{"id":221652,"date":"2025-09-10T03:42:05","date_gmt":"2025-09-10T08:42:05","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/09\/sustainable-ai-physical-neural-networks-exploit-light-to-train-more-efficiently"},"modified":"2025-09-10T03:42:05","modified_gmt":"2025-09-10T08:42:05","slug":"sustainable-ai-physical-neural-networks-exploit-light-to-train-more-efficiently","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/09\/sustainable-ai-physical-neural-networks-exploit-light-to-train-more-efficiently","title":{"rendered":"Sustainable AI: Physical neural networks exploit light to train more efficiently"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/sustainable-ai-physical-neural-networks-exploit-light-to-train-more-efficiently.jpg\"><\/a><\/p>\n<p>Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models. However, the demand for ever-increasing power and computing capacity is rising faster than the performance traditional computers can provide.<\/p>\n<p>To overcome these limitations, research is moving towards innovative technologies such as physical neural networks, analog circuits that directly exploit the laws of physics (properties of light beams, quantum phenomena) to process information. Their potential is at the heart of the study <a href=\"https:\/\/www.nature.com\/articles\/s41586-025-09384-2\" target=\"_blank\">published<\/a> in the journal <i>Nature<\/i>. It is the outcome of collaboration between several international institutes, including the Politecnico di Milano, the \u00c9cole Polytechnique F\u00e9d\u00e9rale in Lausanne, Stanford University, the University of Cambridge, and the Max Planck Institute.<\/p>\n<p>The article entitled \u201cTraining of Physical Neural Networks\u201d discusses the steps of research on training physical neural networks, carried out with the collaboration of Francesco Morichetti, professor at DEIB\u2014Department of Electronics, Information and Bioengineering, and head of the university\u2019s Photonic Devices Lab.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models. However, the demand for ever-increasing power and computing capacity is rising faster than the performance traditional computers can provide. To overcome these limitations, research is moving towards innovative technologies such as physical neural networks, analog circuits [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1902,1617,6,17],"tags":[],"class_list":["post-221652","post","type-post","status-publish","format-standard","hentry","category-bioengineering","category-quantum-physics","category-robotics-ai","category-sustainability"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/221652","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=221652"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/221652\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=221652"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=221652"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=221652"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}