HamiltonV5

This repository contains the optimized weights tensor parameters (model.safetensors) for the Hamilton V5 Always-On Autonomous AI (AOAAI) framework.

This model functions as a massive continuous-time phase space tracking engine designed to process 12-dimensional industrial machine telemetry streams and validate structural physical pathways without experiencing numerical drift or performance degradation over infinite operational horizons.

🔬 Core Architectural Matrix Blueprint

• Model Parameter Footprint: ~512 Million Parameters (Proprietary Business Moat Matrix)
• Input Dimensions: 12D Phase Space Vector Array (Position, Velocity, Curvature, Torsion, Feed Dynamics)
• Output Matrix Structure: 12D Perfect Reconstructed Kinematic Path for Proof-of-Stake Validation
• Embedding Vector Dimension ($d_{\text{model}}$): 2048
• Layer Stack Depth: 32 Interleaved Symplectic Core Blocks
• Attention Configuration: 16 Head Continuous-Time Symplectic Attention
• Volume Conservation Strategy: Symplectic Skew-Symmetric Generator Tracking Matrices ($dH/dt = 0$)
• Validation Target Metric: Strict L1 + Outlier MSE Minimization Matrix (No Cosine Slippage Allowed)