How are neuromorphic computing architectures inspired by the human brain being used to design energy-efficient AI hardware?

Neuromorphic computing architectures mimic the structure and function of the human brain to perform computations in a highly parallel and energy-efficient manner. These architectures, such as spiking neural networks and memristive networks, offer advantages in tasks such as pattern recognition, sensor data processing, and edge computing applications where power efficiency is critical.