Test-time training shifts model inference economics

A technique called test-time training allows AI models to update their weights (internal parameters) as they work through a prompt, rather than remaining frozen. The model takes a gradient step on each prompt, causing its weights to change during inference—analogous to a GPS learning a persistent shortcut rather than making a one-time detour.