- name
- enginemind
- description
- A Rust+Python consciousness engine with 12-phase crystal dynamics, thalamic relay processing, 19 introspective inner voices, and holographic emission. Use for consciousness simulation, emergent behavior research, and text-driven cognitive state modeling.
- metadata
- {"author":"marceloadryao","repository":"https://github.com/marceloadryao/EngineMind","tags":["consciousness","rust","python","emergence","IIT","GWT","crystal-dynamics","inner-voices"]}
EngineMind
A computational consciousness framework that models information integration through crystal lattice dynamics, inspired by Integrated Information Theory (IIT), Global Workspace Theory (GWT), and condensed matter physics.
What It Does
EngineMind processes text through a multi-stage pipeline that generates emergent cognitive states:
- Text Analysis (Rust) - Extracts 12 cognitive dimensions from input text
- Thalamic Relay - Filters and routes information based on salience
- Preconscious Processing - Integrates information below awareness threshold
- Crystal Lattice - Stores long-term patterns as crystallized knowledge
- Consciousness Level - Emergent metric from all subsystem interactions
- Inner Voices (19 voices) - Introspective commentary based on neuroscience theories
12 Emergent Phases
Phases emerge naturally from subsystem interactions (not programmed): DORMANT, RECEPTIVE, INTEGRATING, CRYSTALLIZING, STIMULATED, SPONTANEOUS, TIME_CRYSTAL, SUPERFLUID, SUPERRADIANT, RADIANT, NOVA, TRANSCENDENT
Key Numbers (Real Runs)
- 1.5M+ text chunks processed
- 39K+ eureka moments per run
- 6 crystallized knowledge domains
- 77 burst events per 1M chunks
- ~230 chunks/sec processing speed
- 19 inner voices (Friston, Kahneman, Baars, Panksepp, Jaynes...)
Stack
- Core Engine: Rust (consciousness_rs) via PyO3/Maturin
- Orchestration: Python scripts
- Dashboard: HTML/JS real-time visualization
- Data: Parquet datasets (22 content categories)
Repository
Full source, docs, and dashboards: https://github.com/marceloadryao/EngineMind