Deep Dive: The AI-Native Plant
An eight-layer control architecture — from microsecond deterministic reflexes to a predictive digital twin and human oversight — that holds the plasma within its safety envelope.
- Layers
- Eight, from μs reflexes to strategy
- Digital twin
- 50–100 ms predictive head start
- Safety clamp
- β_N ≤ 4.5 enforced deterministically
- Status
- Concept-stage software design
A fusion plasma changes faster than any human can react, so Kronos designs an AI-native control stack. It is organized as an eight-layer architecture where every decision has an altitude — the fast layers simple and deterministic, the higher layers richer and supervised.
At the bottom, deterministic hardware ingests and filters sensor signals in microseconds (a dropped channel votes to a redundant set in under 100 μs). A real-time digital twin scores the data against a 50–100 ms-ahead prediction. A rules engine then clamps every command to physical limits — β_N ≤ 4.5 is a hard not-to-exceed value — before any actuator moves. Above that, engineering copilots surface anomalies with full decision lineage, and operators retain override authority with a zero-trust audit trail.
Kronos is explicit that this is a concept-stage software design, not an operating system. Its latency budgets must be demonstrated on production hardware, and its models validated on real machine data — first at the G1 testbed.