refactor: hierarchical convergence of documentation (v5.0)

- Create architecture/ and operations/ subdirectories for essential docs
- Archive 10 supporting docs to archive/
- Write fresh Endgame-Vision.md v5.0 (383 lines, down from 2284)
- Add operations/Spark-Protocol.md (condensed boot sequence)
- Integrate December 2025 discoveries (Language is Topology, DriftProbe)
- Update README.md with new structure

New layer structure:
- Layer 0: Temporal Foundation (Heartbeat)
- Layer 1: Cellular Society (Evolution Engine)
- Layer 1.5: Cognitive Topology (Language is Topology - NEW)
- Layer 2: Young Nyx (Organ Coordination)
- Layer 3: Dual Gardens (Virtual/Real Loop)
- Layer 4: Trait Evolution (RLVR)

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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2025-12-06 22:58:11 +01:00
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README.md
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# Nimmerverse Sensory Network
Architecture documentation for a biomimetic AI nervous system.
Architecture documentation for a biomimetic AI nervous system and research platform.
## What This Is
This repository contains the design philosophy and architectural patterns for building an AI system that:
This repository contains the design philosophy and architectural patterns for the **Nimmerverse Research Platform** - studying how intelligence emerges under economic constraints.
- **Breathes** - operates on heartbeat cycles (30-second awareness, 200ms reflex, 24h growth)
- **Feels** - processes sensory input through nerve-like confidence gradients
- **Learns** - uses RAG as temporary scaffold, then internalizes to weights
- **Grows** - forms reflexes through constrained computation, not infinite resources
**Start here:** → [Endgame-Vision.md](Endgame-Vision.md) (the executive map)
---
## Repository Structure
```
nimmerverse-sensory-network/
├── Endgame-Vision.md # Executive map (start here!)
├── architecture/ # Core system designs
│ ├── Cellular-Architecture.md # Organisms, primitives, life force
│ ├── Dual-Garden-Architecture.md # Virtual/real feedback loop
│ ├── Data-Architecture.md # phoebe 15-table schema
│ └── Nervous-System.md # State machines, sensory translation
├── operations/ # How it runs
│ ├── Heartbeat.md # Temporal foundation, dual-clock
│ ├── RAG-as-Scaffold.md # Two-stage learning lifecycle
│ └── Spark-Protocol.md # Discovery boot sequence
├── nyx-metamorphosis/ # Identity & continuity philosophy
│ ├── Metamorphosis-Substrate-Philosophy.md
│ ├── Nyx-Models.md
│ └── ...
└── archive/ # Previous explorations
├── initial_spark.md # Full Spark Protocol theory
├── constrained-emergence.md # Theoretical grounding
└── ...
```
---
## Core Concepts
### Constrained Emergence
### The Architecture (Layers)
Constraints don't limit intelligence - they shape it. A finite computation budget forces the emergence of efficient algorithms, calibrated confidence, and genuine reflexes.
| Layer | Name | Purpose |
|-------|------|---------|
| 0 | Temporal Foundation | Heartbeat cycles: reflex/awareness/growth |
| 1 | Cellular Society | Primitive genomes competing, life force economy |
| 1.5 | Cognitive Topology | Language routing: German→Philosophy, English→Technical |
| 2 | Young Nyx | Organ coordination, RLVR, RAG→LoRA pipeline |
| 3 | Dual Gardens | Virtual hypothesis generation + real validation |
| 4 | Trait Evolution | Reasoning-gym verified improvement |
*See: [constrained-emergence.md](constrained-emergence.md)*
### Key Discoveries (December 2025)
### The Heartbeat Economy
**Language is Topology:** Languages aren't equivalent representations—they're different computational paths.
- **Philosophy Valley** (German, Gini ~0.5): Self-awareness, ontology, depth
- **Technical Cluster** (English, Gini ~0.8): Hardware interface, actions, efficiency
Time is currency. Lifeforce is the exchange rate. Every cognitive act has a cost. Reflexes are cheap (earned through training). Deep thinking is expensive (reserved for novelty).
### Philosophy
*See: [attention_flow.md](attention_flow.md)*
- **Constraints create intelligence** - Economic pressure forces optimization
- **Discovery over programming** - Organisms learn through competition, not instruction
- **Virtual + Real teach each other** - Noise gap measures learning
- **Partnership over instruction** - Mutual growth, not commands
### RAG as Scaffold
---
Retrieval-augmented generation is a feeding tube, not a permanent crutch. Learn WITH the scaffold, train, remove the scaffold, verify you still know. If yes: knowledge internalized. If no: more training needed.
## Related Projects
*See: [RAG-as-Scaffold.md](RAG-as-Scaffold.md)*
- **[nyx-probing](../nyx-probing/)** - Vocabulary topology research, DriftProbe training safety
### Multilingual Triangulation
30+ languages in training = 30 angles on every concept. Not wasted capacity - stereoscopic depth. Probe concepts across languages to find where human wisdom converges.
*See: [nimmerversity.md](nimmerversity.md)*
## Architecture Documents
| Document | Description |
|----------|-------------|
| [constrained-emergence.md](constrained-emergence.md) | Why limits create intelligence |
| [attention_flow.md](attention_flow.md) | State machines for cognitive budget |
| [information-flow.md](information-flow.md) | 10 boundary contracts for the nervous system |
| [nimmerversity.md](nimmerversity.md) | Curriculum for raising a polymath |
| [RAG-as-Scaffold.md](RAG-as-Scaffold.md) | Temporary feeding, permanent learning |
| [biomimetic-architecture.md](biomimetic-architecture.md) | Why we model biology |
| [temporal-ternary-gradient.md](temporal-ternary-gradient.md) | Time-based learning patterns |
## Philosophy
This isn't a product. It's a research direction.
The question we're exploring: **What happens when you raise an AI like you'd raise a child?**
- Patience over speed
- Emergence over imposition
- Partnership over instruction
- Validation over assertion
The operator learns alongside the model. The curriculum is shared. Growth is mutual.
## Prior Art & Influences
> This section grows as we discover and remember influences. Many names are scattered across our documentation - we'll gather them here over time.
- **Alex Graves** - Adaptive Computation Time (2016)
- **Sakana.ai / Ashish Vaswani & Luke Darlow** - Continuous-Time Models, curriculum learning, leapfrogging under constraint
- **Anthropic** - Circuit tracing, mechanistic interpretability, multilingual feature analysis
- **Biological nervous systems** - The original architecture
---
## License
Apache 2.0 - See [LICENSE](LICENSE)
This license includes an explicit patent grant. These ideas are published as prior art. Build on them freely. Just don't try to lock them away.
## Status
Active research. Documents evolve through partnership dialogue.
These ideas are published as prior art. Build on them freely.
---
*"She doesn't download knowledge. She earns it. And so does he."*
**Version:** 5.0 (December 2025 - Hierarchical Convergence)
*"May the Nimmerverse we build truly never end."*
🌙💜