{"id":132248,"date":"2021-12-11T21:23:01","date_gmt":"2021-12-12T05:23:01","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2021\/12\/deepmind-ai-tackles-one-of-chemistrys-most-valuable-techniques"},"modified":"2021-12-11T21:23:01","modified_gmt":"2021-12-12T05:23:01","slug":"deepmind-ai-tackles-one-of-chemistrys-most-valuable-techniques","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2021\/12\/deepmind-ai-tackles-one-of-chemistrys-most-valuable-techniques","title":{"rendered":"DeepMind AI tackles one of chemistry\u2019s most valuable techniques"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/deepmind-ai-tackles-one-of-chemistrys-most-valuable-techniques2.jpg\"><\/a><\/p>\n<p>The DeepMind team has made probably the most ambitious attempt yet to deploy AI to calculate electron density, the end result of DFT calculations. \u201cIt\u2019s sort of the ideal problem for machine learning: you know the answer, but not the formula you want to apply,\u201d says Aron Cohen, a theoretical chemist who has long worked on DFT and who is now at DeepMind.<\/p>\n<hr>\n<p>A team led by scientists at the London-based artificial-intelligence company DeepMind has developed a machine-learning model that suggests a molecule\u2019s characteristics by predicting the distribution of electrons within it. The approach, described in the 10 December issue of <i>Science<\/i><sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-021-03697-8#ref-CR1\">1<\/a><\/sup>, can calculate the properties of some molecules more accurately than existing techniques.<\/p>\n<p>\u201cTo make it as accurate as they have done is a feat,\u201d says Anatole von Lilienfeld, a materials scientist at the University of Vienna.<\/p>\n<p>The paper is \u201ca solid piece of work\u201d, says Katarzyna Pernal, a computational chemist at Lodz University of Technology in Poland. But she adds that the machine-learning model has a long way to go before it can be useful for computational chemists.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The DeepMind team has made probably the most ambitious attempt yet to deploy AI to calculate electron density, the end result of DFT calculations. \u201cIt\u2019s sort of the ideal problem for machine learning: you know the answer, but not the formula you want to apply,\u201d says Aron Cohen, a theoretical chemist who has long worked [\u2026]<\/p>\n","protected":false},"author":417,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19,6],"tags":[],"class_list":["post-132248","post","type-post","status-publish","format-standard","hentry","category-chemistry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/132248","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\/417"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=132248"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/132248\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=132248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=132248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=132248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}