{"id":3384,"date":"2021-12-08T10:51:00","date_gmt":"2021-12-08T09:51:00","guid":{"rendered":"https:\/\/equipes.lps.u-psud.fr\/theorie\/?page_id=3384"},"modified":"2021-12-08T15:46:52","modified_gmt":"2021-12-08T14:46:52","slug":"mott-materials-for-artificial-intelligence","status":"publish","type":"page","link":"https:\/\/equipes.lps.u-psud.fr\/theorie\/mott-materials-for-artificial-intelligence\/","title":{"rendered":"Mott materials for artificial intelligence"},"content":{"rendered":"\n<div class=\"wp-block-image\"><figure class=\"alignright size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai-1024x305.png\" alt=\"\" class=\"wp-image-3462\" width=\"464\" height=\"138\" srcset=\"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai-1024x305.png 1024w, https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai-300x89.png 300w, https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai-768x229.png 768w, https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai-1536x458.png 1536w, https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-content\/uploads\/sites\/15\/2021\/12\/corr_ai.png 1684w\" sizes=\"auto, (max-width: 464px) 100vw, 464px\" \/><\/figure><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">The human brain has about 10<sup>11<\/sup> neurons and 10<sup>15<\/sup> synapses and needs just about ten watts. That degree of interconnection and power e ciency cannot be achieved with silicon electronics. A new disruptive technology made up of neural networks is required. The implementation of arti cial synapses and arti cial neurons remains however a big challenge. Our team has shown that neurons could be made with quantum materials known as Mott insulators. We aim at a decisive theoretical understanding of out-of- equilibrium physics governing the Mott insulators and how they can form neuromorphic networks.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">J. del Valle, J.G. Ram\u00edrez, M.J. Rozenberg, I.K. Schuller.<br>Challenges in materials and devices for resistive-switching-based neuromorphic computing, Journal of Applied Physics 124, 211101 (2018).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><strong>KEYWORDS<\/strong><\/em><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Artificial Intelligence<\/li><li>Neural Networks<\/li><li>Resistive switching<\/li><li>Out-of-equilibrium Mottronics<\/li><li>Neuromorphic functionalities<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>The human brain has about 1011 neurons and 1015 synapses and needs just about ten watts. That degree of interconnection and power e ciency cannot be achieved with silicon electronics. &#8230;<\/p>\n","protected":false},"author":67,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3384","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/pages\/3384","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/users\/67"}],"replies":[{"embeddable":true,"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/comments?post=3384"}],"version-history":[{"count":4,"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/pages\/3384\/revisions"}],"predecessor-version":[{"id":3506,"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/pages\/3384\/revisions\/3506"}],"wp:attachment":[{"href":"https:\/\/equipes.lps.u-psud.fr\/theorie\/wp-json\/wp\/v2\/media?parent=3384"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}