Energy-Efficient and Green AI

Abstract

The rapid growth of Artificial Intelligence (AI) has led to increasing computational demands, resulting in significant energy consumption and environmental impact. Energy-efficient and Green AI focuses on designing algorithms, hardware, and systems that minimize energy use while maintaining high performance, thereby promoting sustainable and environmentally responsible AI practices. This approach encompasses model compression, pruning, quantization, low-power hardware accelerators, and adaptive training strategies to reduce carbon footprint without compromising accuracy. Green AI also emphasizes the evaluation of AI models not only based on performance metrics but also on energy and resource efficiency, fostering transparency and accountability in AI development. By integrating energy-awareness into AI research and deployment, Green AI supports the global push toward sustainable computing, enabling large-scale adoption of AI technologies in a climate-conscious and resource-efficient manner.