{"id":118049,"date":"2021-01-04T17:22:49","date_gmt":"2021-01-05T01:22:49","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2021\/01\/dual-takes-ai-to-the-next-level"},"modified":"2021-01-04T17:22:49","modified_gmt":"2021-01-05T01:22:49","slug":"dual-takes-ai-to-the-next-level","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2021\/01\/dual-takes-ai-to-the-next-level","title":{"rendered":"DUAL takes AI to the next level"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/dual-takes-ai-to-the-next-level2.jpg\"><\/a><\/p>\n<p>Scientists at DGIST in Korea, and UC Irvine and UC San Diego in the US, have developed a computer architecture that processes unsupervised machine learning algorithms faster, while consuming significantly less energy than state-of-the-art graphics processing units. The key is processing data where it is stored in computer memory and in an all-digital format. The researchers presented the new architecture, called DUAL, at the 2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture.<\/p>\n<p>\u201cToday\u2019s computer applications generate a large amount of data that needs to be processed by <a href=\"https:\/\/techxplore.com\/tags\/machine+learning\/\" rel=\"tag\" class=\"\">machine learning<\/a> algorithms,\u201d says Yeseong Kim of Daegu Gyeongbuk Institute of Science and Technology (DGIST), who led the effort.<\/p>\n<p>Powerful \u201cunsupervised\u201d machine learning involves training an algorithm to recognize patterns in <a href=\"https:\/\/techxplore.com\/tags\/large+datasets\/\" rel=\"tag\" class=\"\">large datasets<\/a> without providing labeled examples for comparison. One popular approach is a clustering algorithm, which groups similar data into different classes. These algorithms are used for a wide variety of data analyzes, such as identifying <a href=\"https:\/\/techxplore.com\/tags\/fake+news\/\" rel=\"tag\" class=\"\">fake news<\/a> on social media, filtering spam email and detecting criminal or fraudulent activity online.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Scientists at DGIST in Korea, and UC Irvine and UC San Diego in the US, have developed a computer architecture that processes unsupervised machine learning algorithms faster, while consuming significantly less energy than state-of-the-art graphics processing units. The key is processing data where it is stored in computer memory and in an all-digital format. The [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34,41,6],"tags":[],"class_list":["post-118049","post","type-post","status-publish","format-standard","hentry","category-cybercrime-malcode","category-information-science","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/118049","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=118049"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/118049\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=118049"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=118049"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=118049"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}