{"id":138032,"date":"2022-04-12T14:24:44","date_gmt":"2022-04-12T19:24:44","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2022\/04\/how-to-build-brain-inspired-neural-networks-based-on-light"},"modified":"2022-04-12T14:24:44","modified_gmt":"2022-04-12T19:24:44","slug":"how-to-build-brain-inspired-neural-networks-based-on-light","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2022\/04\/how-to-build-brain-inspired-neural-networks-based-on-light","title":{"rendered":"How to build brain-inspired neural networks based on light"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/how-to-build-brain-inspired-neural-networks-based-on-light2.jpg\"><\/a><\/p>\n<p>Supercomputers are extremely fast, but also use a lot of power. Neuromorphic computing, which takes our brain as a model to build fast and energy-efficient computers, can offer a viable and much-needed alternative. The technology has a wealth of opportunities, for example in autonomous driving, interpreting medical images, edge AI or long-haul optical communications. Electrical engineer Patty Stabile is a pioneer when it comes to exploring new brain-and biology-inspired computing paradigms. \u201cTU\/e combines all it takes to demonstrate the possibilities of photon-based neuromorphic computing for AI applications.\u201d<\/p>\n<p>Patty Stabile, an associate professor in the department of Electrical Engineering, was among the first to enter the emerging field of photonic neuromorphic computing.<\/p>\n<p>\u201cI had been working on a proposal to build photonic digital artificial neurons when in 2017 researchers from MIT published an article describing how they developed a small chip for carrying out the same algebraic operations, but in an analog way. That is when I realized that synapses based on analog technology were the way to go for running artificial intelligence, and I have been hooked on the subject ever since.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Supercomputers are extremely fast, but also use a lot of power. Neuromorphic computing, which takes our brain as a model to build fast and energy-efficient computers, can offer a viable and much-needed alternative. The technology has a wealth of opportunities, for example in autonomous driving, interpreting medical images, edge AI or long-haul optical communications. Electrical [\u2026]<\/p>\n","protected":false},"author":599,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,6,44],"tags":[],"class_list":["post-138032","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-robotics-ai","category-supercomputing"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/138032","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\/599"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=138032"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/138032\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=138032"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=138032"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=138032"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}