Choisir, construire, livrer et apprendre avec moins de friction — architecture, IA en production, delivery, qualité, leadership. Produits fiables et utiles. StrasbourgJoined September 2026
IA en production, localement et sous contrôle : RAG privé, agents métiers, données sensibles et latence maîtrisée. Le vrai sujet n’est plus seulement le modèle, mais l’architecture complète : sécurité, supervision, qualité et coût.
#DGXSpark#IA#LocalAI#RAG#MLOps
Développez vos compétences en data et en intelligence artificielle avec DataCamp. Suivez des formations interactives, pratiquez directement en ligne et progressez à votre rythme.
Commencez dès maintenant : app.datacamp.com#Data#IA#DataScience
Un modèle performant en laboratoire ne suffit pas.
Pour le CTO, MLOps signifie valeur, budget et responsabilités.
Pour le tech lead : traçabilité, évaluation, surveillance et retour arrière.
La vraie réussite : une IA utile et fiable en production.
#MLOps#CTO
Companies that realize returns from AI do so because they change the way they operate, according to MIT Sloan senior lecturer George Westerman. He developed six questions for business leaders to consider when implementing AI: bit.ly/4zcyIvd
Une équipe technique ne manque pas toujours de vélocité. Elle manque parfois d’une décision explicite.
Avant d’ajouter un outil :
- quel problème résout-il ?
- quel compromis crée-t-il ?
- comment mesurer son effet ?
La qualité du delivery commence souvent là.
Une ressource que je recommande aux Tech Leads, Engineering Managers et CTO : Software Lead Weekly.
Une sélection hebdomadaire sur le leadership, la culture, les équipes et la construction de meilleurs produits logiciels.
👉 softwareleadweekly.com
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Own your compute. Or share ours.
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For company updates, check out @GoogleCloud.
Watch #GoogleCloudNext on demand ⬇️
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