Neuromorphic Computing: Building Machines That Think Like the Human Brain A brain-inspired computing paradigm enabling energy-efficient and adaptive artificial intelligence systems

Abstract

Neuromorphic computing is an emerging paradigm that draws inspiration from the human brain to design efficient and adaptive computing systems. Unlike traditional architectures, it integrates memory and processing while using spiking neural networks to enable event-driven computation and low power consumption. This approach supports real-time learning and improves performance in resource-constrained environments. This article explores the principles, hardware implementations, and applications of neuromorphic systems, including their use in robotics, edge computing, and smart sensing. It also highlights potential benefits for Pakistan in sectors such as agriculture and healthcare. Despite challenges like hardware complexity and limited standardization, neuromorphic computing offers a promising path toward energy-efficient and intelligent AI systems.