  In recent years, several studies have provided insight on the functioning of
the brain which consists of neurons and form networks via interconnection among
them by synapses. Neural networks are formed by interconnected systems of
neurons, and are of two types, namely, the Artificial Neural Network (ANNs) and
Biological Neural Network (interconnected nerve cells). The ANNs are
computationally influenced by human neurons and are used in modelling neural
systems. The reasoning foundations of ANNs have been useful in anomaly
detection, in areas of medicine such as instant physician, electronic noses,
pattern recognition, and modelling biological systems. Advancing research in
artificial intelligence using the architecture of the human brain seeks to
model systems by studying the brain rather than looking to technology for brain
models. This study explores the concept of ANNs as a simulator of the
biological neuron, and its area of applications. It also explores why
brain-like intelligence is needed and how it differs from computational
framework by comparing neural networks to contemporary computers and their
modern day implementation.
