DeepMind wants to use artificial intelligence to help scientists experiment with nuclear fusion, which it believes is a contender for “a source of clean, limitless energy” here on Earth.
The company says it collaborated with the Swiss Plasma Center at the EPFL technical university in Switzerland “to develop the first deep reinforcement learning (RL) system” devoted to the tools researchers are using to assess the nuclear fusion’s viability as an energy source.
That reinforcement learning system was designed to “autonomously discover how to control” a tokamak, which DeepMind says is “a doughnut-shaped vacuum surrounded by magnetic coils” that is “used to contain a plasma of hydrogen that is hotter than the core of the Sun.”
It turns out that experimenting with something hotter than the Sun can be difficult. EPFL says that if a tokamak’s settings aren’t carefully managed the plasma within “could collide with the vessel walls and deteriorate.” So researchers have to run their experiments in simulators first.
But those simulators can be hard to use, too, not least because of time constraints. DeepMind says that “plasma simulators are slow and require many hours of computer time to simulate one second of real time.” That’s hardly ideal for scientists racing to investigate nuclear fusion.
It’s also where AI comes in. DeepMind and the Swiss Plasma Center published a study in Nature describing a system that’s said to have allowed them to create “controllers that can both keep the plasma steady and be used to accurately sculpt it into different shapes” for further research.
“Similar to progress we’ve seen when applying AI to other scientific domains,” DeepMind says, “our successful demonstration of tokamak control shows the power of AI to accelerate and assist fusion science, and we expect increasing sophistication in the use of AI going forward.”
