Transfer-learned disruption prediction from the world's tokamak databases.
The AI-Native S.M.A.R.T. Generator Master Blueprint — eight layers (L0→L7), one control stack, wired to both machines. Telemetry rises in microseconds; control descends the same path.
Category: B · physics · Plugs into: L3 · Horizon: FOAK · Status: on the roadmap — not yet built
What it is
Disruptions are rare on any single machine; a model transfer-learned from JET, DIII-D, EAST and Alcator databases brings decades of disruption data to the breeder from the first pulse.
The method
Pre-train on public multi-machine disruption datasets with physics-based precursor features; fine-tune on Hyperion as its own data accrues (domain adaptation).
Why it matters
It gives a mature disruption predictor before we have had our own disruptions — safety and availability from day one. Plugs into L3, feeding the anomaly ensemble.