En intelligence artificielle et en prompt engineering, la g\u00e9n\u00e9ralisation est une capacit\u00e9 essentielle. Qu\u2019est-ce que la g\u00e9n\u00e9ralisation ? C’est la capacit\u00e9 d’un mod\u00e8le d’IA \u00e0 appliquer ce qu’il a appris \u00e0 des donn\u00e9es ou situations nouvelles et inconnues.<\/p>\n
La g\u00e9n\u00e9ralisation est le but ultime de l’apprentissage automatique. Au lieu d’apprendre par c\u0153ur des exemples sp\u00e9cifiques, un mod\u00e8le doit pouvoir extraire les principes sous-jacents des donn\u00e9es d’entra\u00eenement pour les appliquer \u00e0 de nouveaux cas. Imaginez un enfant qui apprend \u00e0 reconna\u00eetre les chats. Apr\u00e8s avoir vu plusieurs exemples de chats, l’enfant peut identifier un chat qu’il n’a jamais vu auparavant, m\u00eame si sa couleur, sa race ou sa posture sont diff\u00e9rentes. C’est la g\u00e9n\u00e9ralisation en action : l’enfant a compris le concept g\u00e9n\u00e9ral de \u00ab\u00a0chat\u00a0\u00bb et ne se limite pas aux exemples pr\u00e9cis qu’on lui a montr\u00e9s.<\/p>\n
En IA, un mod\u00e8le qui g\u00e9n\u00e9ralise bien est un mod\u00e8le performant et utile. Si un mod\u00e8le ne peut pas g\u00e9n\u00e9raliser, il sera limit\u00e9 aux donn\u00e9es d’entra\u00eenement et ne sera pas capable de faire face \u00e0 la complexit\u00e9 du monde r\u00e9el. En prompt engineering, la g\u00e9n\u00e9ralisation est cruciale pour cr\u00e9er des prompts efficaces. Un prompt bien con\u00e7u doit guider le mod\u00e8le pour qu’il g\u00e9n\u00e8re des r\u00e9ponses pertinentes, m\u00eame pour des requ\u00eates l\u00e9g\u00e8rement diff\u00e9rentes. Par exemple, un prompt qui vise \u00e0 g\u00e9n\u00e9rer des descriptions de produits doit fonctionner pour diff\u00e9rents types de produits, et non pas seulement pour ceux utilis\u00e9s dans les exemples d’entra\u00eenement. Un mod\u00e8le capable de g\u00e9n\u00e9ralisation permet d’\u00e9viter le surapprentissage (overfitting), o\u00f9 le mod\u00e8le est trop sp\u00e9cialis\u00e9 aux donn\u00e9es d’entra\u00eenement, et le sous-apprentissage (underfitting), o\u00f9 le mod\u00e8le est trop simpliste pour capturer la complexit\u00e9 des donn\u00e9es.<\/p>\n
En intelligence artificielle et en prompt engineering, la g\u00e9n\u00e9ralisation est une capacit\u00e9 essentielle. Qu\u2019est-ce que la g\u00e9n\u00e9ralisation ? C’est la capacit\u00e9 d’un mod\u00e8le d’IA \u00e0 appliquer ce qu’il a appris \u00e0 des donn\u00e9es ou situations nouvelles et inconnues. Comment fonctionne la g\u00e9n\u00e9ralisation ? La g\u00e9n\u00e9ralisation est le but ultime de l’apprentissage automatique. Au lieu d’apprendre […]<\/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":[68],"tags":[16,125,128,12,331,334],"class_list":["post-902","post","type-post","status-publish","format-standard","hentry","category-g","tag-apprentissage-automatique-machine-learning","tag-donnees-dentrainement","tag-generalisation","tag-prompt-engineering","tag-sous-apprentissage-underfitting","tag-surapprentissage-overfitting"],"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":"En intelligence artificielle et en prompt engineering, la g\u00e9n\u00e9ralisation est une capacit\u00e9 essentielle. Qu\u2019est-ce que la g\u00e9n\u00e9ralisation ? C’est la capacit\u00e9 d’un mod\u00e8le d’IA \u00e0 appliquer ce qu’il a appris \u00e0 des donn\u00e9es ou situations nouvelles et inconnues. Comment fonctionne la g\u00e9n\u00e9ralisation ? La g\u00e9n\u00e9ralisation est le but ultime de l’apprentissage automatique. Au lieu d’apprendre\u2026","_links":{"self":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/902","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=902"}],"version-history":[{"count":1,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/902\/revisions"}],"predecessor-version":[{"id":983,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/902\/revisions\/983"}],"wp:attachment":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/media?parent=902"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/categories?post=902"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/tags?post=902"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}