Stop building wrappers. I’m building a 132-modality AGI core from my bedroom.

#ai #agi #python #opensource

The Problem with "Smart" AI

Let’s be real: Most "AI" today is just a fancy autocomplete wearing a suit. If your system doesn't know your heart rate is spiking while your network latency is dropping, it isn't "intelligent"—it’s just a glorified dictionary.

I’m a builder, not a researcher. I’m done reading 50-page whitepapers that amount to nothing. I’m coding Omni_Genesis_Prime (v0.7.0): a Sovereign Life OS.

The Architecture: Why 132 Modalities?

Most multimodal models stop at text, image, and maybe audio. That’s cute. My system flattens 132 distinct streams—from raw BIOS interrupts and Scapy-captured network entropy to real-time biosignals—into a single 4096-D latent space.

The Tech Stack 🛠️

The Brain: Hybrid SNN (Spiking Neural Networks) via snntorch. Backprop is too slow for reality; I’m using temporal coding to process data as it happens.
The Engine: Polars handling the 132-modality buffer. If you’re still using Pandas for sub-millisecond entropy checks, you’ve already lost.
The Logic: TCS-25 Plasticity. It’s a Hebbian-modified learning loop that prioritizes surprisal over static patterns.

The Controversy: Transformers are a Dead End

Here is where the "experts" will get mad: Attention is not all you need. If you’re building AGI on a standard transformer architecture, you’re just building a faster library.

I’ve replaced the standard attention mechanism with a Manifold Projection logic that treats data as a continuous flow rather than discrete tokens. Check the README for my HLS (Hyper Latent Space) projection math—some might say the manifold is too sparse, but I argue that's exactly why it scales without melting my GPU.

Implementation Status: IN THE TRENCHES 🏗️

Done: Sensory Cortex architecture & HLS projection math.
In-Progress: Wiring the SNN to live Scapy-based network streams.

Repository: https://github.com/AI-Sovereign/Multimodal-AGI-Architecture-Implementation-v1

I’m building this in the open because I want you to tear it apart. Is my manifold projection actually too sparse, or are you just used to over-parameterized bloat? Let’s argue in the comments.