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
America’s data centers managed to keep their electricity use surprisingly steady from 2005 to 2017, with rather small annual increments contained via constant improvement in electronics. Then, around 2017, AI arrived forcefully and disrupted that stability. AI required a different computing machine, one designed not for ordinary tasks, such as our beloved PC, but for … Read more
Walk into any modern AI lab, data center, or autonomous vehicle development environment, and you’ll hear engineers talk endlessly about FLOPS, TOPS, sparsity, quantization, and model scaling laws. Those metrics dominate headlines and product datasheets. If you spend time with the people actually building or optimizing these systems, a different truth emerges: Raw arithmetic capability … Read more