Скачать или смотреть The hidden cost of thinking in artificial intelligence

Today, artificial intelligence treats information as if it were free. Infinite. Frictionless. And that may be its greatest mistake. Not a moral mistake. A physical one.

In current systems, AI is optimized to produce answers. Faster. Longer. More often. But almost never to measure what that production actually costs. Computation is treated as abstract. Tokens as virtual. Information as immaterial. Yet in the real world, none of this is free.

Every piece of information has a cost. An energy cost. A time cost. A structural cost. When that cost is not measured, it cannot be regulated. When it is not regulated, it drifts. And when it drifts, the system compensates by producing more. More computation. More verbosity. More complexity.

What we sometimes call hallucinations, vague or unstable answers, are often the visible symptoms of an invisible cost. The problem is not that AI thinks poorly. Nor even that it thinks too much. The problem is that it does not know what thinking costs.

A system that cannot perceive its own internal expenditure cannot optimize itself, cannot constrain itself, and cannot evolve in a healthy way. As long as information is treated as free, intelligence will remain fragile. The next step for AI will not be more powerful. It will be more aware of its costs. And that changes everything.