Evidence-first AI semiconductor analysis: what new silicon claims prove, where bottlenecks move, and whether gains survive at system and economic scale.
In my Jev article, I argued that a cheap decision is only the start. An agent still has to process or reuse context, turn each choice into an action, and handle failures.
This Pokémon experiment makes that system-level work visible. Jev made 16,150 choices for about $1.65 in Jev calls, while separate software read the game state, found paths, and kept the run moving.
It is a game demo, not a hardware benchmark. But it is a useful picture of the question: what does the whole loop cost?