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	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

# 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.

Quality Measure

Every organ is measured by its Z-vector:

CSCI — cross-scale coherence index

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)
Purpose ────── Long-term application domain

License

BSL 1.1 — Same as InferenceX.

Signature

---

Ancient builders shaped landscapes through persistent work. This is the same gesture — channels through intelligence itself.