The relentless pursuit of artificial intelligence advancement is shifting from a focus on chip development to a critical concern over electricity availability. AI models, especially large language models, demand immense computational resources, leading to staggering electricity consumption. Training these models requires high-performance computing infrastructure, often involving thousands of GPUs running continuously for weeks or months. This creates a significant strain on power grids, with AI-focused data centres consuming as much electricity as 100,000 households.
Data centre electricity consumption is projected to more than double by 2030, with AI being the primary driver. This surge in demand is prompting tech companies to seek alternative solutions, including building their own power infrastructure. The trend raises sustainability concerns, as AI model training consumes massive amounts of fossil-fuel-based electricity, contributing to greenhouse gas emissions. Addressing these challenges requires optimising AI models for energy efficiency and exploring advancements in hardware.
As AI expands, ensuring affordable, reliable, and sustainable electricity becomes crucial. Countries that can meet the energy demands of AI development will be best positioned to benefit from this technological revolution. The industry is exploring diverse solutions, including natural gas, renewables, and nuclear power, to power AI data centres effectively.
