Roman Chernin, CBO and co-founder of $NBIS, just published an article in Forbes titled “The Hidden Advantage of Integrated AI Infrastructure.” It’s a perfect breakdown of why $NBIS stands out from competitors. I highly recommend reading the full piece, but here’s a summary: 🧐 AI is evolving fast, and the infrastructure behind it must evolve too. Simply adding more GPUs and data centers isn’t enough. True efficiency comes from integration across hardware, software, and operations: a full-stack, AI-native approach. "It's software built to use less power and reduce costs. Storage systems that can handle the large datasets AI requires. Data centers designed around specific hardware and AI processing needs. Layers designed to work together from the start, rather than integrated at a later stage." Roman explains that companies controlling their entire stack gain long-term advantages in cost, flexibility, and speed. When data centers, storage, and software are designed together, rather than purchased from different suppliers, every component can be optimized for performance and efficiency. In AI, understanding comes from building. Those who develop across multiple layers, rather than relying solely on vendors, can spot optimization opportunities early and evolve faster. That’s why $NBIS has a deep advantage: its team brings years of experience designing and operating complex cloud systems, having built several data centers from the ground up. That expertise allows the company to optimize every layer of the stack and deliver truly AI-native infrastructure. This is ultimately a battle of economics and operational excellence. Like Formula 1 teams squeezing every drop of performance from their machines, AI infrastructure leaders win by integrating deeply and improving continuously. "It isn’t always the teams with the biggest budgets that win. It is the ones who manage to extract maximum performance from every component such as aerodynamics, power unit optimization, telemetry and data analysis. The same principle applies to vertically integrated AI infrastructure." The first to adapt new hardware, integrate it quickly, and deliver production-ready solutions gain a timing advantage, turning the latest chips into customer value faster than others. Roman’s conclusion says it best: "Those AI infrastructure players that began by renting everything are moving down the supply chain in order to control more components. They are learning what we have implemented from the start. At the end of the day, if you’re just cabling the boxes or building service on top of the infrastructure you don’t control, you’re limited in the game of scale and efficiency. Controlling the stack lets you shape it into the product form customers actually need. If you control the stack, you control the product, the performance and the economics. Control the economics, you can control your (and your customers’) competitive position." All in all, control is the ultimate moat: Control the stack → control performance → control costs → control your competitive edge.