👉 Butterfly computing is a computational paradigm inspired by the structure and function of the human brain, specifically modeled after the neural architecture of the neocortex. It involves a network of artificial neurons, often referred to as "neurons in a butterfly," connected by weighted edges that mimic synapses. Unlike traditional von Neumann architectures, which separate memory and processing units, butterfly computing integrates these functions within the neural network itself. Each "butterfly" neuron processes input data and applies a weighted sum followed by an activation function, similar to biological neurons. The network's output is determined by the collective activity of all these neurons, enabling parallel processing and distributed computation. This approach offers potential advantages in energy efficiency, fault tolerance, and the ability to perform complex tasks like pattern recognition and machine learning directly within the neural network, without the need for extensive data transfer between separate memory and processing units.
