{"id":174142,"date":"2023-10-13T23:22:36","date_gmt":"2023-10-14T04:22:36","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2023\/10\/new-ai-driven-tool-streamlines-experiments"},"modified":"2023-10-13T23:22:36","modified_gmt":"2023-10-14T04:22:36","slug":"new-ai-driven-tool-streamlines-experiments","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2023\/10\/new-ai-driven-tool-streamlines-experiments","title":{"rendered":"New AI-driven tool streamlines experiments"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/new-ai-driven-tool-streamlines-experiments2.jpg\"><\/a><\/p>\n<p>Researchers at the Department of Energy\u2019s SLAC National Accelerator Laboratory have demonstrated a new approach to peer deeper into the complex behavior of materials. The team harnessed the power of machine learning to interpret coherent excitations, collective swinging of atomic spins within a system.<\/p>\n<p>This groundbreaking research, published recently in <a href=\"https:\/\/www.nature.com\/articles\/s41467-023-41378-4\">Nature Communications<\/a>, could make experiments more efficient, providing real-time guidance to researchers during <a href=\"https:\/\/techxplore.com\/tags\/data+collection\/\" rel=\"tag\" class=\"\">data collection<\/a>, and is part of a project led by Howard University including researchers at SLAC and Northeastern University to use machine learning to accelerate research in materials.<\/p>\n<p>The team created this new data-driven tool using \u201cneural implicit representations,\u201d a machine learning development used in computer vision and across different scientific fields such as medical imaging, particle physics and cryo-electron microscopy. This tool can swiftly and accurately derive unknown parameters from <a href=\"https:\/\/techxplore.com\/tags\/experimental+data\/\" rel=\"tag\" class=\"\">experimental data<\/a>, automating a procedure that, until now, required significant human intervention.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at the Department of Energy\u2019s SLAC National Accelerator Laboratory have demonstrated a new approach to peer deeper into the complex behavior of materials. The team harnessed the power of machine learning to interpret coherent excitations, collective swinging of atomic spins within a system. This groundbreaking research, published recently in Nature Communications, could make experiments [\u2026]<\/p>\n","protected":false},"author":359,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,6],"tags":[],"class_list":["post-174142","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/174142","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\/359"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=174142"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/174142\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=174142"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=174142"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=174142"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}