Run:AI integrates GPU optimization tool with MLOps platforms

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Run:AI today announced it has added support for both MLflow, an open source tool for managing the lifecycle of machine learning algorithms, and Kubeflow, an open source framework for machine learning operations (MLOps) deployed on Kubernetes clusters, to its namesake tool for graphical processor unit (GPU) resource optimization. The company also revealed that it has added support for Apache Airflow, open source software that can be employed to programmatically create, schedule, and monitor workflows. The overall goal is to enable GPU optimization, as well as training AI models from within an MLOps platform, Run:AI CEO Omri Geller told VentureBeat. "It can be managed more end-to-end," he said.