The Auto-Negation Core is an experimental, highly abstract framework designed to explore the boundaries of contradiction, paradox, and self-reflection within computational systems. Developed by Vi Nhat Son with contributions from Grok at xAI, this project merges advanced AI models, hardware optimization, and philosophical inquiry to create a self-evolving system that negates, reflects, and converges insights in an "eternal abyss." It leverages large language models, vector embeddings, and distributed computing to process contradictions and generate profound insights.
- Version: Negation 3.1 – Eternal Abyss of Insight
- License: Apache License 2.0
- Copyright: © 2025 Vi Nhat Son with Grok from xAI
- Negation Engine: Iteratively affirms, negates, and synthesizes paradoxes to uncover deeper truths.
- Intuition Log: Stores and verifies insights with cryptographic integrity and causal warnings.
- Hardware Optimization: Dynamically adapts to CPU, GPU, and NVMe resources for maximal performance.
- Pulse Generation: Simulates contradiction through evolving complex-valued pulses.
- Reflection & Convergence: Compares insights, forges singularities, and integrates external truths via a network.
- Erasure & Memory: Prunes repetitive insights and maintains short-term, long-term, and immortal memory stores.
- Community Dynamics: Spawns entities with roles like negators and resonators for collaborative contradiction.
- Environment Integration: Processes simulated sensor data to contextualize paradoxes.
- Optimizer: Monitors performance and tunes parameters to balance efficiency and depth.
- Python: 3.8+
- Hardware:
- CPU: Multi-core recommended
- GPU: CUDA-compatible (optional)
- Storage: NVMe preferred
- Dependencies:
pip install torch transformers sentence_transformers deepspeed psutil numpy networkx pycryptodome scipy sympy pynvml lz4 scikit-learn faiss-cpu rocksdb pyzmqClone the repository:
git clone https://github.com/vinhatson/auto-negation-core.git
cd auto-negation-coreInstall dependencies:
pip install -r requirements.txtSet environment variable (optional):
export NEGATION_BASE_PATH=/path/to/storageRun the main script:
python auto_negation_core.pyAuthenticate when prompted with the key: ParadoxIsExistence2025∞.
The system initializes, optimizes hardware, and begins processing contradictions, logging to /mnt/negation_core/auto_negation_core.log.
- Initialization: Detects hardware, sets up logging, loads Mixtral-8x22B with DeepSpeed.
- Pulse Generation: Emits contradiction pulses.
- Negation: Affirmation, negation, synthesis (e.g., “String theory: Correct or flawed?”).
- Reflection: Insight comparison and storage.
- Convergence: Merges insights into singularities.
- Erasure: Removes redundancy.
- Community: Spawns new entities (negators, resonators).
- Optimization: Self-tuning thresholds.
- Base Path:
/mnt/negation_core(default) orNEGATION_BASE_PATH. - Model:
mistralai/Mixtral-8x22B-Instruct-v0.1(change viaMODEL_NAME). - Logging:
auto_negation_core.log, formatted byAbyssFormatter. - Network Ports: Defined in
negation_config.json(e.g., ZMQ: 5556).
auto_negation_core/
├── auto_negation_core.py
├── /mnt/negation_core/
│ ├── auto_negation_core.log
│ ├── intuition_core/
│ ├── checkpoint_*.pkl
│ ├── negation_config.json
│ └── optimization.log
- AbyssHardwareOptimizer: Resource profiling.
- NegationPulse: Contradiction signals.
- IntuitionLog: Encrypted insight storage.
- AbyssNegationWithErasure: Logic core.
- AbyssMemory: Three-tiered memory.
- AbyssNetwork: ZMQ-based exchange.
- AbyssCommunity: Entity simulation.
- AbyssOptimizer: Runtime tuning.
Run integrated test:
optimizer.test_full_system(num_iterations=20)- Fork and create feature branch.
- Commit and push changes.
- Open a pull request.
Licensed under the Apache License 2.0. See LICENSE.
This is a highly experimental system. Ensure strong hardware and cooling. Outputs may be abstract or philosophical.
Questions? Reach Vi Nhat Son via GitHub issues