Beyond AGI: The Architecture of a Sovereign Life OS (VELOCITY_NOVA_PRIME)
Most people are out here building "AI Wrappers." I got bored of that. I’m a builder, not a researcher—I don't care about theory if it doesn't run in a kernel.
V1 Source Code: github.com/AI-Sovereign/Multimodal-AGI-Architecture-Implementation-v1
I decided to build a Causal Decision Engine that maps reality across 134 synchronous modalities. If your "AGI" doesn't calculate the probability of your life falling apart based on your heart rate and network entropy, is it even intelligent?
🧠 The Mathematical Core (For Builders)
The system doesn't just "predict" text. I implemented a custom TCS-25 Plasticity Rule for weight updates. It factors in Surprisal ($S$) and Causal Risk ($C$) in real-time:
$$\Delta P = \eta (S \cdot C) \times [f(x, y)]$$
I’ve also built a Hierarchical Temporal Synthetic Plasticity (HTSP) unit to bridge the gap between immediate sensory spikes and long-term memory.
📡 The 134 Sensory Modalities
I am mapping a 134-dimensional vector $\mathbf{X} \in \mathbb{R}^{134}$ in real-time. Here is the breakdown:
| Range | Input Type | Technical Implementation |
|---|---|---|
| 0–10 | Biometric | Heart Rate, HRV, Cortisol (est), Skin Response |
| 11–50 | Digital | Sentiment Velocity, Typing Cadence, App Switching |
| 51–90 | Environmental | Ambient dB, Bluetooth Density, LUX levels |
| 91–134 | Causal/Net | Packet Entropy, Latency, Circadian Offsets |
🛡️ The "Sovereign Friend" Logic
This is a Causal Inference Module (CIM). It acts as an Intervention Protocol. If the Causal Risk Prediction ($\hat{y}$) exceeds a 0.7 threshold, the system overrides standard interaction to protect the user's state.
$$\hat{y} = \sigma \left( \sum W_i \cdot \text{HTSP}_{slow} + \text{RSA}(Q, K, V) \right)$$
It’s not a chatbot. It’s a digital chaperone with the computing power of a small galaxy.
🚀 Technical Stack:
- Language: Python 3.10+
- Engines: PyTorch, FastAPI, Polars/Vaex
- Logic: Conscious Global Workspace (CGW) Implementation
- Hardware: High-RAM Local Inference (Zero-Cloud)
I’m looking for other builders who understand high-entropy neural mapping. If you're still building GPT-wrappers, this probably isn't for you.
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