Revolutionizing AI and Computing the Neuromorphic Engineering Paradigm in Neuromorphic Chips

© 2024 by IJCTT Journal
Volume-72 Issue-1
Year of Publication : 2024
Authors : Narayan Hampiholi
DOI :  10.14445/22312803/IJCTT-V72I1P115

How to Cite?

Narayan Hampiholi, "Revolutionizing AI and Computing the Neuromorphic Engineering Paradigm in Neuromorphic Chips," International Journal of Computer Trends and Technology, vol. 72, no. 1, pp. 92-98, 2024. Crossref,

This research explores the cutting-edge field of neuromorphic engineering, providing a thorough analysis of its principles, hardware design, and practical uses. It highlights that event-driven mechanisms, parallel processing, and synaptic plasticity are essential for neuromorphic chip design. This article examines the revolutionary influence of neuromorphic devices across multiple disciplines, such as speech recognition, robotics, and computer vision. Technical and ethical challenges are explained, emphasizing standardization, scalability, and societal ramifications. Besides, this research considers how neuromorphic chips can transform computers and artificial intelligence. It emphasizes the necessity of continual multidisciplinary research and innovation to overcome obstacles and realize this paradigm shift's full potential.
This research aims to define neuromorphic engineering and explain its goal to emulate the neural structure of the human brain to improve computational speed and efficiency. Provide insight into how the human brain processes information through a vast network of neurons and synapses and how this biological model inspires the architecture of neuromorphic chips. Explain how neuromorphic chips can potentially address the limitations of current AI technologies by enabling more efficient processing of complex algorithms and enhancing machine learning capabilities

ML, AI, Robotics, Neuromorphic, Engineering, Computing, Devices, Sensor Networks, Chips, ENIAC.


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