{"id":176152,"date":"2025-11-15T14:17:00","date_gmt":"2025-11-15T22:17:00","guid":{"rendered":"https:\/\/blog.everpuredata.com\/?p=176152"},"modified":"2025-12-06T15:07:16","modified_gmt":"2025-12-06T23:07:16","slug":"why-storage-is-the-unsung-hero-for-ai","status":"publish","type":"post","link":"https:\/\/blog.everpuredata.com\/fr\/perspectives\/why-storage-is-the-unsung-hero-for-ai\/","title":{"rendered":"Pourquoi le stockage est-il le h\u00e9ros m\u00e9connu de l\u2019AI\u00a0?"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-7387b849 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column has-medium-font-size is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:70%\">\n<div class=\"wp-block-group has-border-color has-pure-orange-100-border-color has-primary-background-color has-background is-layout-flow wp-block-group-is-layout-flow\" style=\"border-width:2px;border-top-left-radius:16px;border-top-right-radius:16px;border-bottom-left-radius:16px;border-bottom-right-radius:16px;padding-top:30px;padding-right:30px;padding-bottom:30px;padding-left:30px\">\n<h3 class=\"wp-block-heading\" id=\"h-summary\">Synth\u00e8se<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Le stockage est le pilier de l\u2019AI, mais \u00e0 mesure que la complexit\u00e9 des mod\u00e8les et l\u2019intensit\u00e9 des donn\u00e9es augmentent, les syst\u00e8mes de stockage traditionnels ne peuvent pas suivre le rythme. Les plateformes de stockage agiles et hautes performances sont essentielles pour r\u00e9pondre aux exigences uniques et \u00e9volutives de l\u2019AI.\u00a0\u00a0<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-group pdf-print-hide is-content-justification-right is-nowrap is-layout-flex wp-container-core-group-is-layout-f726d978 wp-block-group-is-layout-flex\"><div class=\"pdfprnt-buttons\"><a href=\"https:\/\/blog.everpuredata.com\/fr\/wp-json\/wp\/v2\/posts\/176152?print=pdf\" class=\"pdfprnt-button pdfprnt-button-pdf\" target=\"_blank\" ><img decoding=\"async\" src=\"https:\/\/blog.everpuredata.com\/wp-content\/plugins\/pdf-print-pro\/images\/pdf.png?1953174090\" alt=\"image_pdf\" title=\"Afficher le PDF\" \/><\/a><a href=\"https:\/\/blog.everpuredata.com\/fr\/wp-json\/wp\/v2\/posts\/176152?print=print\" class=\"pdfprnt-button pdfprnt-button-print\" target=\"_blank\" ><img decoding=\"async\" src=\"https:\/\/blog.everpuredata.com\/wp-content\/plugins\/pdf-print-pro\/images\/print.png?245231721\" alt=\"image_print\" title=\"Contenu imprim\u00e9\" \/><\/a><\/div>\n<\/div>\n\n\n\n<div id=\"CONTENT\" class=\"wp-block-group is-layout-flow wp-block-group-is-layout-flow\">\n<p class=\"wp-block-paragraph\">Dans la course \u00e0 l\u2019intelligence artificielle g\u00e9n\u00e9rale (AGI), la technologie de stockage ouvre la voie. Alors que les algorithmes et le calcul mettent en lumi\u00e8re les avanc\u00e9es de l\u2019AI, le stockage en est le moteur. Au cours de la r\u00e9volution flash, les disques 15K00 ont stagn\u00e9, les performances de calcul ayant doubl\u00e9 tous les deux ans, mais la virtualisation flash est activ\u00e9e et, aujourd\u2019hui, les charges de travail pilot\u00e9es par GPU stimulent l\u2019innovation en mati\u00e8re de stockage, tout en exigeant efficacit\u00e9, durabilit\u00e9 et fiabilit\u00e9.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Les premiers efforts d\u2019AI \u00e9taient limit\u00e9s par la complexit\u00e9 algorithmique et la raret\u00e9 des donn\u00e9es, mais \u00e0 mesure que les algorithmes avan\u00e7aient, des goulets d\u2019\u00e9tranglement sur la m\u00e9moire et le stockage \u00e9mergeaient. Le stockage haute performance a permis d\u2019exploiter des innovations comme ImageNet, qui a aliment\u00e9 les mod\u00e8les de vision, et GPT-3, qui n\u00e9cessitait des p\u00e9taoctets de stockage. Avec <a href=\"https:\/\/explodingtopics.com\/blog\/data-generated-per-day\" target=\"_blank\" rel=\"noreferrer noopener\">400 millions de t\u00e9raoctets de donn\u00e9es g\u00e9n\u00e9r\u00e9s quotidiennement<\/a>, le stockage doit g\u00e9rer les charges de travail \u00e0 l\u2019\u00e9chelle de l\u2019exaoctet avec une latence inf\u00e9rieure \u00e0 la milliseconde pour alimenter l\u2019AGI et le Machine Learning quantique. \u00c0 mesure que l\u2019AI progressait, chaque vague d\u2019innovation a impos\u00e9 de nouvelles exigences au stockage, entra\u00eenant des progr\u00e8s en termes de capacit\u00e9, de vitesse et d\u2019\u00e9volutivit\u00e9 pour s\u2019adapter \u00e0 des mod\u00e8les de plus en plus complexes et \u00e0 des ensembles de donn\u00e9es plus volumineux.<br\/><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Machine Learning classique (1980s-2015)\u00a0:<\/strong> La reconnaissance vocale et les mod\u00e8les d\u2019apprentissage supervis\u00e9 ont entra\u00een\u00e9 la croissance des ensembles de donn\u00e9es, passant de m\u00e9gaoctets \u00e0 gigaoctets, rendant la r\u00e9cup\u00e9ration des donn\u00e9es et l\u2019organisation de plus en plus critiques.<\/li>\n\n\n\n<li><strong>R\u00e9volution du deep learning (2012-2017)\u00a0: <\/strong>Des mod\u00e8les comme AlexNet et ResNet ont pouss\u00e9 les exigences de stockage, tandis que Word2Vec et GloVe ont avanc\u00e9 le traitement du langage naturel, passant au stockage NVMe haute vitesse pour les ensembles de donn\u00e9es \u00e0 l\u2019\u00e9chelle du t\u00e9raoctet.<\/li>\n\n\n\n<li><strong>Mod\u00e8les de base (de 2018 \u00e0 aujourd\u2019hui)\u00a0: <\/strong>BERT a introduit des jeux de donn\u00e9es de l\u2019\u00e9chelle du p\u00e9taoctet, avec GPT-3 et Llama 3 n\u00e9cessitant des syst\u00e8mes \u00e9volutifs \u00e0 faible latence comme Tectonic de Meta pour g\u00e9rer des billions de jetons et supporter un d\u00e9bit de 7TB\/s.<\/li>\n\n\n\n<li><strong>Lois Chinchilla sur l\u2019\u00e9volutivit\u00e9 (2022)\u00a0: <\/strong>Chinchilla a mis l\u2019accent sur la croissance des ensembles de donn\u00e9es plut\u00f4t que sur la taille du mod\u00e8le LLM, n\u00e9cessitant un stockage \u00e0 acc\u00e8s parall\u00e8le pour optimiser les performances.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Le stockage ne se contente pas de prendre en charge l\u2019AI\u00a0: il ouvre la voie \u00e0 l\u2019avenir de l\u2019innovation en g\u00e9rant efficacement et \u00e0 grande \u00e9chelle les donn\u00e9es en constante croissance dans le monde. Par exemple, les applications d\u2019AI dans la <a href=\"https:\/\/blog.everpuredata.com\/news-events\/ai-and-automotive-a-conversation-with-nvidia-and-pure-storage\/\" target=\"_blank\" rel=\"noreferrer noopener\">conduite autonome<\/a> reposent sur des <a href=\"https:\/\/www.purestorage.com\/ai\" target=\"_blank\" rel=\"noreferrer noopener\">plateformes de stockage<\/a> capables de traiter des p\u00e9taoctets de donn\u00e9es de capteurs en temps r\u00e9el, tandis que la <a href=\"https:\/\/blog.everpuredata.com\/perspectives\/modern-flash-storage-genomics-2\/\">recherche g\u00e9nomique<\/a> n\u00e9cessite un acc\u00e8s rapide \u00e0 des ensembles de donn\u00e9es massifs pour acc\u00e9l\u00e9rer les d\u00e9couvertes. Alors que l\u2019AI repousse les limites de la gestion des donn\u00e9es, les syst\u00e8mes de stockage traditionnels sont confront\u00e9s \u00e0 des difficult\u00e9s croissantes pour s\u2019adapter \u00e0 l\u2019\u00e9volution de ces exigences, ce qui souligne la n\u00e9cessit\u00e9 de solutions sp\u00e9cialement con\u00e7ues.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-how-ai-workloads-strain-traditional-storage-systems\">Comment les charges de travail d\u2019AI freinent les syst\u00e8mes de stockage traditionnels<\/h2>\n\n\n\n<h4 class=\"wp-block-heading has-secondary-color has-text-color has-link-color wp-elements-1\" id=\"h-data-consolidation-and-volume-management\"><strong>Consolidation des donn\u00e9es et gestion des volumes<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Les applications d\u2019AI g\u00e8rent des ensembles de donn\u00e9es allant de plusieurs t\u00e9raoctets \u00e0 des centaines de p\u00e9taoctets, d\u00e9passant largement les capacit\u00e9s des syst\u00e8mes de stockage traditionnels tels que NAS, SAN et le stockage en attachement direct traditionnel. Ces syst\u00e8mes, con\u00e7us pour des charges de travail transactionnelles pr\u00e9cises, telles que la g\u00e9n\u00e9ration de rapports ou la r\u00e9cup\u00e9ration d\u2019enregistrements sp\u00e9cifiques, ont du mal \u00e0 faire face aux exigences d\u2019agr\u00e9gation de la science des donn\u00e9es et aux sch\u00e9mas d\u2019acc\u00e8s \u00e0 grande vitesse des charges de travail AI\/ML. L\u2019apprentissage des mod\u00e8les, qui n\u00e9cessite une r\u00e9cup\u00e9ration massive des donn\u00e9es par lots sur l\u2019ensemble des ensembles de donn\u00e9es, met en \u00e9vidence ce d\u00e9salignement. Les architectures rigides, les contraintes de capacit\u00e9 et le d\u00e9bit insuffisant de l\u2019infrastructure traditionnelle la rendent inadapt\u00e9e \u00e0 l\u2019\u00e9volutivit\u00e9 et \u00e0 la vitesse de l\u2019AI, soulignant ainsi le besoin de plateformes de stockage sp\u00e9cialement con\u00e7ues.<\/p>\n\n\n\n<h4 class=\"wp-block-heading has-secondary-color has-text-color has-link-color wp-elements-2\" id=\"h-performance-bottlenecks-for-high-speed-data-access\"><strong>Goulets d\u2019\u00e9tranglement des performances pour un acc\u00e8s rapide aux donn\u00e9es<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">L\u2019analytique et la prise de d\u00e9cisions en temps r\u00e9el sont essentielles pour les charges de travail d\u2019AI, mais les architectures de stockage traditionnelles cr\u00e9ent souvent des goulets d\u2019\u00e9tranglement avec des IOPS insuffisantes, car elles ont \u00e9t\u00e9 con\u00e7ues pour des t\u00e2ches transactionnelles mod\u00e9r\u00e9es plut\u00f4t que pour les exigences de lecture\/\u00e9criture intensives et parall\u00e8les de l\u2019AI. De plus, la latence \u00e9lev\u00e9e due aux disques rotatifs ou aux m\u00e9canismes de mise en cache obsol\u00e8tes retarde l\u2019acc\u00e8s aux donn\u00e9es, ce qui acc\u00e9l\u00e8re l\u2019Insight d\u2019informations strat\u00e9giques et r\u00e9duit l\u2019efficacit\u00e9 des processus d\u2019AI.<\/p>\n\n\n\n<h4 class=\"wp-block-heading has-secondary-color has-text-color has-link-color wp-elements-3\" id=\"h-handling-diverse-data-types-and-workloads\"><strong>Gestion de diff\u00e9rents types de donn\u00e9es et charges de travail<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Les syst\u00e8mes d\u2019AI traitent \u00e0 la fois les donn\u00e9es structur\u00e9es et non structur\u00e9es, y compris le texte, les images, l\u2019audio et la vid\u00e9o, mais les solutions de stockage traditionnelles sont confront\u00e9es \u00e0 cette diversit\u00e9. Elles sont souvent optimis\u00e9es pour les donn\u00e9es structur\u00e9es, ce qui entra\u00eene une r\u00e9cup\u00e9ration lente et un traitement inefficace des formats non structur\u00e9s. De plus, une mauvaise gestion de l\u2019indexation et des m\u00e9tadonn\u00e9es rend difficile l\u2019organisation et la recherche efficace de diff\u00e9rents ensembles de donn\u00e9es. Les syst\u00e8mes traditionnels sont \u00e9galement confront\u00e9s \u00e0 des probl\u00e8mes de performance avec les petits fichiers, courants dans les mod\u00e8les linguistiques d\u2019entra\u00eenement, car les m\u00e9tadonn\u00e9es \u00e9lev\u00e9es entra\u00eenent des retards et des temps de traitement plus longs.<\/p>\n\n\n\n<h4 class=\"wp-block-heading has-secondary-color has-text-color has-link-color wp-elements-4\" id=\"h-legacy-architecture-limitations\"><strong>Limites de l\u2019architecture traditionnelle<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Ces d\u00e9fis se cumulent en raison du fait que les architectures de stockage traditionnelles ne peuvent pas r\u00e9pondre aux exigences des charges de travail d\u2019AI modernes. Elles manquent de l\u2019agilit\u00e9, des performances et de l\u2019\u00e9volutivit\u00e9 n\u00e9cessaires pour r\u00e9pondre aux besoins de l\u2019AI en mati\u00e8re de donn\u00e9es diverses et volumineuses. Ces limites soulignent la n\u00e9cessit\u00e9 de solutions de stockage avanc\u00e9es con\u00e7ues pour relever les d\u00e9fis uniques des applications d\u2019AI, notamment l\u2019\u00e9volutivit\u00e9 rapide, le haut d\u00e9bit, la faible latence et la diversit\u00e9 de la gestion des donn\u00e9es.\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-key-storage-challenges-in-ai\">Principaux d\u00e9fis du stockage dans l\u2019AI<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Les charges de travail d\u2019AI imposent des exigences uniques aux syst\u00e8mes de stockage, et relever ces d\u00e9fis n\u00e9cessite des capacit\u00e9s avanc\u00e9es dans les domaines suivants\u00a0:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Consolidation unifi\u00e9e des donn\u00e9es\u00a0:<\/strong> Les silos de donn\u00e9es fragmentent des informations pr\u00e9cieuses, n\u00e9cessitant une consolidation dans une plateforme unifi\u00e9e qui prend en charge diverses charges de travail d\u2019AI pour un traitement et une formation fluides.<\/li>\n\n\n\n<li><strong>Performances et capacit\u00e9 \u00e9volutives\u00a0:<\/strong> Une plateforme de stockage robuste doit g\u00e9rer diff\u00e9rents profils I\/O et \u00e9voluer de t\u00e9raoctets \u00e0 exaoctets, garantissant ainsi un acc\u00e8s \u00e0 faible latence et haut d\u00e9bit. En permettant une \u00e9volutivit\u00e9 sans interruption, la plateforme permet aux charges de travail d\u2019AI de s\u2019\u00e9tendre en toute transparence \u00e0 mesure que les besoins en donn\u00e9es augmentent, tout en assurant des op\u00e9rations fluides et ininterrompues.<\/li>\n\n\n\n<li><strong>Flexibilit\u00e9 scale-up et scale-out\u00a0: <\/strong>Pour g\u00e9rer l\u2019acc\u00e8s transactionnel \u00e0 faible latence pour les bases de donn\u00e9es vectorielles et les charges de travail \u00e0 forte simultan\u00e9it\u00e9 pour l\u2019entra\u00eenement et l\u2019inf\u00e9rence, il faut une plateforme qui offre les deux capacit\u00e9s.<\/li>\n\n\n\n<li><strong>Fiabilit\u00e9 et disponibilit\u00e9 continue\u00a0:<\/strong> \u00c0 mesure que l\u2019AI devient essentielle pour les entreprises, une disponibilit\u00e9 de 99,9999\u00a0% est essentielle. Une plateforme de stockage doit prendre en charge les mises \u00e0 niveau sans interruption et les actualisations mat\u00e9rielles, garantissant ainsi un fonctionnement continu sans interruption visible pour les utilisateurs finaux.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-optimizing-storage-across-the-ai-pipeline\">Optimisation du stockage sur l\u2019ensemble du pipeline d\u2019AI <\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Des solutions de stockage efficaces sont essentielles \u00e0 chaque \u00e9tape du pipeline d\u2019AI, de la conservation des donn\u00e9es \u00e0 l\u2019entra\u00eenement et \u00e0 l\u2019inf\u00e9rence, car elles permettent aux charges de travail d\u2019AI de fonctionner efficacement et \u00e0 grande \u00e9chelle. Les pipelines d\u2019AI ont besoin d\u2019un stockage capable de g\u00e9rer en toute transparence les t\u00e2ches sensibles \u00e0 la latence, d\u2019\u00e9voluer pour r\u00e9pondre aux exigences de forte simultan\u00e9it\u00e9, de prendre en charge diff\u00e9rents types de donn\u00e9es et de maintenir les performances dans les environnements distribu\u00e9s.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXfpGtQHeFat1Lsld0nPQfkQ5Ee1znjhHAPb_0YyxqdkQTZ7rS_AAAuIvcZEGX0H7fUTqpBGw1Fs6HgS0MGq0ZlRdtsjWUaXDeKSOwq6x9ddHwQMlxZJ2GhpD_68zlw08M5SPI7ftuQdn4wax21TthhVVKY?key=Z9svlj5qAS1uXFkcPyX93A\" alt=\"Conservation des donn&#xE9;es\"\/><\/figure>\n\n\n\n<h6 class=\"wp-block-heading has-text-align-center\" id=\"h-figure-1-storage-patterns-for-ai-are-varied-and-require-a-platform-built-for-multi-dimensional-performance\"><em>Figure\u00a01\u00a0: Les sch\u00e9mas de stockage pour l\u2019AI sont vari\u00e9s et n\u00e9cessitent une plateforme con\u00e7ue pour des performances multidimensionnelles.<\/em><\/h6>\n\n\n\n<p class=\"wp-block-paragraph\">\u00c0 l\u2019\u00e9tape de la conservation des donn\u00e9es, la gestion des ensembles de donn\u00e9es \u00e0 l\u2019\u00e9chelle du p\u00e9taoctet \u00e0 l\u2019exaoctet commence par l\u2019ingestion, o\u00f9 le stockage doit \u00e9voluer en toute transparence pour g\u00e9rer des volumes de donn\u00e9es massifs tout en garantissant un d\u00e9bit \u00e9lev\u00e9. Les applications en temps r\u00e9el, comme la conduite autonome, n\u00e9cessitent un stockage \u00e0 faible latence capable de traiter instantan\u00e9ment les donn\u00e9es entrantes. Les <a href=\"https:\/\/blog.everpuredata.com\/perspectives\/escaping-the-ssd-trap-pure-storage-directflash-module\/\">modules DirectFlash\u00ae (DFM)<\/a> excellent dans ces sc\u00e9narios en contournant les architectures SSD traditionnelles pour acc\u00e9der directement \u00e0 la m\u00e9moire flash NAND, offrant des performances plus rapides et plus coh\u00e9rentes avec une latence consid\u00e9rablement r\u00e9duite. Par rapport aux SSD et SCM traditionnels, les DFM offrent \u00e9galement une plus grande efficacit\u00e9 \u00e9nerg\u00e9tique, ce qui permet aux organisations de r\u00e9pondre aux exigences des charges de travail d\u2019AI \u00e0 grande \u00e9chelle tout en optimisant la consommation d\u2019\u00e9nergie et en maintenant des performances pr\u00e9visibles dans des conditions de forte simultan\u00e9it\u00e9.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Pendant la persistance, les solutions de stockage de donn\u00e9es doivent prendre en charge la conservation \u00e0 long terme et l\u2019accessibilit\u00e9 rapide des donn\u00e9es fr\u00e9quemment consult\u00e9es. L\u2019\u00e9tape de traitement est essentielle pour pr\u00e9parer les donn\u00e9es \u00e0 l\u2019entra\u00eenement, o\u00f9 le stockage doit g\u00e9rer efficacement une vari\u00e9t\u00e9 de types et de tailles de donn\u00e9es, en traitant les donn\u00e9es structur\u00e9es et non structur\u00e9es dans des formats tels que NFS, SMB et objet.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Dans la phase d\u2019entra\u00eenement et d\u2019inf\u00e9rence par l\u2019AI, l\u2019entra\u00eenement par mod\u00e8le g\u00e9n\u00e8re des exigences de lecture\/\u00e9criture intensives, n\u00e9cessitant des architectures scale-out pour garantir les performances sur plusieurs n\u0153uds. \u00c0 ce stade, il est essentiel de disposer de syst\u00e8mes de contr\u00f4le de version et de point de contr\u00f4le efficaces pour \u00e9viter la perte de donn\u00e9es. Outre le point de contr\u00f4le, les architectures \u00e9mergentes telles que la <a href=\"https:\/\/blog.everpuredata.com\/perspectives\/optimize-genai-apps-with-rag-from-pure-storage-and-nvidia\/\">g\u00e9n\u00e9ration augment\u00e9e par r\u00e9cup\u00e9ration (RAG)<\/a> pr\u00e9sentent des d\u00e9fis uniques pour les syst\u00e8mes de stockage. RAG s\u2019appuie sur une r\u00e9cup\u00e9ration efficace des bases de connaissances externes pendant l\u2019inf\u00e9rence, exigeant un stockage \u00e0 faible latence et haut d\u00e9bit capable de g\u00e9rer des requ\u00eates parall\u00e8les simultan\u00e9es. La <a href=\"https:\/\/blog.everpuredata.com\/products\/unlocking-the-power-of-metadata-management-with-flashblade\/\">gestion des m\u00e9tadonn\u00e9es <\/a> et l\u2019indexation \u00e9volutive sont donc soumises \u00e0 une pression accrue, ce qui n\u00e9cessite des architectures de stockage avanc\u00e9es pour optimiser les performances sans goulets d\u2019\u00e9tranglement.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">En alignant les solutions de stockage sur les besoins sp\u00e9cifiques de chaque \u00e9tape du pipeline, les organisations peuvent optimiser les performances de l\u2019AI et maintenir la flexibilit\u00e9 n\u00e9cessaire pour r\u00e9pondre \u00e0 l\u2019\u00e9volution des besoins en AI.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-i-ntroducing-the-data-stream-solution\"><strong>Pr\u00e9sentation de la solution de flux de donn\u00e9es<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Pour r\u00e9soudre le goulet d\u2019\u00e9tranglement persistant li\u00e9 \u00e0 la pr\u00e9paration des donn\u00e9es brutes pour les flux de travail d\u2019AI, Pure Storage vient de <strong>lancer<a href=\"https:\/\/blog.everpuredata.com\/products\/driving-the-future-of-ai-data-readiness-pure-storage-data-stream\/\">Data Stream<\/a><\/strong>, une pile mat\u00e9rielle et logicielle int\u00e9gr\u00e9e centr\u00e9e sur les GPU graphiques et d\u00e9velopp\u00e9e sp\u00e9cifiquement pour la pr\u00e9paration des donn\u00e9es d\u2019AI.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Contrairement aux syst\u00e8mes de stockage traditionnels qui contiennent simplement des donn\u00e9es, le flux de donn\u00e9es automatise activement l\u2019ingestion, la transformation et l\u2019optimisation. Il transforme ensuite les actifs non structur\u00e9s (documents, images, tableaux) en vecteurs et m\u00e9tadonn\u00e9es compatibles avec l\u2019AI \u00e0 grande \u00e9chelle.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Le flux de donn\u00e9es ing\u00e8re d\u2019\u00e9normes volumes de fichiers provenant de sources multiprotocoles (NFS, SMB, S3), effectue un \u00ab\u00a0chunking\u00a0\u00bb s\u00e9mantique (par exemple, phrases, paragraphes) pour pr\u00e9server le contexte, puis enrichit et d\u00e9livre la sortie dans des formats optimis\u00e9s pour les bases de donn\u00e9es vectorielles et les pipelines d\u2019inf\u00e9rence GPU.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">En int\u00e9grant ce traitement dans la couche de stockage elle-m\u00eame, le flux de donn\u00e9es comble le foss\u00e9 entre l\u2019inertie des donn\u00e9es brutes et l\u2019inf\u00e9rence de l\u2019AI en temps r\u00e9el, ce qui permet aux entreprises de r\u00e9duire les mois de pr\u00e9paration des donn\u00e9es en quelques minutes. Vous pouvez ainsi vous assurer que leurs processeurs graphiques restent aliment\u00e9s, que leurs mod\u00e8les restent \u00e0 jour et que leurs pipelines d\u2019inf\u00e9rence fonctionnent sans interruption.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conclusion\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Le stockage est le pilier de l\u2019AI, avec une complexit\u00e9 croissante des mod\u00e8les et une intensit\u00e9 des donn\u00e9es qui entra\u00eenent des demandes exponentielles sur l\u2019infrastructure. Les architectures de stockage traditionnelles ne peuvent pas r\u00e9pondre \u00e0 ces besoins, ce qui rend indispensable l\u2019adoption de solutions de stockage agiles et haute performance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">La relation symbiotique entre l\u2019AI et les plateformes de stockage signifie que les progr\u00e8s r\u00e9alis\u00e9s en mati\u00e8re de stockage ne se limitent pas \u00e0 la prise en charge, mais acc\u00e9l\u00e8rent \u00e9galement les progr\u00e8s r\u00e9alis\u00e9s en mati\u00e8re AI. Pour les entreprises qui commencent tout juste \u00e0 explorer l\u2019AI, la flexibilit\u00e9 est cruciale\u00a0: Ils ont besoin d\u2019un stockage capable d\u2019\u00e9voluer \u00e0 mesure que leurs besoins en donn\u00e9es et en calcul augmentent, de prendre en charge plusieurs formats (fichier, objet, etc.) et de s\u2019int\u00e9grer facilement aux outils existants.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Les entreprises qui investissent dans des plateformes de stockage modernes se positionnent \u00e0 la pointe de l\u2019innovation. Cela n\u00e9cessite\u00a0:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\u00c9valuation de l\u2019infrastructure\u00a0:<\/strong> Identifier les limites actuelles et les domaines \u00e0 am\u00e9liorer imm\u00e9diatement.<\/li>\n\n\n\n<li><strong>Adopter des solutions \u00e9volutives\u00a0:<\/strong> Mettez en \u0153uvre des plateformes qui offrent flexibilit\u00e9, haute performance et croissance fluide.<\/li>\n\n\n\n<li><strong>Planification des besoins futurs\u00a0: <\/strong>Gardez une longueur d\u2019avance sur les tendances \u00e9mergentes pour vous assurer que la plateforme \u00e9volue avec les d\u00e9veloppements de l\u2019AI.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">En privil\u00e9giant les plateformes de stockage comme un \u00e9l\u00e9ment essentiel de la strat\u00e9gie d\u2019AI, les organisations peuvent saisir de nouvelles opportunit\u00e9s, stimuler l\u2019innovation continue et conserver un avantage concurrentiel dans un avenir ax\u00e9 sur les donn\u00e9es.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Vous souhaitez en savoir plus\u00a0?<\/p>\n\n\n\n<p class=\"has-text-align-center wp-block-paragraph\">Consultez la <a href=\"https:\/\/www.google.com\/url?sa=t&amp;source=web&amp;rct=j&amp;opi=89978449&amp;url=https:\/\/www.purestorage.com\/solutions\/ai.html&amp;ved=2ahUKEwjGjMWHhZuKAxVJBdAFHUCeBIEQFnoECBEQAQ&amp;usg=AOvVaw0KVGJxecPqC5aHWSSLFQ0K\">page consacr\u00e9e aux solutions d\u2019AI <\/a><\/p>\n\n\n\n<p class=\"has-text-align-center wp-block-paragraph\">T\u00e9l\u00e9charger le livre blanc\u00a0: \u00ab\u00a0<a href=\"https:\/\/www.purestorage.com\/content\/dam\/pdf\/en\/white-papers\/bwp-the-pure-data-storage-platform-for-ai.pdf\">La plateforme Pure Storage pour l\u2019AI<\/a>\u00a0\u00bb<\/p>\n\n\n\n<div class=\"wp-block-group has-global-padding is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-group box-shadow is-layout-flow wp-block-group-is-layout-flow\">\n<div class=\"wp-block-cover is-light\" style=\"min-height:300px;aspect-ratio:unset;\"><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-0 has-background-dim\"><\/span><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"305\" class=\"wp-block-cover__image-background wp-image-152548\" alt=\"AI Data Platform\" src=\"https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-1024x305.png\" style=\"object-position:82% 49%\" data-object-fit=\"cover\" data-object-position=\"82% 49%\" srcset=\"https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-1024x305.png 1024w, https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-728x217.png 728w, https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-768x229.png 768w, https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-1536x458.png 1536w, https:\/\/blog.everpuredata.com\/wp-content\/uploads\/2024\/12\/AI-Data-Platform-2048x611.png 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><div class=\"wp-block-cover__inner-container has-global-padding is-layout-constrained wp-container-core-cover-is-layout-52e20806 wp-block-cover-is-layout-constrained\">\n<div class=\"wp-block-columns is-not-stacked-on-mobile is-layout-flex wp-container-core-columns-is-layout-1c666923 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-vertically-aligned-center is-layout-flow wp-container-core-column-is-layout-9053edae wp-block-column-is-layout-flow\" style=\"flex-basis:60%\">\n<div class=\"wp-block-group is-layout-flow wp-block-group-is-layout-flow\" style=\"margin-top:0px;margin-bottom:0px;padding-top:0px;padding-bottom:0px\">\n<p class=\"has-contrast-color has-text-color has-link-color wp-elements-5 wp-block-paragraph\" style=\"font-size:0.6rem\">Livre blanc Pure Storage Business<\/p>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading has-contrast-color has-text-color has-link-color wp-elements-6\" id=\"h-the-pure-storage-platform-for-ai-accelerates-and-simplifies-ai-deployments\" style=\"margin-top:0px;margin-bottom:20px;font-size:clamp(1.352rem, 1.352rem + ((1vw - 0.2rem) * 1.413), 2.2rem);line-height:1.2\">Pure Storage<br\/>La plateforme d\u2019AI s\u2019acc\u00e9l\u00e8re <br\/>et simplifie les d\u00e9ploiements d\u2019AI <\/h2>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-left is-nowrap is-layout-flex wp-container-core-buttons-is-layout-0fdbba7e wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button has-custom-font-size\" style=\"font-size:clamp(0.875rem, 0.875rem + ((1vw - 0.2rem) * 0.208), 1rem);line-height:1.2\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/www.purestorage.com\/content\/dam\/pdf\/en\/white-papers\/bwp-the-pure-data-storage-platform-for-ai.pdf\" style=\"background:linear-gradient(190deg,rgba(252,185,0,1) 0%,rgba(255,105,0,1) 100%);padding-top:10px;padding-right:14px;padding-bottom:10px;padding-left:14px\" target=\"_blank\" rel=\"noreferrer noopener\">Lire le livre blanc<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:30%\">\n<div class=\"wp-block-group sticky-content has-mint-green-500-background-color has-background is-layout-flow wp-block-group-is-layout-flow\" style=\"border-radius:20px;padding-top:20px;padding-right:20px;padding-bottom:20px;padding-left:20px\">\n<h2 class=\"wp-block-heading has-text-align-center has-ash-gray-500-color has-text-color has-link-color wp-elements-7\" id=\"h-title\" style=\"font-size:px\">Une r\u00e9volution en mati\u00e8re d\u2019AI<\/h2>\n\n\n\n<p class=\"has-text-align-center has-ash-gray-500-color has-text-color has-link-color wp-elements-8 wp-block-paragraph\" style=\"font-size:clamp(0.875rem, 0.875rem + ((1vw - 0.2rem) * 0.208), 1rem);\">Acc\u00e9l\u00e9rez vos initiatives d\u2019AI avec la plateforme Pure Storage.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-f8bdad00 wp-block-buttons-is-layout-flex\" style=\"margin-top:1em;margin-bottom:1em\">\n<div class=\"wp-block-button is-style-outline button-sticky is-style-outline--2\"><a class=\"wp-block-button__link has-cloud-white-500-color has-basil-green-500-background-color has-text-color has-background has-link-color has-inter-font-family has-custom-font-size wp-element-button\" href=\"https:\/\/www.purestorage.com\/solutions\/ai.html\" style=\"border-style:none;border-width:0px;border-radius:4px;padding-top:14px;padding-right:16px;padding-bottom:14px;padding-left:16px;font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.208), 16px);\" target=\"_blank\" rel=\"noreferrer noopener\">Learn More<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Des v\u00e9hicules autonomes \u00e0 la recherche g\u00e9nomique, l\u2019AI repousse les limites du possible. D\u00e9couvrez comment le stockage contribue \u00e0 acc\u00e9l\u00e9rer ces d\u00e9couvertes. <\/p>\n","protected":false},"author":714,"featured_media":152632,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_ppma_block_editor_authors":""},"categories":[13866],"tags":[13944,15286],"content-position":[15559],"ppma_author":[14468],"class_list":["post-176152","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-perspectives","tag-ai-and-machine-learning-fr","tag-ai-generative","content-position-featured-articles-fr"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.6 (Yoast SEO v28.6) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Acc\u00e9l\u00e9rer l\u2019AI gr\u00e2ce \u00e0 des solutions de stockage plus intelligentes et \u00e9volutives | Everpure Blog<\/title>\n<meta name=\"description\" content=\"Des v\u00e9hicules autonomes \u00e0 la recherche g\u00e9nomique, l\u2019AI repousse les limites du possible. 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