In the age of generative AI, enterprise teams have three options: extend their legacy data and ML platforms, rely on APIs, or build a custom unified platform for generative AI. For teams choosing to build their own custom AI platform, the PARK Stack (PyTorch, AI Frontier Models, Ray, Kubernetes) is quickly becoming the industry standard.
The PARK Stack consists of co-evolving layers: a container orchestrator like Kubernetes for provisioning resources; a distributed compute engine like Ray for scaling applications and handling systems challenges like fault tolerance; AI foundation models that can be tuned, customized, and deployed; and a high-level framework like PyTorch for model development or refinement.
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