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As AI continues to reshape industries, the challenge lies in efficiently deploying and scaling these solutions. MLOps, the fusion of Machine Learning and operational practices, offers a strategic guide for AI-driven enterprises. Drawing from over a decade of experience, we’ll share industry insights on applying MLOps, contrasting the theory with its practical application. In this talk, we’ll discuss the challenges we’ve faced, the lessons learned, and the issues we are yet to resolve. We’ll also highlight MLOps’ role in translating AI’s potential into business results and discuss the critical human element, touching on both technical and organizational changes required for successful implementation. Diego Kiedanski Bio: Diego Kiedanski is a highly accomplished AI Solution Architect at Tryolabs, where he leverages his extensive expertise in computer engineering and artificial intelligence to create innovative solutions for clients. With a strong academic background that includes a degree in Computer Engineering from Uruguay, a Ph.D. in game theory from IP Paris, and postdoctoral research in distributed machine learning systems at Yale University, Diego, is well-equipped to tackle complex challenges. As a dedicated educator, he also shares his knowledge as a professor, teaching courses on AI and its applications in the business world. Diego's unique blend of technical acumen and passion for education makes him an invaluable asset to both his clients and students. Find out more about Tryolabs here: https://tryolabs.com/ TryoLabs Blog post - The Strategic Compass for AI-driven Enterprises: https://tryolabs.com/blog/mlops-the-s... Tryolabs recently did a collab with Google on a library for temporal data. Find info on this at the Temporian Webinar: • Introducing Temporian | Webinar 📌 START LEARNING DVC • 📘 Docs: https://dvc.org/doc • 🎓 Free Online Course: https://learn.dvc.org • 💻 VS Code Extension: https://marketplace.visualstudio.com/... • 📺 Subscribe to our channel: / @dvcorg8370 💬 LET'S CONNECT • GitHub: https://github.com/iterative/dvc • Discord Community: https://dvc.org/chat • Twitter/X: / dvcorg • LinkedIn: / iterative-ai 👇 COMMENT: What part of DVC would you like us to cover next? #DataVersionControl #MLOps #MachineLearning #ReproducibleML #DVC