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AI Architecture › Advanced Capabilities
Advanced Capabilities

OOD Detection & Epistemic Gating

Detect when the plant is outside the training distribution and defer before acting.

STRATEGY / SLOW ▲ ▼ MICROSECOND REAL-TIMEL7Ecosystem & Strategytelemetry ▲ control ▼open ▸L6Experience & Visualizationtelemetry ▲ control ▼open ▸L5Applications & Copilotstelemetry ▲ control ▼open ▸L4Orchestrationtelemetry ▲ control ▼open ▸L3Twin Modeling & AItelemetry ▲ control ▼open ▸L2Data Fabrictelemetry ▲ control ▼open ▸L1Control Planetelemetry ▲ control ▼open ▸L0Foundationtelemetry ▲ control ▼open ▸PHYSICAL S.M.A.R.T. GENERATOR PLANTBREEDER · HYPERION1R0 1.2 m · A 2.5 · 16.84 T · δ −0.30BURNER · TANDEM MIRROR2317 T throat · 26.49 T plug · fₙ 5.44% · DEC1 center stack + plasma · 2 high-field plug · 3 expander → direct converterCOLOR GRAMMAR strategy AI-workflow infra/data models reactor/DECLINE SEMANTICStelemetry (µs)controlKRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATORMASTER BLUEPRINTSHEET 01REV. 2026-08L0-L7 · 2 MACHINES
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: A · methodology  ·  Plugs into: L3  ·  Horizon: FOAK  ·  Status: on the roadmap — not yet built

What it is

A dedicated out-of-distribution detector flags plant states unlike anything seen in training, and separates epistemic uncertainty (the model does not know) from aleatoric uncertainty (irreducible noise).

The method

Density models, deep ensembles, or Mahalanobis distance in feature space; high epistemic uncertainty routes the decision to rules or to a human instead of to an actuator.

Why it matters

The most dangerous AI failure is confident wrongness off-distribution; this makes the loop degrade toward caution exactly when it should. Plugs into L3, feeding the L4 gate.

Content reviewed August 2026 · design-and-simulation stage