Training and running advanced AI systems requires significant computational resources, raising concerns about energy consumption. This article examines the environmental footprint of AI.

From the carbon emissions associated with large-scale model training to the electronic waste generated by specialized hardware, AI development has ecological consequences.

We'll look at efforts to measure and reduce these impacts through more efficient algorithms and sustainable practices.