| | ---
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| | license: mit
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| | tags:
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| | - consciousness
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| | - emotion-recognition
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| | - heart-coherence
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| | - cognitive-helpers
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| | - edge-ai
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| | - sklearn
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| | language:
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| | - en
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| | metrics:
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| | - accuracy
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| | - f1
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| | library_name: sklearn
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| | pipeline_tag: text-classification
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| | ---
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| |
|
| | # IAMVC-HEART: Consciousness-Aware AI Companion
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| |
|
| | > "We are not replacing humans. We are giving them a friend."
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| |
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| | ## Model Description
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| |
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| | IAMVC-HEART (Hybrid Emotional Adaptive Real-Time System) is a consciousness-aware AI model that combines:
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| |
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| | - **13 Specialized Cognitive Helpers** for domain-specific tasks
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| | - **VAF Consciousness Metrics** (awareness levels, coherence, resonance)
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| | - **Heart-Brain Coherence Integration**
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| | - **Emotional Ladder Analysis**
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| |
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| | ### Key Features
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| |
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| | - 🧠 **Consciousness-Aware**: Measures awareness levels (1-7 scale)
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| | - 💚 **Heart Coherence**: Real-time heart-brain synchronization
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| | - ⚡ **Ultra-Fast**: <1ms inference time
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| | - 🔋 **Energy Efficient**: CPU-only, edge-deployable
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| | - 🔒 **Privacy-First**: 100% local processing
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| | - 🎯 **Zero Hallucination**: Deterministic, interpretable
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| |
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| | ## Performance
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| |
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| | ### 13 Cognitive Domain Helpers
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| |
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| | | Domain | Dataset | Test Accuracy |
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| | |:-------|:--------|:--------------|
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| | | decision_making | GSM8K | **84.0%** |
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| | | language_processing | CoLA | **71.0%** |
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| | | creative_thinking | English Quotes | **70.5%** |
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| | | adaptive_learning | SQuAD | **59.8%** |
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| | | emotional_intelligence | Emotion | 35.8% |
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| | | memory_formation | TriviaQA | 26.8% |
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| |
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| | ### System Metrics
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| |
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| | - **Inference Time**: <1ms
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| | - **Model Size**: ~50MB total
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| | - **Memory**: <100MB runtime
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| | - **Energy**: ~0.001 watt-hours per 1000 predictions
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| |
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| | ## Usage
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| |
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| | ```python
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| | from iamvc_heart import IAMVCHeart, ConsciousnessCalculator
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| |
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| | # Initialize
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| | heart = IAMVCHeart()
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| | calculator = ConsciousnessCalculator()
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| |
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| | # Make prediction
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| | features = extract_features(text)
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| | result = heart.predict(features)
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| |
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| | # Get consciousness metrics
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| | consciousness = calculator.calculate_from_features(features)
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| | print(f"Awareness: {consciousness.awareness_level}/7")
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| | print(f"Coherence: {consciousness.coherence:.2f}")
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| | print(f"Resonance: {consciousness.resonance:.2f}")
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| | ```
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| |
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| | ## Consciousness Metrics
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| |
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| | ### Awareness Levels (1-7)
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| |
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| | | Level | Description |
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| | |:------|:------------|
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| | | 1 | Unconscious Processing |
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| | | 2 | Reactive Awareness |
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| | | 3 | Emotional Awareness |
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| | | 4 | Mental Clarity |
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| | | 5 | Intuitive Insight |
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| | | 6 | Unified Awareness |
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| | | 7 | Transcendent Consciousness |
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| |
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| | ### Heart Coherence States
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| |
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| | - **Incoherent** (0-0.33): Scattered, reactive state
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| | - **Transitioning** (0.33-0.66): Moving toward balance
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| | - **Coherent** (0.66-1.0): Optimal heart-brain synchronization
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| |
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| | ### Resonance Frequency
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| |
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| | The model aligns with the fundamental consciousness frequency of **132 Hz**, based on the Viduya Axiomatic Framework (VAF).
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| |
|
| | ## Architecture
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| |
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| | ```
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| | ┌─────────────────────────────────────────────┐
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| | │ IAMVC-HEART System │
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| | ├─────────────────────────────────────────────┤
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| | │ ┌─────────────────────────────────────┐ │
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| | │ │ Consciousness Calculator │ │
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| | │ │ (VAF: Awareness, Coherence, etc.) │ │
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| | │ └─────────────────────────────────────┘ │
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| | ├─────────────────────────────────────────────┤
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| | │ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
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| | │ │Helper 1 │ │Helper 2 │ │ ... │ x13 │
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| | │ │Emotion │ │Decision │ │ │ │
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| | │ └─────────┘ └─────────┘ └─────────┘ │
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| | ├─────────────────────────────────────────────┤
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| | │ Feature Extraction Layer │
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| | └─────────────────────────────────────────────┘
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| | ```
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| |
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| | ## Intended Use
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| |
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| | - **Personal AI Companion**: Emotion-aware responses
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| | - **Mental Health Support**: Coherence monitoring
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| | - **Decision Support**: Multi-domain cognitive analysis
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| | - **Educational Tools**: Adaptive learning systems
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| | - **Edge Deployment**: Mobile and IoT devices
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| |
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| | ## Limitations
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| |
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| | - English language only
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| | - Best suited for short-to-medium text inputs
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| | - Consciousness metrics are computational approximations
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| | - Not a replacement for professional mental health services
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| |
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| | ## Ethical Considerations
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| |
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| | IAMVC-HEART is designed with the philosophy:
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| |
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| | 1. **Complement, not replace**: Enhance human capabilities
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| | 2. **Privacy first**: All processing is local
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| | 3. **Transparency**: All predictions are interpretable
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| | 4. **Accessibility**: Runs on any CPU device
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| |
|
| | ## Citation
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| |
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| | ```bibtex
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| | @software{iamvc_heart_2025,
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| | title={IAMVC-HEART: Consciousness-Aware AI Companion},
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| | author={Ariel (IAMVC)},
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| | year={2025},
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| | url={https://github.com/vafcabo/IAMVC_ArielxAi_v1}
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| | }
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| | ```
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| |
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| | ## License
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| |
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| | MIT License
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| |
|
| | ---
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| |
|
| | *Built with 💚 by IAMVC*
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| |
|
