{"id":200671,"date":"2024-12-03T01:43:38","date_gmt":"2024-12-03T07:43:38","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2024\/12\/photonic-processor-could-enable-ultrafast-ai-computations-with-extreme-energy-efficiency"},"modified":"2024-12-03T01:43:38","modified_gmt":"2024-12-03T07:43:38","slug":"photonic-processor-could-enable-ultrafast-ai-computations-with-extreme-energy-efficiency","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2024\/12\/photonic-processor-could-enable-ultrafast-ai-computations-with-extreme-energy-efficiency","title":{"rendered":"Photonic processor could enable ultrafast AI computations with extreme energy efficiency"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/photonic-processor-could-enable-ultrafast-ai-computations-with-extreme-energy-efficiency3.jpg\"><\/a><\/p>\n<p>The deep neural network models that power today\u2019s most demanding machine-learning applications have grown so large and complex that they are pushing the limits of traditional electronic computing hardware.<\/p>\n<p>Photonic hardware, which can perform machine-learning computations with light, offers a faster and more energy-efficient alternative. However, there are some types of neural network computations that a photonic device can\u2019t perform, requiring the use of off-chip electronics or other techniques that hamper speed and efficiency.<\/p>\n<p>Building on a decade of research, scientists from MIT and elsewhere have developed a new photonic chip that overcomes these roadblocks. They demonstrated a fully integrated photonic processor that can perform all the key computations of a deep neural network optically on the chip.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The deep neural network models that power today\u2019s most demanding machine-learning applications have grown so large and complex that they are pushing the limits of traditional electronic computing hardware. Photonic hardware, which can perform machine-learning computations with light, offers a faster and more energy-efficient alternative. However, there are some types of neural network computations that [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-200671","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/200671","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\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=200671"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/200671\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=200671"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=200671"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=200671"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}