Repository: https://github.com/AI-Sovereign/Multimodal-AGI-Architecture-...
The architecture handles 132 asynchronous modalities—from biological signals to network entropy via Scapy—flattened into a 1344-dimensional causal manifold. By utilizing a tiered "Tri-Brain" pipeline across decoupled packages (see /packages and /TCS), the system maintains cognitive stability where standard models fail.
Technical Specifications: * Modular Architecture: Distributed logic across specialized directories, separating the Sensory Cortex from the Causal Inference engine. * Tiered Processing: Integration of snnTorch (Spiking Neural Networks) for reflexive temporal triggers and torch_geometric (GNNs) for episodic memory retention. * TCS-25 Plasticity: Implementation of Hebbian-modified logic prioritizing "Surprisal" (MSE delta) over static weights, enabling online learning without backprop latency. * Performance: Optimized with Polars for sub-millisecond entropy checks across the full 132-modality buffer.
Current Status: The Sensory Cortex and HTSP (Hierarchical Temporal) units are fully operational. The system handles the 512-to-4096 latent space expansion with high precision. This is an implementation-first project; the codebase is the proof.
I am releasing this v0.7.0 codebase for architectural peer-review and technical validation. I am specifically interested in discussing the HLS projection math and the orchestration of modular inference engines with anyone working on non-transformer AGI paradigms.