The Environmental Impact of AI and Large Language Models: Sustainability Challenges

Abstract

The rapid development and deployment of artificial intelligence (AI), particularly large language models (LLMs), have introduced significant sustainability challenges. These models require vast computational resources, leading to substantial energy consumption and a corresponding increase in carbon emissions. The environmental impact is further exacerbated by the extensive data storage and processing needs associated with training and deploying these models. As AI continues to grow in influence across various sectors, the energy demands of maintaining and scaling LLMs could contribute to a significant carbon footprint. Addressing these challenges involves exploring energy-efficient algorithms, optimizing hardware usage, and adopting sustainable practices throughout the AI lifecycle. The intersection of AI advancement and environmental sustainability necessitates a careful balancing act to mitigate the ecological impact while continuing to innovate in this transformative field.