11 Modular Cognition

Kedge Modular Cognition Layers represent core architectural innovation: specialized reasoning engines composed into unified intelligence rather than monolithic transformer.

Seven cognition layers operate concurrently with independent parameter spaces totaling 287M parameters. Inter-layer communication via Vector Bus protocol maintaining causal consistency.

Layer 1 Pattern Decoder: Token-level semantic extraction, 92ms specialization. Layer 2 Context Weaver: Memory synthesis across 24K window. Layer 3 Intent Resolver: Query decomposition and agent routing.

Layer 4 Reasoning Core: Multi-step logic synthesis. Layer 5 Knowledge Integrator: External context fusion. Layer 6 Safety Arbiter: Cross-layer validation and veto. Layer 7 Response Composer: Natural language synthesis.

Dynamic layer activation: Query vectors determine active layer subset optimizing compute for specific reasoning modes. Average activation 4.2 layers per inference.

Composition achieves emergent capabilities exceeding individual layer performance by 214%. Agent personalities emerge from layer weighting rather than separate models.

Modularity enables continuous evolution: individual layers upgraded independently without retraining entire system.

7 Cognition Layers
Pattern → Context → Intent → Reasoning → Knowledge → Safety → Response
Dynamic activation: avg 4.2 layers
214% emergent gain
7 layers | 287M parameters
Vector Bus protocol