{"id":67710,"date":"2019-07-15T15:04:46","date_gmt":"2019-07-15T19:04:46","guid":{"rendered":"http:\/\/danielschristian.com\/learning-ecosystems\/?p=67710"},"modified":"2019-07-15T15:04:46","modified_gmt":"2019-07-15T19:04:46","slug":"ai-analyzed-3-3-million-scientific-abstracts-and-discovered-possible-new-materials-technologyreview-com","status":"publish","type":"post","link":"http:\/\/danielschristian.com\/learning-ecosystems\/2019\/07\/15\/ai-analyzed-3-3-million-scientific-abstracts-and-discovered-possible-new-materials-technologyreview-com\/","title":{"rendered":"AI analyzed 3.3 million scientific abstracts and discovered possible new materials [technologyreview.com]"},"content":{"rendered":"<p><strong><a href=\"https:\/\/www.technologyreview.com\/f\/613933\/ai-nlp-scientific-abstracts-material-science\/\" target=\"_blank\" rel=\"noopener noreferrer\">AI analyzed 3.3 million scientific abstracts and discovered possible new materials<\/a> <\/strong>&#8212; from technologyreview.com<\/p>\n<p><em>Excerpt:<\/em><\/p>\n<p style=\"padding-left: 40px;\">A group of researchers have now used this technique to munch through 3.3 million scientific abstracts published between 1922 and 2018 in journals that would likely contain materials science research. The resulting word relationships captured fundamental knowledge within the field, including the structure of the periodic table and the way chemicals\u2019 structures relate to their properties.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI analyzed 3.3 million scientific abstracts and discovered possible new materials &#8212; from technologyreview.com Excerpt: A group of researchers have now used this technique to munch through 3.3 million scientific abstracts published between 1922 and 2018 in journals that would likely contain materials science research. The resulting word relationships captured fundamental knowledge within the field, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[356,364],"tags":[],"class_list":["post-67710","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence-agents-llms-and-related","category-chemistry"],"_links":{"self":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/67710","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/comments?post=67710"}],"version-history":[{"count":2,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/67710\/revisions"}],"predecessor-version":[{"id":67712,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/67710\/revisions\/67712"}],"wp:attachment":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/media?parent=67710"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/categories?post=67710"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/tags?post=67710"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}