The G-GAM Engine & Discrete Conformal Mappings
Deep technical specifications of Ipvive's conformal autoencoder and dual-cycle relational intelligence pipeline.
Section 2.1: Conformal Autoencoder Architecture
G-GAM acts as a geometric autoencoder bridging natural language queries with non-Euclidean biology. It maps high-dimensional representations to hyperbolic representations using a global atlas of localized homeomorphisms:
where each local map φα: Uα → Hα is homeomorphic to a hyperbolic manifold of constant negative curvature Hα.
Mathematical Invariants
- Angle Preservation: Conformal scaling factor λ(x) > 0.
- Exponential Expansion: Curvature K = -1 matching cell line growth.
- Homeomorphic Continuity: Boundary preserving disk mappings.
Section 2.2: Dual-Cycle Processing & Unified Cognitive Pipeline
FAST CYCLE (INNERWORLD MAPPINGS)
Timeframe: Real-time (<10ms)
Processes internal multi-omic vectors, clinical datasets, and physiological matrices in negative curvature hyperbolic space to resolve biophysical ground truth and prevent cell-state degradation.
SLOW CYCLE (OUTERWORLD MAPPINGS)
Timeframe: Long-Baseline Strategic Reasoning
Driven by an open-source Blum Conscious Turing Machine (CTM) framework. Manages the decentralized execution mesh of partner agents (Catalyzer.us, myASHISUTO.ai, Lenzu.us, WISERR.world).