NVIDIA & General Atomics team up for an AI-driven digital twin of a fusion reactor

NVIDIA and General Atomics, with help from major super-computing centres, have built a high-fidelity digital twin of a fusion reactor, designed to simulate in seconds what used to take weeks. The digital twin uses three large AI surrogate models trained on decades of fusion data and runs on powerful GPU infrastructure (including NVIDIA’s omni-verse, CUDA libraries and leading supercomputers). This isn’t just for show: the system synchronises with the real-world reactor (the DIII‑D National Fusion Facility) so teams of 700+ scientists can run “what-if” experiments virtually, refine designs, improve stability of plasma, and speed up progress toward fusion energy.

Why it matters:

• This is AI in service of very real physical systems (not just chatbots or recommendation engines). It shows how AI + surrogates + digital twins are opening new frontiers in science and engineering.

• With increased simulation speed and power comes increased responsibility: data transparency, model reliability, safety, bias in simulation outcomes, and how these tools are governed become very real issues.

• For organisations in AI-for-good, energy, climate or infrastructure sectors, this move points to a template: combining physics models + AI + digital twins to tackle tough real-world problems.

The fusion of AI and fusion energy (yes, the pun was inevitable) means we’re one step closer to realistically simulating “bottle a star” scenarios. But the flip side: as these complex systems scale, so does the need for strong governance, meaningful auditability and responsibility in how they’re used.

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