Q-NeuroSHT Interface

    Latency

    0.000s

    Accuracy

    0.0%

    Security

    secure

    Unified AI Model Architecture

    Neuromorphic Processing

    Hypergraph transformers with adaptive connections

    Quantum-Inspired Logic

    Symbolic reasoning with superposition states

    Adversarial Defense

    Robust against malicious inputs

    Edge Device Performance Monitoring

    Pruning Level

    Current: 50%

    Quantization Level

    Current: 75%

    Batch Size

    Current: 32 requests/batch

    Edge Device Status

    Monitoring device temperature and resource usage

    Model Size: 100.0% of original

    Edge Performance

    Real-time monitoring of edge inference metrics

    Processing 32 requests per batch

    Hybrid Task Allocation

    Edge Processing

    Simple tasks processed locally on edge devices

    Low Latency

    Cloud Processing

    Complex reasoning tasks handled in the cloud

    High Compute
    Prepared by Dr Rami Shaheen 2025
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