“Beyond GPUs: What True AI-Native Infrastructure Really Means” from “AI_Cloud Essentials” by pods4.me

AI-native infrastructure is no longer optional; it is the foundation every modern enterprise needs to scale AI reliably and cost effectively. In this episode, Independent AI Strategist Ritu Jyoti sits down with Jacob Feldman, Lead Solutions Architect at CoreWeave, to break down what true AI-native infrastructure really means and why GPUs alone will not get your models into production. You will learn how the right architecture can eliminate bottlenecks, reduce training time, and unlock the performance your AI teams have been missing. Together, Ritu and Jacob unpack the full AI stack: networking, storage, orchestration, security, and observability, and explain how each layer impacts speed, cost, and long term ROI. They share real-world insights from working with leading CIOs, CTOs, and Heads of AI, giving you a clear blueprint for moving from pilot experiments to scalable AI deployment. In this episode, you will learn: Why general purpose cloud slows AI teams down How InfiniBand, bare metal compute, and AI optimized storage transform performance What AI-native actually means across the full lifecycle (training to inference to continuous refinement) The operational pitfalls that stall enterprise AI and how to avoid them How to build for reliability, scale, and predictable cost in every AI workload Do not risk stalled pilots, rising GPU costs, and fragile architectures. Learn how to build AI systems that truly scale and give your teams the infrastructure advantage they need now.