Beyond efficiency: Scaling AI sustainably.

Wu, C.-J., Acun, B., Raghavendra, R., & Hazelwood, K. (2024, June 22). Beyond efficiency: Scaling AI sustainably. arXiv. https://doi.org/10.48550/arXiv.2406.05303

To scale artificial intelligence sustainably, we must look beyond mere energy efficiency and address the total lifecycle carbon footprint of computing infrastructure. While hardware optimizations have significantly improved performance-per-watt, the explosion of generative AI has led to a massive increase in embodied carbon—the emissions generated during the manufacturing of chips and data centers. The researchers argue that truly "Green AI" requires a holistic strategy that includes hardware-software co-design, the use of renewable energy, and a circular economy focused on extending the life of equipment. Ultimately, the industry must transition to a design philosophy where carbon telemetry and metrics are treated as primary constraints alongside traditional goals like speed and cost.