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Malware\",\"level\":2}},{\"id\":\"N7XJS-TqDS\",\"type\":\"paragraph\",\"data\":{\"text\":\"Learn how to uncover potential malware and security risks on your cloud Linux server using essential scanning tools.\"}},{\"id\":\"1eKdJrx1V4\",\"type\":\"header\",\"data\":{\"text\":\"Why Malware Detection is Crucial for Your Cloud Server\",\"level\":3}},{\"id\":\"-F7t6S9j7U\",\"type\":\"paragraph\",\"data\":{\"text\":\"Some unexpected behavior on a cloud Linux server could be a result of a malware infection, while other malicious software might not alert to its presence. 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Scanning your system for different types of unwanted programs can help identify potential issues, or at least give you peace of mind knowing that your server is clean.",{"id":249,"data":250,"type":238},"s3CIUJkMfd",{"text":251},"There are multiple options for ensuring your cloud server is free from malware. 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Ce guide explique le RAG, les LLM, l'état, la mémoire et les outils à l'aide d'un modèle mental simple.","\u002Fuploads\u002F2026\u002F09\u002Fwhat-is-rag-the-simplest-explanation-of-how-it-works-1790377492124-khjagt.webp","2026-09-25T19:03:00.000Z",{"id":435,"slug":436,"title":437,"excerpt":438,"featuredImage":439,"publishedAt":440},"492","mcp-explained-what-it-connects-what-it-does-not-do-and-where-it-fits","MCP expliqué : ce qu'il connecte, ce qu'il ne fait pas et où il s'intègre","Le protocole de contexte de modèle connecte les applications d’IA à des outils, des ressources et des invites externes par le biais d’une frontière standard client-serveur. Découvrez ce que fait le MCP, ce qu’il ne fait pas et où il s’intègre dans l’architecture des agents.","\u002Fuploads\u002F2026\u002F10\u002Fmcp-explained-what-it-connects-what-it-does-not-do-and-where-it-fits-1791486640275-7ub1cq.webp","2026-10-08T15:09:00.000Z",{"id":442,"slug":443,"title":444,"excerpt":445,"featuredImage":446,"publishedAt":447},"495","sovereign-ai-control-of-models-data-infrastructure-and-dependencies","IA souveraine : contrôle des modèles, des données, des infrastructures et des dépendances","L'IA souveraine concerne le contrôle effectif sur les modèles, les données, l'infrastructure, les logiciels, les opérations et les dépendances stratégiques — et non simplement l'endroit où un modèle d'IA est hébergé.","\u002Fuploads\u002F2026\u002F10\u002Fsovereign-ai-control-of-models-data-infrastructure-and-dependencies-1791488833132-niy85x.webp","2026-10-08T15:45:00.000Z",{"id":449,"slug":450,"title":451,"excerpt":452,"featuredImage":453,"publishedAt":454},"475","managed-agent-harness-vs-self-hosted-agent-loop-what-you-gain-what-you-lose","Harnais d'agent géré vs boucle d'agent auto-hébergée : ce que vous gagnez, ce que vous perdez","“Agent auto-hébergé” peut désigner des architectures très différentes. Ce guide distingue le harnais géré, l'environnement d'exécution auto-hébergé et la boucle d'agent entièrement auto-opérée—et montre de quelle frontière de contrôle les équipes ont réellement besoin.","\u002Fuploads\u002F2026\u002F09\u002Fmanaged-agent-harness-vs-self-hosted-agent-loop-what-you-gain-what-you-lose-1790352403475-kj10jh.webp","2026-09-25T12:05:00.000Z",{"id":456,"slug":457,"title":458,"excerpt":459,"featuredImage":460,"publishedAt":461},"473","openai-agents-api-vs-agents-sdk-vs-responses-api-what-should-you-build-on-in-2026","OpenAI Agents API vs Agents SDK vs Responses API : sur quoi devriez-vous construire en 2026 ?","La stack d'agents d'OpenAI a changé en septembre 2026. Ce guide d'architecture sépare l'API Agents, le SDK Agents, l'API Responses et le SDK Codex selon la propriété du runtime — afin que les équipes puissent choisir la bonne limite de contrôle au lieu de comparer des noms de produits.","\u002Fuploads\u002F2026\u002F09\u002Fopenai-agents-api-vs-agents-sdk-vs-responses-api-what-should-you-build-on-in-2026-1790351846714-zi7lus.webp","2026-09-25T11:56:00.000Z",{"id":463,"slug":464,"title":465,"excerpt":466,"featuredImage":467,"publishedAt":468},"494","air-gapped-ai-how-ai-systems-work-without-internet-or-cloud-access","IA en environnement isolé : comment les systèmes d’IA fonctionnent sans accès à Internet ni au cloud","L'IA en environnement isolé exécute des modèles, du RAG et des applications d'IA à l'intérieur d'un domaine de sécurité isolé, sans dépendance à Internet ni au cloud. Découvrez comment les modèles, les données, les mises à jour et les outils fonctionnent hors ligne.","\u002Fuploads\u002F2026\u002F10\u002Fair-gapped-ai-how-ai-systems-work-without-internet-or-cloud-access-1791487983978-e6xqf0.webp","2026-10-08T11:32:00.000Z",{"id":470,"slug":471,"title":472,"excerpt":473,"featuredImage":474,"publishedAt":475},"466","the-gpu-is-not-the-product-future-proof-private-ai-architecture","Le GPU n'est pas le produit : architecture d'IA privée pérenne","Une infrastructure d'IA privée ne devrait pas être conçue autour d'un seul GPU ou d'un seul modèle. Une approche plus résiliente combine des GPU d'inférence rapides, des systèmes d'IA riches en mémoire, des nœuds d'IA physique et des modèles cloud de pointe optionnels derrière une couche de routage prenant en compte les capacités.","\u002Fuploads\u002F2026\u002F09\u002Fthe-gpu-is-not-the-product-future-proof-private-ai-architecture-1790140878812-8hsl39.webp","2026-09-23T01:19:00.000Z",{"id":477,"slug":478,"title":479,"excerpt":480,"featuredImage":481,"publishedAt":482},"479","where-does-an-llm-get-its-data-rag-data-sources-in-python","D'où un LLM tire-t-il ses données ? Sources de données RAG en Python","Un LLM ne connaît pas magiquement vos fichiers, bases de données ou API. Cette suite pratique de la série sur le RAG montre, avec du Python simple, comment des données externes deviennent des preuves récupérables : des fichiers texte et du SQL à la recherche en texte intégral, aux embeddings, à l'assemblage du contexte et à l'appel final au LLM.","\u002Fuploads\u002F2026\u002F09\u002Fwhere-does-an-llm-get-its-data-rag-data-sources-in-python-1790517200521-nfsi5i.webp","2026-09-27T05:51:00.000Z",{"id":484,"slug":485,"title":486,"excerpt":487,"featuredImage":488,"publishedAt":489},"498","can-evidence-survive-the-ai-pipeline-the-evidence-preservation-chain","Les preuves peuvent-elles survivre au pipeline d’IA ? — La chaîne de préservation des preuves","Une preuve peut être correcte à la source et devenir néanmoins peu fiable après l'analyse syntaxique, la normalisation, le découpage, la récupération et l'assemblage du contexte. La chaîne de préservation des preuves vérifie si l'identité, la provenance, la portée et le sens survivent à l'ensemble du pipeline d'IA.","\u002Fuploads\u002F2026\u002F10\u002Fcan-evidence-survive-the-ai-pipeline-the-evidence-preservation-chain-1792096396174-urdg9z.webp","2026-10-15T16:31:00.000Z",{"id":491,"slug":492,"title":493,"excerpt":494,"featuredImage":495,"publishedAt":496},"386","enterprise-start-here-your-gateway-to-operational-excellence","Enterprise Start Here: Your Gateway to Operational Excellence","New to our enterprise platform? This guide provides a structured onboarding path, from foundational reference models to actionable playbooks, runbooks, and assessments designed for seamless implementation.","\u002Fuploads\u002F2026\u002F02\u002Ffrom-global-business-to-the-kitchen-a-reverse-communication-system-that-still-scales-1771251820950-zhp2bz.webp","2026-03-01T11:55:00.000Z","fallback",[],[]]