The conversation highlights the evolution of machine learning infrastructure, particularly the successful integration with Kubernetes for training models. Initially, the focus was on real-time inference, but the team recognized the need for better support in model training. By developing APIs and tools for resource management, they aimed to streamline the process and enhance collaboration with the orchestration team.
