{"id":12939,"date":"2020-10-19T14:16:25","date_gmt":"2020-10-19T13:16:25","guid":{"rendered":"https:\/\/datascientest.com\/?p=12939"},"modified":"2023-10-28T08:58:29","modified_gmt":"2023-10-28T08:58:29","slug":"machine-learning-technique-ia-lo-shot","status":"publish","type":"post","link":"https:\/\/datascientest.com\/machine-learning-technique-ia-lo-shot","title":{"rendered":"Une nouvelle technique permet d&rsquo;entra\u00eener l&rsquo;IA sans donn\u00e9es"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"12939\" class=\"elementor elementor-12939\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-382a979 e-flex e-con-boxed e-con\" data-id=\"382a979\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7275f09 elementor-widget elementor-widget-heading\" data-id=\"7275f09\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Les chercheurs de l'Universit\u00e9 de Waterloo, dans l'Ontario, aux \u00c9tats-Unis, ont d\u00e9velopp\u00e9 une nouvelle technique de Machine Learning intitul\u00e9e \"LO-Shot Learning\". Elle permet d'entra\u00eener un mod\u00e8le d'intelligence artificielle avec une poign\u00e9e de donn\u00e9es seulement...<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7a37fc1 e-flex e-con-boxed e-con\" data-id=\"7a37fc1\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d1d1d82 elementor-widget elementor-widget-text-editor\" data-id=\"d1d1d82\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>\u00c0 l&rsquo;heure actuelle, le Machine Learning ou apprentissage automatique requiert<strong> de vastes volumes de donn\u00e9es<\/strong>. Pour entra\u00eener une intelligence artificielle, il est n\u00e9cessaire de la \u00ab\u00a0nourrir\u00a0\u00bb \u00e0 l&rsquo;aide de nombreuses donn\u00e9es.<\/p><p>Par exemple, pour apprendre \u00e0 reconna\u00eetre un chat,<strong> une IA devra analyser des milliers de photos de chats<\/strong>. C&rsquo;est la raison pour laquelle cette technologie requiert une lourde puissance de calcul et n\u00e9cessite du temps.<\/p><p>Il s&rsquo;agit aussi d&rsquo;une <strong>diff\u00e9rence majeure entre l&rsquo;intelligence humaine et l&rsquo;intelligence artificielle<\/strong>. En effet, il suffit \u00e0 un enfant de voir quelques exemples d&rsquo;un objet pour pouvoir le reconna\u00eetre toute sa vie.<\/p><p>Pour combler ce foss\u00e9, une <a href=\"https:\/\/arxiv.org\/abs\/2009.08449\" target=\"_blank\" rel=\"noopener\">\u00e9quipe de chercheurs de l&rsquo;Universit\u00e9 de Waterloo<\/a> dans l&rsquo;Ontario a d\u00e9cid\u00e9 de d\u00e9velopper une nouvelle m\u00e9thode permettant \u00e0 une IA de pouvoir reconna\u00eetre <strong>plus d&rsquo;objets que le nombre d&rsquo;exemples<\/strong> sur lesquels elle a \u00e9t\u00e9 entra\u00een\u00e9e. Cette nouvelle m\u00e9thode est intitul\u00e9e \u00ab\u00a0less than one-shot learning\u00a0\u00bb ou \u00ab\u00a0LO-shot learning\u00a0\u00bb.<\/p><blockquote><p>Dans le cadre d&rsquo;une d\u00e9monstration, les chercheurs ont utilis\u00e9 <strong>l&rsquo;ensemble de donn\u00e9es MNIST<\/strong> d\u00e9di\u00e9 \u00e0 la vision par ordinateur. Ce dataset rassemble plus de 60 000 images d&rsquo;entra\u00eenement repr\u00e9sentant des chiffres manuscrits de 0 \u00e0 9.<\/p><\/blockquote>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1507ea9 elementor-widget__width-initial elementor-widget elementor-widget-video\" data-id=\"1507ea9\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/oKzNUGz21JM&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-57ea485 elementor-widget elementor-widget-text-editor\" data-id=\"57ea485\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>En utilisant une technique r\u00e9cemment pr\u00e9sent\u00e9e par le MIT, <strong>les chercheurs ont \u00ab\u00a0compress\u00e9\u00a0\u00bb MNIST<\/strong> en seulement 10 images, optimis\u00e9es pour contenir une quantit\u00e9 d&rsquo;informations \u00e9quivalente \u00e0 l&rsquo;ensemble complet. Ainsi, en s&rsquo;entra\u00eenant seulement sur ces dix images, le mod\u00e8le a pu atteindre la m\u00eame pr\u00e9cision que s&rsquo;il avait \u00e9t\u00e9 entra\u00een\u00e9 sur le <a href=\"https:\/\/datascientest.com\/dataset-definition\">dataset<\/a> complet.<\/p><p>Ils sont all\u00e9s encore plus loin en r\u00e9duisant le nombre d&rsquo;images \u00e0 5. Pour ce faire, ils ont cr\u00e9\u00e9 des images m\u00ealant plusieurs chiffres ensemble. Ces images ont ensuite \u00e9t\u00e9 <strong>fournies \u00e0 l&rsquo;IA avec des \u00e9tiquettes \u00ab\u00a0hybrides\u00a0\u00bb<\/strong>\u00a0capturant les caract\u00e9ristiques partag\u00e9es entre diff\u00e9rents chiffres.<\/p><p>Par exemple,<strong> le chiffre 3 pr\u00e9sente des similitudes avec le chiffre 8<\/strong>. Une image peut donc \u00eatre \u00e9tiquet\u00e9e comme repr\u00e9sentant \u00e0 60% le chiffre 3, \u00e0 30% le chiffre 8, et \u00e0 10% le chiffre 0.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bf51a19 elementor-widget elementor-widget-image\" data-id=\"bf51a19\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"708\" height=\"296\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/sample-lo-shot.png\" class=\"attachment-full size-full wp-image-13042\" alt=\"sample lo shot\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/sample-lo-shot.png 708w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/sample-lo-shot-300x125.png 300w\" sizes=\"(max-width: 708px) 100vw, 708px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Source : Universit\u00e9 de Waterloo<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bdf8624 e-flex e-con-boxed e-con\" data-id=\"bdf8624\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fc63d2c elementor-widget elementor-widget-heading\" data-id=\"fc63d2c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Machine Learning : le LO-Shot Learning permet aux petites entreprises d'acc\u00e9der \u00e0 l'IA<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-65587e0 elementor-widget elementor-widget-text-editor\" data-id=\"65587e0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Apr\u00e8s cette premi\u00e8re tentative r\u00e9ussie de LO-shot learning, les chercheurs ont<strong> tent\u00e9 de trouver les limites de cette m\u00e9thode<\/strong>. Ils se sont alors aper\u00e7us que m\u00eame deux exemples peuvent suffire \u00e0 encoder un nombre illimit\u00e9 de cat\u00e9gories distinctes.<\/p><p>Pour le d\u00e9montrer, l&rsquo;\u00e9quipe s&rsquo;est bas\u00e9e sur l&rsquo;un des algorithmes de Machine Learning les plus simples :<strong> le k-nearest neighbor (kNN)<\/strong> ou m\u00e9thode des k plus proches voisins. Cette m\u00e9thode permet de classifier des objets en utilisant une approche graphique.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-39dd4ec elementor-widget__width-initial elementor-widget elementor-widget-video\" data-id=\"39dd4ec\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=9pvbEP1eyNY&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bcea10c elementor-widget elementor-widget-text-editor\" data-id=\"bcea10c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Une s\u00e9rie de <strong>petits ensembles de donn\u00e9es synth\u00e9tiques<\/strong> a \u00e9t\u00e9 cr\u00e9\u00e9e, avec des \u00e9tiquettes hybrides. L&rsquo;algorithme a ensuite \u00e9t\u00e9 capable de s\u00e9parer le sch\u00e9ma en davantage de cat\u00e9gories qu&rsquo;il n&rsquo;y avait de points de donn\u00e9es.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5fe04d elementor-widget elementor-widget-image\" data-id=\"f5fe04d\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1758\" height=\"954\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot.png\" class=\"attachment-full size-full wp-image-13040\" alt=\"entrainement lo shot\" loading=\"lazy\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot.png 1758w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot-300x163.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot-1024x556.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot-768x417.png 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/entrainemen-lo-shot-1536x834.png 1536w\" sizes=\"(max-width: 1758px) 100vw, 1758px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Source : Universit\u00e9 de Waterloo<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-29325f6 elementor-widget elementor-widget-text-editor\" data-id=\"29325f6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>N\u00e9anmoins, le concept de LO-shot learning pr\u00e9sente encore des faiblesses. S&rsquo;il est applicable \u00e0 un algorithme visuel et interpr\u00e9table comme le <a href=\"https:\/\/datascientest.com\/knn\">kNN<\/a>, <strong>les r\u00e9seaux de neurones sont bien plus complexes<\/strong>. Il est donc tr\u00e8s difficile de concevoir les \u00e9tiquettes.<\/p><p>Par ailleurs, la m\u00e9thode de distillation des donn\u00e9es <strong>requiert un vaste ensemble de donn\u00e9es initial<\/strong> pouvant \u00eatre compress\u00e9. \u00c0 pr\u00e9sent, les chercheurs travaillent \u00e0 une technique permettant l&rsquo;ing\u00e9nierie de ces Data Sets synth\u00e9tiques, manuellement ou \u00e0 l&rsquo;aide d&rsquo;un autre algorithme.<\/p><p>Malgr\u00e9 ces limites, le LO-shot learning pourrait s&rsquo;av\u00e9rer tr\u00e8s utile pour r\u00e9duire la puissance de calcul, le temps et la quantit\u00e9 de donn\u00e9es n\u00e9cessaires \u00e0 l&rsquo;entra\u00eenement des mod\u00e8les d&rsquo;intelligence artificielle. Ainsi,<strong> l&rsquo;IA pourrait devenir accessible<\/strong> aux entreprises et aux industries jusqu&rsquo;\u00e0 pr\u00e9sent frein\u00e9es par ces exigences.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8d544e9 e-flex e-con-boxed e-con\" data-id=\"8d544e9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5e247e3 elementor-widget elementor-widget-text-editor\" data-id=\"5e247e3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Vous savez d\u00e9sormais ce qu&rsquo;est le LO-shot Learning. Pour plus d&rsquo;informations sur le m\u00eame sujet, d\u00e9couvrez <a href=\"https:\/\/datascientest.com\/machine-learning\">notre dossier complet sur le Machine Learning<\/a> et <a href=\"https:\/\/datascientest.com\/clustering-focus-sur-lalgorithme-des-k-moyennes\">notre focus sur l&rsquo;algorithme des k-moyennes<\/a>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Les chercheurs de l&rsquo;Universit\u00e9 de Waterloo, dans l&rsquo;Ontario, aux \u00c9tats-Unis, ont d\u00e9velopp\u00e9 une nouvelle technique de Machine Learning intitul\u00e9e \u00ab\u00a0LO-Shot Learning\u00a0\u00bb. Elle permet d&rsquo;entra\u00eener un mod\u00e8le d&rsquo;intelligence artificielle avec une poign\u00e9e de donn\u00e9es seulement&#8230; \u00c0 l&rsquo;heure actuelle, le Machine Learning ou apprentissage automatique requiert de vastes volumes de donn\u00e9es. Pour entra\u00eener une intelligence artificielle, il [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":13105,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2431],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Une nouvelle technique permet d&#039;entra\u00eener l&#039;IA sans donn\u00e9es<\/title>\n<meta name=\"description\" content=\"Les chercheurs de l&#039;universit\u00e9 de Waterloo ont d\u00e9velopp\u00e9 une nouvelle technique de Machine Learning pour entra\u00eener l&#039;IA avec peu donn\u00e9es.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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