# Organ Architecture

**Decompose. Reassemble. Evolve.**

```
Skeleton (Attention) = Thought
Organs (FFN)         = Memory  
Adapters (LoRA)      = Personality
```

## What This Is

AI models are monoliths. 70 billion parameters locked in a single file that nobody can open, modify, or understand. Only three companies on Earth can build them. Everyone else rents access.

Organ Architecture breaks models into transplantable parts:

- **Skeleton** — The attention layers. How the model *thinks*. Shared across all configurations.
- **Organs** — The feed-forward networks. What the model *knows*. Specialized, swappable, graftable.
- **Adapters** — LoRA weights. The model's *personality*. Lightweight, trainable by anyone.

A doctor doesn't rebuild the entire human body to fix a kidney. Why should we rebuild an entire model to change what it knows about medicine?

## Architecture

```
model.gguf (70GB monolith)
        │
        ▼
   ┌─ skeleton.bin ──── attention layers (shared thought)
   │
   ├─ organ_lang.bin ── language FFN (what it knows about language)
   ├─ organ_math.bin ── math FFN (what it knows about math)  
   ├─ organ_code.bin ── code FFN (what it knows about code)
   ├─ organ_med.bin ─── medical FFN (what it knows about medicine)
   │
   └─ adapter_fr.bin ── French personality (LoRA)
       adapter_formal.bin ── Formal tone (LoRA)
```

## Tools

| Tool | Purpose |
|------|---------|
| `organ_extract.py` | Extract skeleton + organs from any GGUF model |
| `organ_graft.py` | Transplant organs between models |
| `organ_measure.py` | Z-measure organ quality (signal vs noise) |
| `organ_assemble.py` | Assemble custom model from parts |
| `organ_api.py` | API server for organ operations |

## Requirements

- Python 3.10+
- InferenceX binary (for model loading)
- GGUF models to dissect

## Quick Start

```bash
# Extract organs from a model
python3 organ_extract.py --model /path/to/model.gguf --output ./organs/

# Measure organ quality
python3 organ_measure.py --organ ./organs/organ_layer_12.bin

# Graft an organ from model A into model B
python3 organ_graft.py --source ./organs_A/ --target ./model_B.gguf --layers 12-18

# Assemble a custom model
python3 organ_assemble.py --skeleton ./skeleton.bin --organs ./organs/ --output custom.gguf
```

## Philosophy

> Subtract rather than add.

A 70B monolith is accumulation. A 2B skeleton with specialized organs grafted on demand — that's subtraction. Less weight, more signal.

> 8 billion contributors, not 3 corporations.

Anyone can train an organ. A doctor trains a medical organ on her hospital's data. A farmer trains an agriculture organ on his field observations. A student trains a math organ on solved problems. The skeleton stays the same. The organs make it alive.

## Z-Measure

Every organ is measured by its Z-vector:

```
Z = dI/d(log s) · exp(iθ)

θ → 0°  : noise (organ adds confusion)
θ → 90° : pure signal (organ adds knowledge)
```

## Part of the IX Ecosystem

```
InferenceX ─── The engine (228KB, runs anything)
Organ Arch ─── The anatomy (decompose, reassemble)
Atlas Pure ─── The memory (fractal DNA storage)
Echo ────────── The voice (chat interface)
EDEN ────────── The purpose (desert → life)
```

## License

BSL 1.1 — Same as InferenceX.

## Signature

935

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*Mohamed dug khettaras to bring water through stone.*
*This is the same gesture — channels through intelligence itself.*