tldr - powered by Generative AI

• Using machine learning can improve results in studying subatomic particles, as demonstrated by the jet energy regression example
• Kubeflow can help run machine learning workloads
• Challenges in implementing the demo included finding the correct version of the Triton server image and customizing TensorBoard
• Possible improvements include profile replication across multiple clusters, making pipelines namespace, and adding limit range resources to profiles