The AI industry has converged on a deceptively simple metric: cost per token. It’s easy to understand, easy to compare, and easy to market. Every new system promises to drive it lower. Charts show steady declines, sometimes dramatic ones, reinforcing the impression that AI inference is rapidly becoming cheaper and more efficient. But simplicity, in … Read more
The saying “round pegs do not fit square holes” persists because it captures a deep engineering reality: inefficiency most often arises not from flawed components, but from misalignment between a system’s assumptions and the problem it is asked to solve. A square hole is not poorly made; it’s simply optimized for square pegs. Modern large … Read more
From 2005 to 2017—the pre-AI era—the electricity flowing into U.S. data centers remained remarkably stable. This was true despite the explosive demand for cloud-based services. Social networks such as Facebook, Netflix, real-time collaboration tools, online commerce, and the mobile-app ecosystem all grew at unprecedented rates. Yet continual improvements in server efficiency kept total energy consumption … Read more