Commonwealth Fusion Systems
Assembly Line
The Inside Story of Google’s Quiet Nuclear Quest
The first research effort came from a proposal by my colleague Ted Baltz, a senior Google engineer, who wanted to bring the company’s computer-science expertise to fusion experiments at TAE Technologies in Foothill Ranch, Calif. He believed machine learning could improve plasma performance for fusion.
In 2014, TAE was experimenting with a warehouse-size plasma machine called C-2U. This machine heated hydrogen gas to over a million degrees Celsius and created two rings of plasma, which were slammed together at a speed of more than 960,000 kilometers per hour. Powerful magnets compressed the combined plasma rings, with the goal of fusing the hydrogen and producing energy. The challenge for TAE, as for all other companies trying to build commercial fusion reactors, was how to heat, contain, and control the plasma long enough to achieve real energy output, without damaging its machine.
A nice side benefit from our multiyear collaboration with TAE was that people within the company—engineers and executives—became knowledgeable about fusion. And that resulted in Alphabet investing in two fusion companies in 2021, TAE and Commonwealth Fusion Systems. By then, my colleagues at Google DeepMind were also using deep reinforcement learning for plasma control within tokamak fusion reactors.