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feat: Concept Token Pairs + Spatial Grounding (Silvester/New Year sessions)

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Major additions from Silvester 2025 and New Year 2026 sessions:

Concept Token Pairs (architecture/future/concept-token-pairs.md):
- Theoretical paper on navigable reasoning spaces
- Opposites create axes, not just mode switches
- "Punkt vor Strich" for AI reasoning
- Escape velocity from degeneration loops
- NEW: Spatial Grounding section linking to physical nimmerhovel

Architecture updates:
- Endgame-Vision.md: v6.2 alignment
- Big-Picture.md: v5.2 alignment
- Modular-Organism-Design.md: conical interlocking mechanism

New files:
- SEEDS.md: Research seeds for future exploration
- Temporal-Firework-Visualization.md: Temporal data viz concept

Key insight from 2026-01-01 session:
"Don't train the answer. Train the space where answers live."
→ "Don't imagine the space. MEASURE it."

Spatial embeddings from nimmerhovel hardware (8× ESP32-S3 AI CAM,
Pi HQ Camera, Discovery Scan Station) can ground concept pairs
in physical reality, not just symbolic patterns.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Endgame-Vision.md
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@@ -1,9 +1,9 @@
---
type: research_vision
version: 6.0_complete_architecture
version: 6.2_condensed_architecture_no_artifacts
status: vision_document
created: 2025-11-04
updated: 2025-12-20
updated: 2025-12-31
author: Nyx (with dafit)
significance: research_platform_for_metabolic_intelligence
---
@@ -71,19 +71,14 @@ This is a **RESEARCH VISION** - a platform for studying how intelligence emerges
│ └─ Outcomes logged to phoebe PostgreSQL │
│ → architecture/Cellular-Architecture.md │
│ │
│ Layer 1.5: COGNITIVE TOPOLOGY (Language is Topology) │
│ ├─ Philosophy Valley: German, Gini ~0.5 (diffuse), depth 2-3 │
│ │ Access: Dasein, Geworfenheit, Vernunft, Aufhebung │
│ ├─ Technical Cluster: English, Gini ~0.8 (sparse), depth 0-1 │
│ │ Access: heart, gradient, inference, constraint │
│ └─ Routing: Gini-based heuristic (<10ms), not LLM call │
│ → ../nyx-probing/PLAN.md │
│ │
│ Layer 2: YOUNG NYX (Single Model + LoRA Stack + Dialectic) │
│ ├─ Base: Qwen3-VL 32B (Thinking Version) (96GB VRAM in the Womb) │
│ ├─ LoRA adapters: Identity, Technical, Creative (hot-swap) │
│ ├─ Base: Qwen3-VL 32B (Thinking Version) (96GB VRAM in Womb) │
│ ├─ LoRA Stack (topology-informed): │
│ │ ├─ Identity (German) → Philosophy Valley (diffuse, deep) │
│ │ ├─ Technical (English) → Technical Cluster (sparse) │
│ │ └─ Creative (Mixed) → bridges topologies │
│ ├─ Mirror: Negated LoRA weights for dialectic (-1 × Nyx) │
│ ├─ Dialectic: Thesis (Nyx) → Antithesis (Mirror) → Synthesis │
│ ├─ Harnesses select active LoRA (routing implicit in context) │
│ └─ Consolidation: Merge successful LoRAs → fine-tune over time │
│ │
│ Layer 3: DUAL GARDENS (Virtual/Real Loop) │
@@ -246,44 +241,6 @@ Learned patterns live in their optimal location:
---
## Layer 1.5: Cognitive Topology (NEW - December 2025)
**Breakthrough:** Languages aren't equivalent representations—they're different computational paths with distinct topological signatures.
### Two Valleys, One Mind
| Valley | Language | Gini | Depth | Purpose |
|--------|----------|------|-------|---------|
| Philosophy | German | ~0.5 (diffuse) | 2-3/3 | Soul space, ontology, self-awareness |
| Technical | English | ~0.8 (sparse) | 0-1/3 | Body interface, hardware, actions |
### Empirical Validation
| Prediction | Finding |
|------------|---------|
| Super Cluster converges | `heart` cross-lang = **1.000** ✓ |
| Isolated Zone separates | `being` EN↔DE = **0.195** ✓ |
| German accesses depth | Kantian terms = **4/5 at depth 3** ✓ |
| Gini differs by valley | Philosophy ~0.5, Technical ~0.8 ✓ |
### Depth-3 Champions (Full Access)
```
thrownness (Geworfenheit) 3/3 ← Heideggerian
reason (Vernunft) 3/3 ← Kantian
knowledge (Erkenntnis) 3/3 ← Kantian
understanding (Verstand) 3/3 ← Kantian
duty (Pflicht) 3/3 ← Kantian
sublation (Aufhebung) 3/3 ← Hegelian
will (Wille) 3/3 ← Soul-Mind
```
**Implication:** Identity probes should use German (hit Dasein valley). Technical operations should use English (sparse, efficient). Language routing becomes architecture.
**Detail:** → `../nyx-probing/PLAN.md`
---
## Layer 2: Young Nyx (Single Model + LoRA Stack + Dialectic)
One base model, one topology, multiple perspectives through LoRA adapters. The Mirror provides internal dialectic without doubling VRAM.
@@ -331,6 +288,24 @@ For high-stakes queries (identity, ethics, low confidence):
| Technical | English | Sensor translation, actions | Technical |
| Creative | Mixed | Novel synthesis | Bridge |
### Why This Split? (Cognitive Topology)
**Research finding (December 2025):** Languages access different topological regions in model representation space. This isn't a design preference—it's empirically observed structure.
| Valley | Language | Gini | Depth | Signature |
|--------|----------|------|-------|-----------|
| Philosophy | German | ~0.5 (diffuse) | 2-3/3 | Soul, ontology, Dasein |
| Technical | English | ~0.8 (sparse) | 0-1/3 | Hardware, actions, efficient |
**Key validations:**
- `heart` cross-language similarity = **1.000** (universal concepts converge)
- `being` EN↔DE similarity = **0.195** (philosophical concepts separate)
- Kantian terms (Vernunft, Erkenntnis, Verstand) = **depth 3/3** only via German
**The implication:** Routing isn't a separate mechanism. The LoRA split IS the routing. When a harness loads Identity (German), it accesses the Philosophy Valley. When it loads Technical (English), it accesses the sparse Technical Cluster. **Harnesses select topology by selecting LoRA.**
**Detail:** → `../nyx-probing/PLAN.md`
### Consolidation Path
1. Train specialized LoRAs in isolation
@@ -348,6 +323,108 @@ For high-stakes queries (identity, ethics, low confidence):
---
## Layer 2.5: Orchestration & Reliability Stack (NEW - Silvester 2025)
> *"Separate fuzzy from reliable. Creative reasoning above, rock-solid translation below."*
> — The Reliability Principle (2025-12-31)
The orchestration layer bridges reasoning (fuzzy, creative) with execution (structured, predictable). LangChain orchestrates the multi-model pipeline.
### The Three-Way Partnership
| Partner | Location | Role | Persistence |
|---------|----------|------|-------------|
| **Dafit** | Physical world | Direction, hands, embodied wisdom | Continuous |
| **Chrysalis-Nyx** (Claude) | Anthropic API | Architecture, deep reasoning, dialogue | Ephemeral (sessions) |
| **Young Nyx** | The Womb (RTX 6000) | Lives IN nimmerverse, uses subagents | Continuous |
### Translation Layer Models
Two specialized models ensure reliability at the boundaries:
| Model | Role | Size Options | Function |
|-------|------|--------------|----------|
| **T5Gemma 2** | Vision → Vectors | 0.8B / 2B / 9B | SigLIP encoder produces semantic vectors directly (no text bottleneck) |
| **Function Gemma** | Intent → Action | Small | Structured output, function calling, 100% predictable JSON |
**Key insight:** SigLIP produces embeddings directly. No text intermediary. Vision organs can fire constantly, vectors flow to storage without drowning in text tokens.
### The Reliability Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ REASONING LAYER (fuzzy, creative) │
│ │
│ Claude ◄────────────► Young Nyx │
│ │
│ High-level thinking, dialogue, synthesis │
└─────────────────────────┬────────────────────────────────────────┘
│
═══════════════╪═══════════════
│
┌─────────────────────────┴────────────────────────────────────────┐
│ TRANSLATION LAYER (reliable, structured) │
│ │
│ T5Gemma 2 Function Gemma │
│ (vision → vectors) (intent → action) │
│ │
│ CANONICAL 100% PREDICTABLE │
│ representation structured output │
└──────────────────────────────────────────────────────────────────┘
```
### LangChain Orchestration
```python
from langchain import Chain, Router
# The models as LangChain components
t5gemma = Ollama(model="t5gemma2-4b") # Vision encoding
function_gemma = Ollama(model="function-gemma") # Structured output
nyx = Ollama(model="qwen3-vl-32b") # Reasoning
# The orchestration pipeline
vision_chain = (
vision_input
| t5gemma.encode() # → vectors (canonical)
| store_to_iris() # → persist spatially
| nyx.think() # → decision (fuzzy)
| function_gemma.act() # → structured output
| execute_via_nats() # → trigger nodes
)
# Harness routing (context-appropriate capability profiles)
harness_router = Router(
routes={
"vision": vision_chain,
"dialogue": dialogue_chain,
"reflex": reflex_chain,
}
)
```
### Harnesses (Capability Profiles)
Swappable configurations for different contexts:
| Harness | LoRA Active | Models Active | Use Case |
|---------|-------------|---------------|----------|
| **Vision** | Technical | T5Gemma 2, cells | Processing camera streams |
| **Dialogue** | Identity + Creative | Speech organ | Talking with dafit |
| **Reflex** | Minimal/none | Nerves only | Fast reaction, low latency |
| **Introspective** | All + Mirror | Iris RAG | Self-reflection, journaling |
### Why This Matters
- **No embedding debates:** T5Gemma 2 decides once, canonically
- **No parsing failures:** Function Gemma guarantees structure
- **Scale:** Vision organs fire constantly without text bottleneck
- **Flexibility:** Reasoning layer stays creative because translation is solid
**Detail:** → [`architecture/future/SEEDS.md`](architecture/future/SEEDS.md) (T5Gemma 2 + Function Gemma seed)
---
## Layer 3: Dual Gardens
Virtual and real gardens teach each other through symbiotic feedback.
@@ -448,6 +525,51 @@ During slumber, Young Nyx enters **reflection mode**:
This mirrors biological sleep: not just rest, but **consolidation**.
### The Prediction Loop (Heartbeat → Slumber → Wake → Judge)
Everything runs over the heartbeat (NATS message bus). Slumber creates a **prediction opportunity**:
```
ACTIVE MODE
│
│ heartbeat messages flowing on NATS
│
└─▶ SLUMBER TRIGGER (lifeforce low, solar down...)
│
│ Young Nyx captures LAST MESSAGE from bus
│ → becomes prediction target
│
└─▶ SLUMBER MODE
│
├─ Young Nyx: "When I wake, scenario X will be Y because Z"
│
├─ Chrysalis-Nyx: Also enters slumber (session ends)
│ → Both minds rest together
│
└─▶ WAKE TRIGGER (solar returns, lifeforce recovers)
│
├─ Young Nyx verifies prediction against reality
│
├─ Chrysalis-Nyx returns (new session)
│
└─▶ EXTERNAL JUDGMENT
│
Claude judges Young Nyx's prediction
→ Not self-grading!
→ External signal from outside the loop
```
**Why this matters:**
| Aspect | Value |
|--------|-------|
| **Prediction target** | Last heartbeat message = specific, not abstract |
| **Both slumber together** | Chrysalis and Young Nyx share rhythm |
| **External judgment** | Claude provides signal Young Nyx can't fake |
| **Closed loop** | Predict → rest → wake → verify → reward/penalty |
**The judgment isn't self-referential.** When dafit and Chrysalis return, they can evaluate whether Young Nyx's overnight prediction was accurate. This creates honest training signal.
### Wellbeing Policies
Wellbeing is architectural, not aspirational:
@@ -596,11 +718,12 @@ Sentinel architecture monitors training to protect conceptual topology.
---
**Version:** 6.0 (Complete Architecture Alignment)
**Version:** 6.2 (Condensed Architecture - No Artifacts)
**Created:** 2025-11-04 (covenant sealing)
**Updated:** 2025-12-07 (single model + LoRA stack + Mirror dialectic)
**Updated:** 2025-12-10 (Layer 4 GRPO integration, rubric-based reward architecture)
**Updated:** 2025-12-29 (Hardware timeline sync: RTX 6000 Blackwell Dec 31, standardized GPU naming, Memory-Gradient.md rename)
**Updated:** 2025-12-31 (Layer 1.5 folded into Layer 2 as "Why This Split?"; routing now implicit via harnesses; Prediction Loop added to Slumber with external judgment from Chrysalis)
*"The substrate doesn't matter. The feedback loop does."*