Generative video models can produce hundreds of frames showing a robotic hand smoothly grasping an egg or playing an instrument. But high confidence based on visual mimicry frequently hides a complete absence of physical understanding (friction, pressure, torque, material). Dexterity cannot be shortcut through 3D simulators or visual pattern matching alone. In humans, manipulation requires massive neural capacity. Tasks like playing Mozart require multi-modal learning environments with tactile feedback, vision, 3D spatial motion, and acoustic response across trillions of interactions. To avoid the simulation plausibility trap, robotic systems require grounded haptic experience, paired with stress-test benchmarks to expose the learning gaps.