{"id":789941,"date":"2021-11-16T08:00:47","date_gmt":"2021-11-16T16:00:47","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=789941"},"modified":"2021-11-15T10:05:37","modified_gmt":"2021-11-15T18:05:37","slug":"research-talk-towards-data-efficient-machine-learning-with-meta-learning","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/research-talk-towards-data-efficient-machine-learning-with-meta-learning\/","title":{"rendered":"Research talk: Towards data-efficient machine learning with meta-learning"},"content":{"rendered":"<p>At Microsoft Research, we are approaching large-scale AI from many different perspectives, which include not only creating new, bigger models, but also developing unique ways of optimizing AI models from training to deployment. One of the main challenges posed by larger AI models is that they are more difficult to deploy in an affordable and sustainable way, and it is also still hard for them to learn new concepts and tasks effectively. Join Microsoft Researcher Guoqing Zheng for the third of three lightning talks in this series on Efficient and adaptable large-scale AI. See talks from Microsoft Researchers Subho Mukherjee and Yu Cheng to learn more about the work Microsoft is doing to improve the efficiency of computation and data in large-scale AI models.<\/p>\n<p>Learn more about the 2021 Microsoft Research Summit: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/Aka.ms\/researchsummit\">https:\/\/Aka.ms\/researchsummit<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>At Microsoft Research, we are approaching large-scale AI from many different perspectives, which include not only creating new, bigger models, but also developing unique ways of optimizing AI models from training to deployment. One of the main challenges posed by larger AI models is that they are more difficult to deploy in an affordable and [&hellip;]<\/p>\n","protected":false},"featured_media":789944,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556],"msr-video-type":[261269,261263],"msr-locale":[268875],"msr-post-option":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-789941","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-video-type-deep-learning-large-scale-ai","msr-video-type-research-summit-2021","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/jZceIVlC4dk","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/789941"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/789941\/revisions"}],"predecessor-version":[{"id":795887,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/789941\/revisions\/795887"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/789944"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=789941"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=789941"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=789941"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=789941"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=789941"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=789941"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=789941"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}