DeepMind will apply its Torax AI to simulate and optimize plasma behavior in Commonwealth Fusion Systems’ SPARC reactor, and the partners are exploring AI‑based real‑time control. Fusion requires continuously tuning many magnetic and operational parameters faster than humans can, which AI can potentially handle. If successful, AI control could be the key to sustaining net‑energy fusion.
— AI‑enabled fusion would reshape energy, climate, and industrial policy by accelerating the arrival of scalable, clean baseload power and embedding AI in high‑stakes cyber‑physical control.
EditorDavid
2026.01.10
75% relevant
The article reports a concrete operational advance on EAST (plasma‑wall self‑organization and ECRH‑assisted start‑up) that targets the same control and long‑duration stability problems AI control systems are designed to manage; success in extending density limits increases the near‑term value of robust AI control and real‑time autonomy for reactors — directly connecting experimental fusion progress to the existing idea that AI will be central to operating next‑generation fusion devices.
BeauHD
2026.01.09
85% relevant
The EAST result rests on precise, time‑dependent control of startup conditions (gas pressure and electron‑cyclotron heating) and engineered plasma‑wall interactions to suppress impurities and stabilize high density. That same class of fine‑grained, real‑time control is what proposals for AI‑based plasma controllers (e.g., DeepMind/CFS work) aim to provide, so the article concretely supports the claim that improved control systems—including AI‑driven closed‑loop regulation—can unlock previously assumed physical limits.
BeauHD
2025.10.16
100% relevant
Google DeepMind’s partnership with CFS to use Torax for SPARC plasma optimization and possible reactor control.
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