Series
The Intelligence Layer
Thirty specialized models, four architecture types, distributed across three compute zones. The intelligence layer launches on cloud inference, bootstraps proprietary models from real interaction data, and deploys them to subscriber homes and regional nodes over twenty-four months. After reading this series, you understand why the system is decomposed, how each model is built, and what keeps them accurate over time.
BMT-06.01
Why Thirty Models, Not One
Five constraints make a monolithic model unviable: edge deployment, sub-200ms safety latency, incremental updates, offline resilience, and deployability across three compute zones …
BMT-06.02
The Right Architecture for the Right Task
SSMs for streaming, MoE for classification, Transformers for generation, hybrids for mixed profiles. The portfolio uses four architecture types because measurement showed that one …
BMT-06.03
Edge Intelligence
A three-zone architecture distributes intelligence across Local Pane (Zone 1), Community Pane (Zone 2), and cloud reasoning (Zone 3). Privacy, latency, and resilience are satisfied …
BMT-06.04
The Training Philosophy
Launch on cloud inference. Use every subscriber interaction as training data. Deploy proprietary models to Zone 1 and Zone 2 over twenty-four months while Zone 3 remains the …
BMT-06.05
Model Lifecycle
Models degrade, drift, and become stale. The lifecycle system monitors three dimensions continuously, validates through A/B testing and clinical review, and deploys updates to Zone …
Synthesis