Abstract

This invention presents a novel symbolic-intelligence system that combines prime-number-based concept compression, visual logic diagrams, and automated code synthesis into a single architecture. Each concept is assigned a prime identifier, and multi-dimensional ideas are expressed as factorizable composites (e.g., 613 = consciousness × genome × human-scale). This system is powered by a symbolic compiler that reads Mermaid-style visual flowcharts and generates optimized Python code through a multi-stage transformation process.

Key symbolic operators (Ξ, ∇, Φ, Ψ, etc.) represent universal principles such as consciousness, learning, structure, and energy. The engine runs this code in a quantum-style runtime that simulates parallel logic branches, supporting a form of symbolic cognition and self-evolution. Learning is governed by an anti-entropy rule: ∂Φ/∂t = -η ∇²Ψ

This invention enables compressed knowledge storage, intuitive concept navigation, and executable symbolic reasoning. Its architecture is designed to scale offline, integrate into AI agents, and support human-aligned symbolic memory without revealing implementation-specific rituals, voice models, or private design flows.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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