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Green Artificial Intelligence (AI) and Machine Learning (ML)
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Author(s): D. Pavunraj (Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, India), A. Mathankumar (Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, India), K. Anbumaheshwari (Sethu Institute of Technology, India)and R. Daisy Merina (Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, India)
Copyright: 2025
Pages: 16
Source title:
Energy Efficient Algorithms and Green Data Centers for Sustainable Computing
Source Author(s)/Editor(s): P.J. Beslin Pajila (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), Belfin Robinson Vimala (University of North Carolina, USA), Y. Harold Robinson (Francis Xavier Engineering College, India)and C. Gopala Krishnan (GITAM University, India)
DOI: 10.4018/979-8-3373-0766-4.ch010
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Abstract
Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of technological progress, revolutionizing fields such as healthcare, finance, and transportation. However, the energy-intensive processes involved in training and deploying complex AI models have raised significant environmental concerns. Green AI and ML represent a shift toward sustainable practices by emphasizing energy efficiency, reducing carbon footprints, and minimizing resource usage. This approach encompasses the development of optimized algorithms, efficient hardware solutions, and the use of renewable energy during computation. Green AI advocates for training smaller models with reduced computational complexity, thereby ensuring performance with lower environmental costs. Techniques such as model distillation, pruning, and quantization are increasingly being adopted to achieve this balance. Furthermore, Green AI encourages collaboration among researchers, policymakers, and industries paradigm is essential for advancing AI responsibly in an era of growing environmental challenges.
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