Neuromorphic Computing: Brain-Inspired Architectures for Efficient AI

This paper surveys neuromorphic computing architectures — hardware and software systems modelled on biological neural organisation. We examine spiking neural networks, event-driven computation, temporal coding, and energy efficiency advantages over conventional von Neumann architectures. Implications for deploying sovereign AI systems on edge hardware with constrained power budgets are analysed.