Neural Networks, Artificial Intelligence and the Computational Brain

TL;DR

This paper reviews the structure and function of biological and artificial neural networks, emphasizing their applications in AI and the importance of brain-inspired models for advancing intelligent systems.

Contribution

It explores the parallels between biological and artificial neural networks and discusses their applications and significance in artificial intelligence development.

Findings

Neural networks are used in pattern recognition and medical diagnostics.

Artificial neural networks model biological neurons for AI applications.

Brain-inspired architectures are crucial for advancing intelligent systems.

Abstract

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.