AI on the Edge: Why Smaller Models Win on Cost and Speed

🎧 Episode 7 — AI on the Edge: Why Smaller Models Win on Cost and SpeedFor the last few years, the AI conversation has been dominated by scale. Bigger models. Bigger budgets. Bigger infrastructure. But quietly, a different story is unfolding.In this episode of The AI Storm, we explore why smaller, faster, edge-deployed AI models are increasingly outperforming large, centralized systems—on cost, speed, reliability, and control.This isn’t a technical deep dive. It’s a leadership conversation.You’ll learn:Why many real-world AI use cases don’t need massive modelsHow edge and smaller models are being used in retail, manufacturing, security, and operationsWhat “training,” “fine-tuning,” and “retraining” actually mean in practical business termsWhether companies should buy off-the-shelf models or invest in building their ownThe new roles and skills emerging around edge AI and model operationsHow leaders should think about ROI, governance, and long-term sustainabilityThis episode is about designing intelligence for reality, not for demos.If you lead teams, build platforms, or make decisions about AI strategy, this conversation will help you rethink where intelligence should live—and why smaller may be smarter.🎙️ Hosted by Krishna Goli🌩️ Finding direction and decisiveness in the storm of AI