The Tech Blog Writer Podcast - Inspired Tech Startup Stories & Interviews With Tech Leaders, Entrepreneurs And Innovators

AI is everywhere, yet scaling it remains a serious challenge for many enterprises. Organizations are eager to move beyond pilot projects, but they quickly run into obstacles—cloud costs spiral out of control, GPUs sit idle due to inefficiencies, and infrastructure bottlenecks slow down innovation. If AI is supposed to be the future, why is the underlying infrastructure still holding it back? In this episode, I’m joined by John Blumenthal, Chief Product Officer at Volumez, and Diane Gonzalez, Senior Director of Business Development and Product, to unpack the hidden inefficiencies of AI infrastructure and explore whether Data Infrastructure as a Service (DIaaS) is the answer. They explain why traditional AI infrastructure models are failing and why manual optimization simply can’t keep up with modern AI workloads. John argues that the problem is beyond human management, stating, “No human being is going to be able to answer that question—to actually arrive at that optimization. So you have to turn it over to a