We need energy for AI, and AI for energy

In 1903, Mark Twain wrote that "It takes a thousand men to invent a telegraph, or a steam engine, or a phonograph, or a photograph, or a telephone or any other important thing."

- ERIC SCHMIDT

This observation still mostly holds true. The invention of artificial intelligence required decades of work by thousands of scientists, engineers, and industry leaders. It will require many more men and women to develop the technology in the years ahead.

As the march of AI accelerates, a new requirement has become apparent: the next breakthroughs will consume colossal quantities of energy. AI guzzles electricity—a single ChatGPT query requires ten times as much as a conventional web search. As AI usage increases, its energy requirements will rise, and if demand outstrips supply, the technology's development will be strangled.

We must also take another look at nuclear energy, either by restarting existing plants already connected to the grid, or by building the next generation of smaller, safer, and more efficient reactors.

AI's electricity usage is projected to increase from four terawatt-hours in 2023 to 93 TWh in 2030—more than Washington State used in 2022.

The data centers that underpin AI development at scale—powering GPT-4, Gemini, and other frontier models—need around-the-clock access to power. They already account for roughly 3% of annual US electricity consumption, and this share is expected to more than double in the next five to ten years. More broadly, AI's electricity usage is projected to increase from four terawatt-hours in 2023 to 93 TWh in 2030—more than Washington State used in 2022. And that's a conservative estimate; AI could consume this much power as early as 2025.