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aem-GridColumn--default--12"},"columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-45e14dc9dc","text":"\u003Cp\u003EAujourd’hui, nous sommes ravis d’annoncer Snowflake Cortex AISQL en public preview, qui intègre de puissantes fonctionnalités d’IA directement dans le moteur SQL de Snowflake. Cortex AISQL permet à nos clients de créer des pipelines d’IA évolutifs sur des données d’entreprise multimodales avec des commandes SQL familières. Traitez du texte (public preview), des images (public preview) et de l’audio (public preview bientôt) plus rapidement et de manière plus rentable et obtenez des informations plus approfondies à partir de données structurées et non structurées en même temps.\u003C/p\u003E\r\n\u003Cp\u003EL’analyse de données subit une profonde transformation, portée par l’IA. Les entreprises d'aujourd'hui savent que les informations précieuses vont bien au-delà des données tabulaires traditionnelles : elles sont souvent intégrées dans diverses sources non structurées telles que des documents, des images et des fichiers audio. \u003C/p\u003E\r\n\u003Cp\u003EÀ mesure que la variété des données augmente, les analyses nécessitent des processus en plusieurs étapes de plus en plus sophistiqués pour extraire, synthétiser et combiner des informations provenant de différentes sources. Cependant, l’analyse de cette riche mosaïque de données à l’échelle de l’entreprise présente des défis techniques et opérationnels importants. \u003C/p\u003E\r\n\u003Cp\u003ELes entreprises peinent à rassembler divers outils spécialisés et ensembles de compétences pour traiter et analyser ces informations, compromettant ainsi leur efficacité et leur évolutivité tout en entraînant des informations retardées et de moindre qualité.\u003C/p\u003E\r\n\u003Cp\u003EPour relever ces défis, Snowflake intègre de puissantes fonctionnalités d’IA générative directement dans son moteur SQL central, permettant ainsi aux analystes d’accomplir davantage en moins de temps grâce aux outils suivants :\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EOpérateurs d’IA expressifs et composables\u003C/b\u003E : un nouvel ensemble d’opérateurs alimentés par l’IA qui effectue un mappage en toute transparence avec les primitives SQL existantes telles que FILTER et AGGREGATE. Ainsi, les analystes peuvent facilement créer des pipelines d’IA évolutifs à l’aide de commandes SQL familières pour détecter de subtiles anomalies dans les données opérationnelles, agréger des informations exploitables à partir des transcriptions des appels clients ou classer de vastes bibliothèques d’images.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EPrise en charge native des données multimodales\u003C/b\u003E : l’introduction d’un nouveau type de données FILE permet de référencer directement les données multimodales (y compris le texte, les images et l’audio) dans des tables Snowflake. Tous les opérateurs d’IA sont conçus pour fonctionner de manière fluide entre ces diverses modalités de données, éliminant ainsi la nécessité de systèmes de traitement séparés.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EOptimisation significative des coûts et des performances :\u003C/b\u003E grâce aux fonctionnalités natives et aux optimisations des performances intégrées dans le moteur SQL de Snowflake, Cortex AISQL réduit considérablement le temps de traitement et les dépenses de calcul. Les benchmarks internes de Cortex AISQL Performance Optimization (private preview) montrent une réduction du temps d’exécution des requêtes jusqu’à 70 % pour les opérations telles que FILTER et JOIN, avec des économies correspondantes par rapport aux implémentations manuelles, répondant directement aux préoccupations concernant l’évolutivité de l’IA et la viabilité économique pour l’adoption par les entreprises.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E« Snowflake Cortex AISQL a accéléré le développement de notre application Service Technician, qui permet à nos techniciens d’interagir et d’analyser facilement des milliers de manuels d’utilisation dans plusieurs langues afin de résoudre les problèmes des clients plus rapidement que nous ne l’aurions imaginé. La révolution pour nous a été de voir comment Cortex AISQL intègre de manière fluide divers types de données, du texte aux images et au-delà, ouvrant un chemin plus rapide entre les données et les informations qui transforme le travail de nos équipes », explique Ahmad AI-Mashahedi, Lead Data Scientist pour Toyota Material Handling Europe.\u003C/p\u003E\r\n\u003Ch1\u003ELes principales fonctionnalités de Cortex AISQL\u003C/h1\u003E\r\n\u003Cp\u003ECortex AISQL intègre les fonctionnalités d’IA directement dans les environnements SQL, permettant ainsi une analyse sophistiquée en plusieurs étapes pour divers types de données. Dans les sections suivantes, nous explorerons comment ces fonctionnalités de base optimisent les performances, réduisent les coûts et permettent des flux de travail analytiques complexes.\u003C/p\u003E\r\n\u003Ch3\u003EOpérations d’IA unifiées pour diverses données avec Cortex AISQL\u003C/h3\u003E\r\n\u003Cp\u003ELa principale force de Cortex AISQL réside dans sa capacité à permettre aux utilisateurs de construire des pipelines d’IA sophistiqués sur plusieurs modalités de données directement dans leur environnement SQL familier. Cette intégration élimine la séparation entre la data stack d’un client et la stack d’IA, offrant une plateforme unifiée pour une analyse sophistiquée sur un large éventail de données.\u003C/p\u003E\r\n\u003Cp\u003ECortex AISQL introduit les opérateurs d’IA en tant que primitives SQL natives, entièrement intégrées dans l’écosystème Snowflake. Par exemple :\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EAI_FILTER applique une logique de filtrage basée sur l’IA directement dans la clause WHERE. \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003ELes opérations JOIN peuvent désormais être basées sur des relations basées sur l’IA, et non plus seulement sur des clés prédéfinies, ce qui permet d’établir des connexions entre différents formats de données en fonction de la compréhension sémantique (par exemple, joindre un CV à une description de poste en fonction de l’évaluation de l’adéquation par une IA). \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EAI_AGG, un opérateur d’agrégation pionnier alimenté par l’IA, est conçu pour travailler avec GROUP BY afin d’extraire des informations complexes à partir de diverses lignes de données. \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EAI_CLASSIFY amélioré peut prendre en charge la classification multi-étiquettes à la fois pour le texte et les images.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-013a1db99b","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--b5888b22-4a2c-4508-b18d-b5a2fe33508a/screenshot-2025-05-30-at-8.32.29%25E2%2580%25AFam.png?preferwebp=true&quality=85","alt":"Figure 1: AI capability meets SQL primitives.","lazyEnabled":true,"height":"990","width":"2052","title":"Figure 1: AI capability meets SQL primitives.",":type":"snowflake-site/components/image"},"blog_text_1663165861":{"id":"blog-text-6b8a9d3564","text":"\u003Cp\u003ECortex AISQL élargit considérablement la surface des données adressables, avec tous les nouveaux opérateurs conçus pour travailler efficacement sur les données texte, image et, bientôt, audio, via des opérateurs unifiés. Puisqu’il n’y a pas besoin de services supplémentaires, cela transforme les data analysts en super-héros de l’IA capables de travailler avec tous types de données.\u003C/p\u003E\n\u003Ch3\u003ELibérer des informations approfondies : analyse avancée en plusieurs étapes avec des pipelines d’IA\u003C/h3\u003E\n\u003Cp\u003ELes fonctionnalités d’IA ouvrent de nouvelles perspectives d’analyse et permettent de répondre à des questions de plus en plus complexes en plusieurs étapes, allant au-delà des simples recherches. Alors que la génération augmentée de récupération (RAG) excelle dans les tâches de recherche ponctuelle, les problèmes analytiques plus profonds nécessitent d’orchestrer plusieurs étapes basées sur l’IA pour synthétiser les informations.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-746969b51a","alignment":"left","layout":"card","showQuoteIcon":false,"quote":"Considérez la profondeur analytique requise dans cette requête : « Quelles sont la croissance annuelle des revenus et les perspectives de marché pour les entreprises qui ont récemment subi un changement de CEO et opèrent dans le secteur des énergies renouvelables ? »\r\n","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_102841155":{"id":"blog-text-a8d8a1357a","text":"\u003Cp\u003EY répondre implique de :\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ci\u003EExécuter des recherches\u003C/i\u003E parmi d’importantes collections de documents pour identifier les informations pertinentes.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ci\u003EFiltrer \u003C/i\u003Eles critères clés des sections pertinentes des documents, tels que les changements de CEO et le secteur d’activité dont l’entreprise relève (énergie renouvelable).\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ci\u003EExtraire \u003C/i\u003Edes informations clés telles que le chiffre d’affaires et les déclarations de perspectives à partir de données non structurées.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ci\u003EJoindre \u003C/i\u003Edes informations non structurées à des données structurées pour le calcul de la croissance des revenus d’une année sur l’autre.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ci\u003ESynthétiser\u003C/i\u003E les résultats en un résumé clair et cohérent permettant une compréhension approfondie des tendances et des perspectives.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ECortex AISQL rend ce flux de travail analytique complexe réalisable grâce à ses opérateurs d’IA composables et à son intégration SQL native. En permettant aux analystes d’enchaîner les opérations basées sur l’IA, du filtrage de documents à l’extraction sémantique en passant par la jonction intelligente, le tout dans une syntaxe SQL familière, il élimine le besoin de plusieurs outils spécialisés et d’un code personnalisé. Cette approche unifiée transforme ce qui nécessitait traditionnellement une expertise en data science et des semaines de développement en requêtes SQL directes que les business analysts peuvent créer et modifier en quelques minutes.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1865652061":{"id":"image-728245c147","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--2788b5b5-c0e8-4e29-b576-ac0d9e7303f9/screenshot-2025-05-29-at-3.34.03%25E2%2580%25AFpm.png?preferwebp=true&quality=85","alt":"Figure 2: Building an AI pipeline using Cortex AISQL.","lazyEnabled":true,"height":"1164","width":"1976","title":"Figure 2: Building an AI pipeline using Cortex AISQL.",":type":"snowflake-site/components/image"},"blog_text_246277908":{"id":"blog-text-a2a739a8ed","text":"\u003Cp\u003EÀ l’avenir, ce type de questions analytiques complexes deviendra de plus en plus courant dans les environnements professionnels. Les entreprises devront combiner plusieurs modèles analytiques entre les données structurées et non structurées pour extraire des informations significatives de leurs données. Cortex AISQL répond à ce besoin croissant en permettant aux analystes de construire des pipelines d’IA sophistiqués, permettant ainsi aux équipes de répondre à ces questions composites avec SQL de manière native.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_1684898516":{"id":"quote-item-6fc1ddfb64","alignment":"left","layout":"card","showQuoteIcon":true,"quote":"Pendant des décennies, les outils de BI supposaient que les données étaient propres et structurées - mais les décisions réelles reposent sur du contenu désordonné et non structuré comme les PDF, les images et les reçus, explique Mike Palmer, CEO de Sigma. Cortex AISQL supprime ce goulot d'étranglement, et avec Sigma et Snowflake, transforme l'expertise humaine en analyse évolutive et intelligente. »","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1459449202":{"id":"blog-text-1f1bb0bcb4","text":"\u003Ch3\u003ERéduisez le temps et les coûts des requêtes, mais pas la précision\u003C/h3\u003E\n\u003Cp\u003ERéduire les délais et les coûts de traitement est essentiel pour l’IA d’entreprise. En exécutant les fonctions d’IA dans le moteur de requête central de Snowflake, nous combinons l’IA et le traitement des données structurées au même endroit, en utilisant le parallélisme et la mise en lots de l’entrepôt Snowflake pour optimiser les deux à la fois.\u003C/p\u003E\n\u003Cp\u003ECette évolutivité est essentielle pour les cas d’usage réels d’entreprise. Envisagez une tâche telle que « Trouver des maisons modernes et attrayantes à moins de 10 miles de San Francisco dans ma gamme de prix ». Notre système planifie intelligemment l’exécution sur plusieurs clauses WHERE, pour appliquer des filtres standard pour le prix et la distance afin de réduire d’abord le jeu de données avant d’utiliser un modèle de langage visuel pour évaluer les qualités « modernes et attrayantes », garantissant ainsi une efficacité optimale. \u003C/p\u003E\n\u003Cp\u003EL’un des principaux objectifs de Cortex AISQL est de fournir ces puissantes fonctionnalités d’IA avec des performances et une rentabilité exceptionnelles, sans compromettre la précision des informations. Nous avons mis en œuvre Adaptive LLM Optimization (private preview) de manière stratégique pour orchestrer des modèles plus petits pour des tâches plus simples, tout en réservant des LLM plus grands pour des analyses plus complexes. Cette approche graduée garantit une utilisation optimale des ressources tout en maintenant des résultats de haute qualité. \u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_188602535":{"id":"image-397f77a20d","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--795e0e88-d318-4fb5-9c20-0383aab6be05/screenshot-2025-05-29-at-3.34.38%25E2%2580%25AFpm.png?preferwebp=true&quality=85","alt":"Figure 3: Cortex AISQL offers world-class performance on AI queries.","lazyEnabled":true,"height":"1084","width":"1748","title":"Figure 3: Cortex AISQL offers world-class performance on AI queries.",":type":"snowflake-site/components/image"},"title_v2":{"id":"blog-title-7e29f134e7","propertiesId":"cortex-aisql-apporte-une-analyse-de-donnees-unifiee-aux-flux-de-travail-du-secteur","type":"heading4","lines":["Cortex AISQL apporte une analyse de données unifiée aux flux de travail du secteur"],":type":"snowflake-site/components/blog/blog-title","appliedCssClassNames":"left-alignment"},"blog_text_1964063270":{"id":"blog-text-f9ea1447e3","text":"\u003Cp\u003ECortex AISQL aide les secteurs, des services financiers au retail en passant par la santé, à obtenir de nouvelles informations et à automatiser des processus complexes à partir de leurs données structurées et non structurées.\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EServices financiers :\u003C/b\u003E les institutions du marché des capitaux peuvent désormais automatiser le traitement complexe des actions des entreprises avec une efficacité sans précédent. Grâce à AI_FILTER sur de vastes flux d’actualités et de documents réglementaires, les analystes peuvent identifier instantanément les annonces d’événements pertinentes. Ces résultats sont ensuite associés de manière transparente aux postes vacants internes grâce à la mise en correspondance intelligente des noms et des identifiants des entreprises, alimentée par l’IA, permettant ainsi d’évaluer l’impact précisément et d’éclairer les mesures à prendre, ce qui était auparavant impossible à grande échelle.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ERetail et e-commerce : \u003C/b\u003Eles équipes d’expérience client peuvent détecter les problèmes émergents de qualité des produits en temps réel en utilisant AI_AGG pour regrouper et analyser des milliers d’avis clients par SKU. Le système applique AI_FILTER pour signaler les produits présentant des tendances préoccupantes, telles que des montées soudaines d’opinions négatives ou des rapports de défauts spécifiques, ce qui permet aux équipes d’assurance qualité de réagir rapidement à des problèmes potentiels avant qu’ils n’affectent la réputation de la marque ou ne déclenchent des rappels coûteux.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESanté :\u003C/b\u003E les chercheurs en médecine accélèrent les découvertes grâce à des analyses alimentées par l’IA qui font le lien entre les notes cliniques non structurées et les dossiers des patients structurés. En appliquant AI_FILTER aux notes des médecins, les chercheurs peuvent identifier les patients présentant des schémas de symptômes spécifiques non pris en compte dans les codes de diagnostic standard. Ces informations peuvent ensuite être associées, à l’aide de JOIN, aux résultats de laboratoires et aux antécédents médicamenteux afin de découvrir des corrélations subtiles qui pourraient indiquer de nouvelles voies de traitement ou des facteurs de risque jusque-là inconnus.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003ECes cas d’usage démontrent comment Cortex AISQL transforme des processus lents et manuels en flux de travail intelligents très efficaces. \u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_776461705":{"id":"quote-item-94c09f59fd","alignment":"left","layout":"card","showQuoteIcon":true,"quote":"Apporter des LLM directement aux requêtes SQL a changé la donne pour l'analyse. Ce qui nécessitait des modèles de NLP ou de vision compliqués peut désormais être géré avec une seule ligne de SQL. Nous sommes ravis de voir comment nos clients conjoints peuvent poser des questions plus profondes et débloquer des informations auparavant hors de portée. » \r\nArmin Efendic, Lead Partner Engineer chez Hex.","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1166111163":{"id":"blog-text-4e23d4df89","text":"\u003Ch3\u003EDisponibilité de Cortex AISQL\u003C/h3\u003E\r\n\u003Ctable\u003E\r\n\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EOpérateur\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003ETexte\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EMultimodal\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_COMPLETE\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_FILTER\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_CLASSIFY\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_EMBED\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EBientôt en public preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EBientôt en public preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_SIMILARITY\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EOptimisation adaptative AI_FILTER\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPrivate preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003E-\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_AGG\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003E-\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_SUMMARIZE_AGG\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EPublic preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003E-\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EAI_TRANSCRIBE\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003E-\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd\u003E\u003Cp\u003EBientôt en public preview\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\r\n\u003Ch3\u003ETransformez l’analyse de données dès aujourd’hui\u003C/h3\u003E\r\n\u003Cp\u003ECortex AISQL redéfinit la façon dont les entreprises passent de leurs données aux informations. Grâce à sa connexion facile à toutes les sources de données d’un client via différentes modalités \u003Ca href=\"https://www.snowflake.com/fr/blog/openflow-revolutionizes-data-movement-ai/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Evia Openflow\u003C/a\u003E, Snowflake facilite plus que jamais l’utilisation d’opérateurs SQL alimentés par l’IA pour analyser ensemble les données structurées et non structurées. Cortex AISQL assure un traitement hautes performances à un coût inférieur à celui des pipelines d’IA orchestrés manuellement, ce qui permet d’obtenir des informations fiables dans toute l’entreprise tout en maintenant les capacités de sécurité et de gouvernance qui font la réputation de Snowflake.\u003C/p\u003E\r\n\u003Cp\u003ELa public preview de Cortex AISQL est désormais ouverte à tous les clients Snowflake. Lancez-vous dès aujourd’hui et découvrez comment ces puissantes capacités peuvent transformer l’analyse de données. \u003C/p\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003ELancez-vous avec Cortex AISQL grâce aux ressources suivantes : \u003C/b\u003E\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EEssayez \u003Ca href=\"https://quickstarts.snowflake.com/guide/getting-started-with-cortex-aisql/index.html#0\"\u003ECortex AISQL\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003ERegardez la démo : \u003Ca href=\"https://www.youtube.com/watch?v=1lrQ8r6XxUM\"\u003ESee Cortex AISQL in action\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EDocumentation :\u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql\"\u003E Get started with Cortex AISQL\u003C/a\u003E today\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_text_1671605061":{"id":"blog-text-025fce5928","text":"\u003Cp\u003E\u003Ci\u003EDéclarations prévisionnelles\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Ci\u003ECet article contient des déclarations prévisionnelles, notamment de futures offres de produits. Il ne constitue en aucun cas un engagement à fournir des offres de produits. Les offres et résultats réels peuvent varier et faire l’objet de risques connus et inconnus, ainsi que d’incertitudes. Découvrez notre dernier 10‑Q pour en savoir plus.\u003C/i\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_text_1663165861","quote_item","blog_text_102841155","image_1865652061","blog_text_246277908","quote_item_1684898516","blog_text_1459449202","image_188602535","title_v2","blog_text_1964063270","quote_item_776461705","blog_text_1166111163","blog_text_1671605061"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{},"columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"author_chip":"aem-GridColumn 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