msr-locale":[268875],"msr-impact-theme":[],"class_list":["post-1054512","msr-group","type-msr-group","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-group-type-group","msr-locale-en_us"],"msr_group_start":"","msr_detailed_description":"","msr_further_details":"","msr_hero_images":[],"msr_research_lab":[],"related-researchers":[{"type":"user_nicename","display_name":"Robert Sim","user_id":36650,"people_section":"Leadership","alias":"rsim"},{"type":"user_nicename","display_name":"Gbola Afonja","user_id":42846,"people_section":"Team","alias":"gafonja"},{"type":"user_nicename","display_name":"Wei-Ning Chen","user_id":44040,"people_section":"Team","alias":"weiningchen"},{"type":"user_nicename","display_name":"Yanzhi Chen","user_id":44045,"people_section":"Team","alias":"t-chenyanzhi"},{"type":"user_nicename","display_name":"Huseyin Atahan Inan","user_id":40426,"people_section":"Team","alias":"huinan"},{"type":"user_nicename","display_name":"Lukas Wutschitz","user_id":38775,"people_section":"Team","alias":"luwutsch"}],"related-publications":[900579,1034898,1031928,1025313,1018440,1015809,996270,994119,975756,957027,957018,945306,945099,939993,691908,900555,879069,864054,863118,851473,837859,830107,790535,785137,781984,762406,753328,750094],"related-downloads":[],"related-videos":[],"related-projects":[1155944,866259,788945,648207],"related-events":[],"related-opportunities":[],"related-posts":[793088,1038870],"tab-content":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1054512","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-group"}],"version-history":[{"count":123,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1054512\/revisions"}],"predecessor-version":[{"id":1158067,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/1054512\/revisions\/1158067"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1054521"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1054512"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1054512"},{"taxonomy":"msr-group-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group-type?post=1054512"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1054512"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1054512"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}