In the realm of artificial intelligence (AI), where data crunching and machine-learning algorithms reign supreme, the demand for energy has emerged as a critical concern. Mark P. Mills, the executive director of the National Center for Energy Analytics (an initiative I oversee at the Texas Public Policy Foundation), argues that the energy requirements for AI systems are far more substantial than most of us know. His insights paint a sobering picture of the energy landscape that awaits us as AI continues its relentless advance into every facet of modern life.
Mills contends that the computational intensity of AI applications, such as deep learning and real-time data processing, is driving an unprecedented surge in energy consumption. According to the International Energy Agency, the global electricity consumption by AI alone could reach 1,000 terawatt-hours (TWh) annually by 2026, slightly more than the total electricity consumption of Japan. The appetite will be formidable as it becomes integral to industries ranging from health care to finance, and transportation to agriculture.
At the heart of the debate lies a fundamental question: Can renewable energy sources adequately power the AI revolution? Silicon Valley, home to tech giants like Google, Facebook, and Tesla, has been a vocal advocate for renewable energy solutions. Many of these companies have committed to ambitious sustainability goals, including achieving carbon neutrality or even operating entirely on renewable energy. Most of these promises are hollow, at best, in that they rely on periodic renewable energy contracts to make the claim that they’re 100 percent
