Explore how Kubernetes and MLOps practices can enhance scalability, reliability, and reproducibility in generative AI workflows in this 49-minute conference talk from NDC London 2024. Discover the power of Kubernetes in orchestrating distributed generative AI training and inference pipelines, while learning how MLOps practices ensure efficient model development, deployment, and monitoring. Gain insights into unlocking the full potential of generative AI while achieving seamless scalability and operational excellence for organizations. Delve into the combination of these technologies to empower AI-driven solutions and improve overall workflow efficiency.
Kubernetes and MLOps for Scalable and Reproducible Generative AI
Overview
Syllabus
Kubernetes and MLOps for Scalable and Reproducible Generative AI - Annie Talvasto - NDC London 2024
Taught by
NDC Conferences
Related Courses
-
Machine Learning Operations (MLOps) for Generative AI
-
KubeDDR - Predictive Scoring with MLOps on Kubernetes
-
Achieving Real-Time Generative AI During Gameplay for Games on Kubernetes
-
Scaling Kubernetes Clusters for Generative Models - Managing GPU Resources for AI Applications
-
MLOps at the Crossroads - Challenges and Future Directions
-
From Notebook to Kubernetes: Scaling GenAI Pipelines with ZenML
