{"id":14514,"date":"2026-05-07T01:16:06","date_gmt":"2026-05-07T01:16:06","guid":{"rendered":"https:\/\/techtrendfeed.com\/?p=14514"},"modified":"2026-05-07T01:16:06","modified_gmt":"2026-05-07T01:16:06","slug":"deep-suppose-is-now-rolling-out","status":"publish","type":"post","link":"https:\/\/techtrendfeed.com\/?p=14514","title":{"rendered":"Deep Suppose is now rolling out"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div>\n<h2 data-block-key=\"zkdtx\">How Deep Suppose works: extending Gemini\u2019s parallel \u201cpondering time\u201d<\/h2>\n<p data-block-key=\"6irie\">Simply as individuals sort out advanced issues by taking the time to discover completely different angles, weigh potential options, and refine a remaining reply, Deep Suppose pushes the frontier of pondering capabilities by utilizing parallel pondering methods. This strategy lets Gemini generate many concepts without delay and take into account them concurrently, even revising or combining completely different concepts over time, earlier than arriving at the perfect reply.<\/p>\n<p data-block-key=\"br919\">Furthermore, by extending the inference time or &#8220;pondering time,&#8221; we give Gemini extra time to discover completely different hypotheses, and arrive at inventive options to advanced issues.<\/p>\n<p data-block-key=\"baesa\">We\u2019ve additionally developed novel reinforcement studying methods that encourage the mannequin to make use of those prolonged reasoning paths, thus enabling Deep Suppose to turn out to be a greater, extra intuitive problem-solver over time.<\/p>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>How Deep Suppose works: extending Gemini\u2019s parallel \u201cpondering time\u201d Simply as individuals sort out advanced issues by taking the time to discover completely different angles, weigh potential options, and refine a remaining reply, Deep Suppose pushes the frontier of pondering capabilities by utilizing parallel pondering methods. This strategy lets Gemini generate many concepts without delay [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":14516,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[55],"tags":[542,4371],"class_list":["post-14514","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning","tag-deep","tag-rolling"],"_links":{"self":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/14514","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14514"}],"version-history":[{"count":1,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/14514\/revisions"}],"predecessor-version":[{"id":14515,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/14514\/revisions\/14515"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/media\/14516"}],"wp:attachment":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14514"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14514"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14514"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<!-- This website is optimized by Airlift. Learn more: https://airlift.net. Template:. Learn more: https://airlift.net. Template: 69d9690a190636c2e0989534. Config Timestamp: 2026-04-10 21:18:02 UTC, Cached Timestamp: 2026-05-07 03:06:07 UTC -->