👉 Hairy computing, also known as spiking neural networks (SNNs), is a computational paradigm that draws inspiration from the biological nervous system, particularly the intricate structure and function of neurons in the brain. Unlike traditional artificial neural networks that rely on continuous signals, hairy computing uses discrete spikes or pulses to transmit information, mimicking the way neurons communicate through electrical impulses. This approach offers several advantages, including energy efficiency, as spikes only occur when significant changes happen in the input, reducing unnecessary computations. Moreover, it allows for more natural and biologically plausible processing of temporal information, making it particularly suitable for tasks involving sensory data, such as speech recognition and real-time decision-making. By emulating the brain's efficiency and adaptability, hairy computing represents a promising direction in the development of more intelligent and resource-conscious AI systems.
