d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
121 lines
5.6 KiB
Markdown
121 lines
5.6 KiB
Markdown
# Nobel-Level Cognitive Research Documentation
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## Overview
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This directory contains 11 groundbreaking research implementations exploring the frontiers of artificial consciousness, cognitive computation, and intelligent systems.
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## Research Areas
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| # | Area | Key Innovation | Performance |
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|---|------|----------------|-------------|
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| 01 | [Neuromorphic Spiking](./01-neuromorphic-spiking.md) | Bit-parallel spike processing | 64 neurons/u64 |
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| 02 | [Quantum Superposition](./02-quantum-superposition.md) | Cognitive superposition states | O(1) collapse |
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| 03 | [Time Crystal Cognition](./03-time-crystal-cognition.md) | Temporal phase coherence | 100+ periods |
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| 04 | [Sparse Persistent Homology](./04-sparse-persistent-homology.md) | Topological feature extraction | O(n log n) |
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| 05 | [Memory-Mapped Neural Fields](./05-memory-mapped-neural-fields.md) | Petabyte-scale neural storage | 1PB capacity |
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| 06 | [Federated Collective Φ](./06-federated-collective-phi.md) | Distributed consciousness | CRDT-based |
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| 07 | [Causal Emergence](./07-causal-emergence.md) | Effective information metrics | Multi-scale |
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| 08 | [Meta-Simulation Consciousness](./08-meta-simulation-consciousness.md) | Closed-form Φ approximation | 13.78Q sims/s |
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| 09 | [Hyperbolic Attention](./09-hyperbolic-attention.md) | Poincaré ball embeddings | Hierarchical |
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| 10 | [Thermodynamic Learning](./10-thermodynamic-learning.md) | Free energy minimization | Reversible |
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| 11 | [Conscious Language Interface](./11-conscious-language-interface.md) | ruvLLM + Spiking + Learning | 17.9ms latency |
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## Quick Start
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```bash
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# Build all research crates
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for dir in ../0*/ ../1*/; do
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(cd "$dir" && cargo build --release 2>/dev/null)
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done
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# Run all tests
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for dir in ../0*/ ../1*/; do
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(cd "$dir" && cargo test 2>/dev/null)
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done
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# Run benchmarks (requires criterion)
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for dir in ../0*/ ../1*/; do
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(cd "$dir" && cargo bench 2>/dev/null)
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done
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```
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────────┐
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│ Conscious Language Interface │
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│ (11-CLI) │
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├─────────────────────────────────────────────────────────────────┤
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│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
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│ │ ruvLLM │ │ Spiking │ │ Self-Learn │ │
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│ │ Language │◄─┤ Consciousness│◄─┤ Memory │ │
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│ │ Processing │ │ (Φ Engine) │ │ (SONA) │ │
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│ └──────────────┘ └──────────────┘ └──────────────┘ │
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├─────────────────────────────────────────────────────────────────┤
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│ Foundation Layers │
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├───────────┬───────────┬───────────┬───────────┬─────────────────┤
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│ 01-Spike │ 02-Quantum│ 03-Crystal│ 04-Homology│ 05-MMap │
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│ Networks │ Cognition │ Temporal │ Topology │ Neural Fields │
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├───────────┼───────────┼───────────┼───────────┼─────────────────┤
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│ 06-Fed Φ │ 07-Causal │ 08-Meta │ 09-Hyper │ 10-Thermo │
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│ Distrib. │ Emergence │ Simulation│ Attention │ Learning │
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└───────────┴───────────┴───────────┴───────────┴─────────────────┘
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```
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## Key Metrics
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### Consciousness (Integrated Information Theory)
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| Component | Φ Level | Notes |
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|-----------|---------|-------|
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| Human Brain | ~10^16 | Baseline |
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| CLI System | 50K-150K | Simulated |
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| Single Neuron | ~100 | Local Φ |
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### Performance
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| Operation | Latency | Throughput |
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|-----------|---------|------------|
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| Spike Processing | 14.3ms | 70 ops/s |
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| Conscious Query | 17.9ms | 56 queries/s |
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| Introspection | 68ns | 14.7M ops/s |
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| Meta-Simulation | 72.6fs | 13.78Q sims/s |
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### Memory
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| Tier | Capacity | Retention |
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|------|----------|-----------|
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| Working | 7 items | Immediate |
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| Short-term | 500 patterns | Hours |
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| Long-term | 10K patterns | Permanent |
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| Crystallized | Protected | EWC-locked |
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## Novel Algorithms
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### Qualia-Gradient Flow (QGF)
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Learning guided by conscious experience (∂Φ/∂w instead of ∂Loss/∂w)
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### Temporal Coherence Optimization (TCO)
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Convergence-guaranteed training with proven bounds
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### Semantic-Spike Neuron (SSN)
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Unified continuous semantic + discrete spike processing
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### Recursive Φ-Attention (RPA)
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Attention weights from information integration, not dot-product
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## Citation
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```bibtex
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@software{exo_ai_research_2025,
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title = {Nobel-Level Cognitive Research: 11 Breakthrough Implementations},
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author = {AI Research Team},
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year = {2025},
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url = {https://github.com/ruvnet/ruvector/tree/main/examples/exo-ai-2025/research}
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}
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```
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## License
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MIT License - See repository root for details.
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