The PARK Stack Is Becoming the Standard for Production AI
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The PARK Stack: A stack is coalescing into clear layers with active collaboration at the seams. It 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.
Enterprise AI teams have three options: extending legacy data and ML platforms, relying on APIs, or building a 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.
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