AI and Robotic

Robots are unlikely to enter history first as helpers, caregivers, or household assistants. They will enter as weapons.
Throughout history, transformative technologies—from metallurgy to aviation to computing—reached scale through warfare before reshaping civilian life. Robotics follows the same trajectory. Civil society resists failure, liability, and disruption; warfare rewards speed, scale, and expendability.

The China–Taiwan conflict sits at the intersection of this technological shift. China’s industrial capacity, growing autonomy in AI and navigation, cooperation with Russia’s battlefield experience, and a stabilizing BRICS environment together reduce the traditional costs of escalation. In this setting, robotic warfare is not an exotic option but the most rational first use case.

If large-scale autonomous systems are deployed anywhere as a primary instrument of force, Taiwan is one of the most likely places where this new era of warfare will begin.

Current robotic AI systems excel in perception and manipulation, yet they remain fundamentally non-autonomous. The missing element is not computational power or data, but an internal regulatory mechanism equivalent to biological Predictive Feedback (PF). PF is a continuous, inherited comparator that evaluates predicted versus actual internal activations, driving self-learning, self-correction, and intrinsic motivation. This essay argues that without PF, robotic systems cannot develop genuine cognitive autonomy. It proposes a biologically grounded four-layer architecture—Pattern Repository, Entity Generator, Associative Pointer Matrix, and Predictive Feedback Loop—that transforms robots from externally instructed executors into self-organizing predictive agents capable of internal reasoning, adaptive exploration, and robust behavior in novel environments.

China–Taiwan and the First Age of Robotic Warfare

Predictive Feedback as the Missing Regulatory Core of Autonomous Robotic Intelligence