{"id":1177,"date":"2025-01-01T10:00:00","date_gmt":"2025-01-01T09:00:00","guid":{"rendered":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/c\/definition-cot\/"},"modified":"2025-01-01T10:00:00","modified_gmt":"2025-01-01T09:00:00","slug":"definition-cot","status":"publish","type":"post","link":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/c\/definition-cot\/","title":{"rendered":"Cot"},"content":{"rendered":"<p>CoT (Chain-of-Thought) est une technique avanc\u00e9e en prompt engineering qui permet d&rsquo;am\u00e9liorer les performances des mod\u00e8les de langage en les incitant \u00e0 raisonner \u00e9tape par \u00e9tape. Qu&rsquo;est-ce que CoT ?  C&rsquo;est une m\u00e9thode qui guide l&rsquo;IA pour d\u00e9composer un probl\u00e8me complexe en une s\u00e9rie d&rsquo;\u00e9tapes logiques, comme le ferait un humain, avant de fournir une r\u00e9ponse finale.<\/p>\n<h3>Comment fonctionne CoT ?<\/h3>\n<p>CoT encourage les mod\u00e8les de langage \u00e0 expliciter leur raisonnement.  Au lieu de simplement fournir une r\u00e9ponse, l&rsquo;IA est invit\u00e9e \u00e0 d\u00e9tailler les \u00e9tapes interm\u00e9diaires de sa r\u00e9flexion.  Imaginez que vous demandiez \u00e0 quelqu&rsquo;un de r\u00e9soudre un probl\u00e8me math\u00e9matique.  Avec CoT, au lieu de donner directement le r\u00e9sultat, la personne vous expliquerait son calcul \u00e9tape par \u00e9tape : \u00ab\u00a0D&rsquo;abord je fais ceci, ensuite cela, et donc j&rsquo;arrive \u00e0 ce r\u00e9sultat\u00a0\u00bb.  Cette approche permet d&rsquo;obtenir des r\u00e9ponses plus pr\u00e9cises et plus fiables, notamment pour les t\u00e2ches qui requi\u00e8rent un raisonnement logique.<\/p>\n<h3>Pourquoi CoT est-il important ?<\/h3>\n<p>CoT est crucial car il permet d&rsquo;am\u00e9liorer la transparence et la fiabilit\u00e9 des mod\u00e8les de langage. En explicitant le raisonnement de l&rsquo;IA, CoT permet de comprendre comment elle est arriv\u00e9e \u00e0 une conclusion donn\u00e9e. De plus, le fait de d\u00e9composer un probl\u00e8me en plusieurs \u00e9tapes rend plus probable la r\u00e9solution de t\u00e2ches complexes.  Par exemple, pour une question comme : \u00ab Jean a 3 pommes et en donne 2 \u00e0 Marie. Paul a 5 pommes et en re\u00e7oit 1 de la part de Sophie. Combien de pommes ont Jean et Paul au total ? \u00bb, CoT permet \u00e0 l&rsquo;IA de d\u00e9composer le calcul : \u00ab Jean a 3 &#8211; 2 = 1 pomme. Paul a 5 + 1 = 6 pommes. Au total, ils ont 1 + 6 = 7 pommes. \u00bb<\/p>\n<h3>Termes associ\u00e9s<\/h3>\n<ul id=\"TermesAssocies\">\n<li><a href=\"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/?s=Prompt+Engineering\">Prompt Engineering<\/a><\/li>\n<li><a href=\"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/?s=Raisonnement+pas+%C3%A0+pas\">Raisonnement pas \u00e0 pas<\/a><\/li>\n<li><a href=\"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/?s=Mod%C3%A8les+de+langage\">Mod\u00e8les de langage<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>CoT (Chain-of-Thought) est une technique avanc\u00e9e en prompt engineering qui permet d&rsquo;am\u00e9liorer les performances des mod\u00e8les de langage en les incitant \u00e0 raisonner \u00e9tape par \u00e9tape. Qu&rsquo;est-ce que CoT ? C&rsquo;est une m\u00e9thode qui guide l&rsquo;IA pour d\u00e9composer un probl\u00e8me complexe en une s\u00e9rie d&rsquo;\u00e9tapes logiques, comme le ferait un humain, avant de fournir une [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[17],"tags":[647,70,12,570],"class_list":["post-1177","post","type-post","status-publish","format-standard","hentry","category-c","tag-cot","tag-modeles-de-langage","tag-prompt-engineering","tag-raisonnement-pas-a-pas"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"","author_link":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"CoT (Chain-of-Thought) est une technique avanc\u00e9e en prompt engineering qui permet d&rsquo;am\u00e9liorer les performances des mod\u00e8les de langage en les incitant \u00e0 raisonner \u00e9tape par \u00e9tape. Qu&rsquo;est-ce que CoT ? C&rsquo;est une m\u00e9thode qui guide l&rsquo;IA pour d\u00e9composer un probl\u00e8me complexe en une s\u00e9rie d&rsquo;\u00e9tapes logiques, comme le ferait un humain, avant de fournir une\u2026","_links":{"self":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/1177","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/comments?post=1177"}],"version-history":[{"count":0,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/1177\/revisions"}],"wp:attachment":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/media?parent=1177"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/categories?post=1177"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/tags?post=1177"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}