Source: The Next Web
The article identifies a concrete but overlooked cost in the AI buildout: not compute itself, but the supporting infrastructure required at scale. As training demands grow, infrastructure constraints risk becoming a bottleneck, shifting competitive advantage away from model makers toward companies solving foundational problems—data centers, cooling systems, power delivery, networking. The engineer highlighted here represents a category of founder likely to attract capital as cloud providers and AI labs confront infrastructure limits, not talent limits, in their expansion plans.