The future of AI will require an energy breakthrough. The answer is a fusion moonshot.

The Biden administration recently announced plans to work with tech firms on power usage. Technological revolutions have always come with novel challenges: building infrastructure, navigating dual-purpose applications and preparing our workforce. For the growing industry surrounding AI, this challenge is energy. Progress in AI will soon face the limits of the power available on the grid. As the administration now recognizes, maximizing AI’s potential will require an energy breakthrough. While the nation needs diverse approaches, the best solution is the promise of fusion.

Currently, AI models are run from data centers. These models require power to build, or “train,” and to run, or “inference.” Both are energy-intensive. Combined, the vast expansion of AI means that the electricity consumption of building and running AI models may soon match the power generation of small countries — and then grow beyond that. Estimates project that a single utility in Virginia will see annual data center power demand grow by nearly 79,000 GWh by 2038 — the equivalent of adding nearly 6.1 million homes to the grid.

To meet that demand, AI firms and utilities will need to turn to new technologies. Fusion energy, the process that powers the sun and stars, holds the potential to provide a clean, safe and virtually limitless source of energy. Unlike fossil fuels, it doesn’t release greenhouse gases, and unlike nuclear fission, it doesn’t generate dangerous radioactive waste, nor does it bring a similar risk of accidents.

Skeptics contend that fusion has long promised much but failed to deliver. Historically, that has been true. But there is reason to believe this moment is different. Recent advancements in this field are promising. Lawrence Livermore National Lab has repeatedly broken power generation records, and achieved net energy, an important milestone.

Around the globe, investment in fusion is accelerating. China spends an estimated $1.5 billion per year on fusion, compared to the U.S. government’s $763 million in 2023. The U.K., Germany and Japan have all announced new investments and strategies. The private sector has invested over $6 billion in fusion start-ups.

Success in AI itself may also enable fusion science. In February, a team from Princeton announced that they had utilized a specialized AI model to significantly improve the stability of the superheated plasma in a fusion reactor — an important requirement for a successful and commercially sustainable fusion reactor.

To read the complete article, visit Utility Dive.