{"id":102366,"date":"2020-02-14T13:08:07","date_gmt":"2020-02-14T21:08:07","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2020\/02\/artificial-intelligence-gets-its-own-system-of-numbers"},"modified":"2020-02-14T13:08:07","modified_gmt":"2020-02-14T21:08:07","slug":"artificial-intelligence-gets-its-own-system-of-numbers","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2020\/02\/artificial-intelligence-gets-its-own-system-of-numbers","title":{"rendered":"Artificial Intelligence Gets Its Own System of Numbers"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/artificial-intelligence-gets-its-own-system-of-numbers2.jpg\"><\/a><\/p>\n<p>BF16, the new number format optimized for deep learning, promises power and compute savings with a minimal reduction in prediction accuracy.<\/p>\n<p>BF16, sometimes called BFloat16 or Brain Float 16, is a new number format optimised for AI\/deep learning applications. Invented at Google Brain, it has gained wide adoption in AI accelerators from Google, Intel, Arm and many others.<\/p>\n<p>The idea behind BF16 is to reduce the compute power and energy consumption needed to multiply tensors together by reducing the precision of the numbers. A tensor is a three-dimensional matrix of numbers; multiplication of tensors is the key mathematical operation required for AI calculations.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>BF16, the new number format optimized for deep learning, promises power and compute savings with a minimal reduction in prediction accuracy. BF16, sometimes called BFloat16 or Brain Float 16, is a new number format optimised for AI\/deep learning applications. Invented at Google Brain, it has gained wide adoption in AI accelerators from Google, Intel, Arm [\u2026]<\/p>\n","protected":false},"author":396,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2229,6],"tags":[],"class_list":["post-102366","post","type-post","status-publish","format-standard","hentry","category-mathematics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/102366","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\/396"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=102366"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/102366\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=102366"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=102366"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=102366"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}