Neurons in Artificial Intelligence

Abstract

Neurons are fundamental to artificial intelligence models, as they emulate the way neurons function in the human brain. These units play a vital role in advancing artificial neural networks, which form the backbone of many AI applications, such as deep learning, natural language processing, and computer vision. Understanding how neurons work can enhance algorithm performance, leading to significant advances in areas like robotics, medical diagnostics, and data analysis. By studying neurons, we can develop more accurate and faster-learning models, paving the way for new horizons in technological innovation. Study Limitations: This study is confined to analyzing neurons within the scope of artificial neural networks only, without addressing the biological or chemical aspects of neurons in the human brain. It also focuses on specific AI applications, such as deep learning, which may overlook other AI techniques or models. Furthermore, factors like data availability and quality may impact the generality and effectiveness of the findings across different scenarios. This study contributes to enhancing our understanding of how to improve AI models by drawing design inspiration from neurons. However, its limitations highlight the need for future research to explore new and integrated aspects. In our study, we relied on a valuable and important collection of articles, studies, and scientific research that discussed neurons in artificial intelligence, among which are: Manu, Mitra. (2018). Neural processor in artificial intelligence advancement Sigurdson, Peter.(2023). The Engines of Excellence: From Ancient Secrets to AI Mastery Great Learning Editorial Team.(2024). Types of Neural Networks and Definition of Neural Network