THE ENVIRONMENTAL IMPERATIVE OF AI COMPUTE OPTIMIZATION: BALANCING PROGRESS WITH SUSTAINABILITY

Abstract

With an emphasis on the increasing energy consumption issues in AI infrastructure, this article explores the crucial connection between the development of artificial intelligence and environmental sustainability. It examines how large-scale AI processes, from model training to inference, affect the environment and examines different optimization techniques used by the sector. In addition to exploring the importance of sophisticated cooling solutions and sustainable power sources, the article looks into important methodologies including hardware acceleration, resource allocation optimization, and model deployment strategies. It illustrates how optimization and efficiency enhancements can drastically lower the environmental impact of AI operations while preserving performance standards through a thorough examination of existing industry practices and research findings.