Guest Editorial Special Issue on Resource Sustainable Computational and Artificial Intelligence

Abstract

In Recent years, the rapid advancements in computational and artificial intelligence (C/AI) have led to successful applications across various disciplines, driven by neural networks and powerful computing hardware. However, these achievements come with a significant challenge: the resource-intensive nature of current AI systems, particularly deep learning models, results in substantial energy consumption and carbon emissions throughout their lifecycle. This resource demand underscores the urgent need to develop resource-constrained AI and computational intelligence methods. Sustainable C/AI approaches are crucial not only to mitigate the environmental impact of AI systems but also to enhance their role as tools for promoting sustainability in industries like reliability engineering, material design, and manufacturing.