Explore the latest updates from the AutoML and Training Working Groups in this informative 36-minute panel discussion featuring experts from Apple, CyberAgent, Nutanix, and an Open Source Evangelist. Gain insights into Katib's 2024 roadmap, including V1 APIs graduation, advanced parameter distribution support, and large language model parameter tuning. Discover the Training Operator's plans for LLM API support via Python SDK, advanced suspend semantics, and indexed job support. Learn about Kubernetes-native projects like Katib for hyperparameter tuning and neural architecture search, as well as the Training Operator for scalable distributed training across various ML frameworks. Understand how these tools are shaping the future of cloud native machine learning and high-performance computing on Kubernetes.
AutoML and Training Working Group Updates - Kubeflow Developments
CNCF [Cloud Native Computing Foundation] via YouTube
Overview
Syllabus
Panel: AutoML and Training Working Group Updates
Taught by
CNCF [Cloud Native Computing Foundation]
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