The artificial intelligence boom is reshaping tech and the economy and significantly increasing energy consumption. For example, large language models, such as ChatGPT, require about ten times the electricity of a traditional Google query.
With emerging AI capabilities in audio and video generation, energy demand will be several times higher. This high energy consumption is making companies reexplore the idea of restarting dormant nuclear reactors, considering all of the above approaches to energy production.
Data centers have experienced continuous growth for decades, but the rise of AI is creating an unprecedented increase in their energy requirements.
AI requires more computational and data storage resources, straining the existing electrical grid, which is often already near capacity. This situation is worsened by the lag between the rapid growth of data centers, which take one to two years to build, and the slower process of adding new power to the grid, which takes several years.
Fifteen states host 80% of U.S. data centers, with Virginia alone consuming over 25% of its electricity for data centers. The push to integrate more renewable energy sources into the grid and the intermittent nature of renewables like wind and solar create headaches caused by matching supply with demand.
As AI demands continue to increase, California and the rest of the United States must rethink how to alleviate grid stress and its approach to energy production.
For more information, contact Sean Wallentine.