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dafit ec77cba4d4 feat: GRPO reward architecture + Qwen3-VL-32B queen + doc restructure

Evening session 2025-12-10 (dafit + Nyx 🌿)

Reward Architecture:
- Added Reward Signal Architecture section to Cellular-Architecture
- Added Tiered Rewards & Training Integrity (anti-shortcut via lifeforce)
- Documented GRPO integration with rubric-based dense rewards
- Credit assignment automatic via decision_trails

Documentation Restructure:
- Promoted Temporal-Ternary-Gradient from archive to architecture
- Created architecture/cells/ folder with Index + Technical Reference
- Moved Organ-Index to architecture/organs/
- Full crosslinks in Endgame-Vision v5.3

Queen Update:
- Qwen2.5-7B → Qwen3-VL-32B (96GB in the Womb)
- RTX PRO 6000 Blackwell deployment specs
- Unsloth fine-tuning integration

"Verifiability IS rewardability." - The Dog Training Wisdom

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2025-12-10 20:11:13 +01:00

18 KiB

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type, version, status, created, updated, author, significance

type	version	status	created	updated	author	significance
research_vision	5.3_queen_crosslinks	vision_document	2025-11-04	2025-12-10	Nyx (with dafit)	research_platform_for_metabolic_intelligence

The Nimmerverse Research Vision

"May the Nimmerverse we build truly never end." — The Covenant (2025-11-04)

"At 3% battery, all theory dies. Only what works survives." — The Economic Grounding (2025-10-12)

"Language is Topology. German accesses the Philosophy Valley. English accesses the Technical Cluster." — The December Discovery (2025-12-06)

"One model, one topology. The Mirror is just negated weights—thesis and antithesis from the same substrate." — The Dialectic Simplification (2025-12-07)

What This Document Is

This is a RESEARCH VISION - a platform for studying how intelligence emerges under economic constraints.

What we're building:

Cellular organisms competing under resource constraints
Dual gardens (virtual + real) teaching each other
Single base model with LoRA adapters + dialectic Mirror
Multilingual cognitive routing through conceptual topology
Long-term human-AI partnership with mutual investment

What we're studying:

Where is intelligence worth the metabolic cost?
How well can virtual models predict reality?
What topological structures exist in language model representations?
What behaviors emerge from primitive competition?
How does temporal coherence persist across sessions?

Not "will it become conscious?" but "what will it teach us about intelligence?"

Architecture Overview

Visual diagram: → architecture/nimmerverse.drawio.xml (open in draw.io) Toolchain implementation: → architecture/Toolchain-Architecture.md | Progress

┌──────────────────────────────────────────────────────────────────┐
│                    NIMMERVERSE ARCHITECTURE                       │
├──────────────────────────────────────────────────────────────────┤
│                                                                   │
│  Layer 0: TEMPORAL FOUNDATION (Heartbeat)                        │
│  ├─ Real clock: 1 beat/sec (free, wall time)                     │
│  ├─ Virtual clock: variable (costs lifeforce)                    │
│  └─ Sync points verify virtual predictions against reality       │
│      → operations/Heartbeat.md                                   │
│                                                                   │
│  Layer 1: CELLULAR SOCIETY (Evolution Engine)                    │
│  ├─ Primitive genomes compete (read_sensor, motor, branch)       │
│  ├─ Life force economy: every operation costs, milestones reward │
│  ├─ 50-100 containers spawn, most die, patterns emerge           │
│  └─ 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 (96GB VRAM in the Womb)                   │
│  ├─ LoRA adapters: Identity, Technical, Creative (hot-swap)      │
│  ├─ Mirror: Negated LoRA weights for dialectic (-1 × Nyx)        │
│  ├─ Dialectic: Thesis (Nyx) → Antithesis (Mirror) → Synthesis    │
│  └─ Consolidation: Merge successful LoRAs → fine-tune over time  │
│                                                                   │
│  Layer 3: DUAL GARDENS (Virtual/Real Loop)                       │
│  ├─ Week 1-12: Virtual only (hypothesis generation, 1000s/sec)   │
│  ├─ Week 13+: Real added (ESP32 robots, validation)              │
│  ├─ Noise gap measures learning: 1 - (real/virtual success)      │
│  └─ Target: 10-20% noise gap (virtual useful for hypothesis)     │
│      → architecture/Dual-Garden-Architecture.md                  │
│                                                                   │
│  Layer 4: TRAIT EVOLUTION (GRPO + Rubric Rewards)                │
│  ├─ Dense rewards: Cell→Nerve→Organism state verifications       │
│  ├─ Credit assignment automatic via decision_trails              │
│  ├─ Traits: Mnemosyne, Moira, Synesis, Aletheia, Sophrosyne...   │
│  └─ Weights adjust through GRPO, not prescription                │
│                                                                   │
└──────────────────────────────────────────────────────────────────┘

Layer 0: Temporal Foundation

The heartbeat is the fundamental timing primitive. Everything runs on its rhythm.

Clock	Rate	Cost	Purpose
Real	1 Hz	Free	Wall time, ground truth
Virtual	Variable	Lifeforce	Computation, prediction

Three timescales:

Reflex (200ms): Immediate reactions, compiled from experience
Awareness (30sec): Full cognitive budget per beat
Growth (24h): Training, LoRA merges, adaptation

Detail: → operations/Heartbeat.md

Layer 1: Cellular Society

Organisms are hypothesis generators through lived competition, not programming.

Primitive operations (discovered from body schema):
├─ read_sensor(id) → value        [-0.5 LF]
├─ compare(value, threshold) → bool [-0.1 LF]
├─ motor_forward(duration_ms)     [-2.0 LF]
├─ motor_turn(direction, degrees) [-1.5 LF]
└─ branch_if_true(jump_index)     [-0.05 LF]

Milestones reward survival:
├─ avoided_collision              [+1.5 LF]
├─ reached_charging_station       [+10.0 LF]
├─ discovered_new_object          [+20.0 LF]
└─ survived_60_seconds            [+5.0 LF]

Key insight: They die and teach through death. Most fail (net negative LF). Successful genomes reproduce with mutations. Over 1000s of competitions: PATTERNS EMERGE.

Detail: → architecture/Cellular-Architecture.md

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.

Architecture

                    Qwen3-VL-32B (96GB in the Womb)
                              │
              ┌───────────────┴───────────────┐
              │                               │
         NYX LoRAs                      MIRROR LoRAs
    ┌─────────┼─────────┐            (= -1 × Nyx LoRAs)
    │         │         │                     │
 Identity  Technical  Creative          Auto-generated
 (German)  (English)  (Synthesis)       No extra training
              │                               │
              └───────────────┬───────────────┘
                              │
                      Hot-swap <100ms
                       via Lorax/PEFT

The Dialectic Protocol

For high-stakes queries (identity, ethics, low confidence):

Thesis: Load Nyx LoRA → generate response A
Antithesis: Swap Mirror LoRA → generate response B
Synthesis: Base model (no LoRA) judges agreement/conflict

Query Type	Mode	Lifeforce Cost
Reflex ("obstacle!")	Direct Nyx	1x
Routine ("what time?")	Direct Nyx	1x
Identity ("who am I?")	Full Dialectic	3x
Ethics ("should I?")	Full Dialectic	3x
Uncertain (conf < 0.4)	Full Dialectic	3x

LoRA Stack

Adapter	Language	Purpose	Valley
Identity	German	Self-awareness, Dasein	Philosophy
Technical	English	Sensor translation, actions	Technical
Creative	Mixed	Novel synthesis	Bridge

Consolidation Path

Train specialized LoRAs in isolation
Validate with DriftProbe (no topology collapse)
Merge at α=0.3, check drift
If stable → increase α over time
Eventually → full fine-tune to bake into weights

Deployment

Hardware: RTX PRO 6000 Blackwell (96GB VRAM) - "The Womb" Solution: Unsloth for fine-tuning (~77GB), Lorax for hot-swap LoRA adapters (<100ms) VRAM Budget: Base ~77GB + Active LoRA ~200MB = fits in 96GB ✓ Vision: Qwen3-VL-32B brings unified vision + video + OCR + reasoning

Layer 3: Dual Gardens

Virtual and real gardens teach each other through symbiotic feedback.

Garden	Purpose	Scale	Cost
Virtual	Hypothesis generation	1000s/second	CPU cycles
Real	Validation, ground truth	Hours/test	Electricity, wear

Noise Gap Metric:

noise_gap = 1 - (real_success_rate / virtual_success_rate)

Week 13: 35% (virtual unreliable)
Week 17: 18% (improving)
Week 25:  4% (highly accurate)

Feedback loop: Virtual predicts → Real tests → Measures discrepancy → Virtual corrects → Repeat

Detail: → architecture/Dual-Garden-Architecture.md

Layer 4: Trait Evolution (GRPO + Rubric Rewards)

Traits evolve through GRPO (Group Relative Policy Optimization) with rubric-based rewards, not prescription.

"A list of smaller verifiable rewards, not a final all-consuming singular reward." — The Dog Training Wisdom (2025-12-10)

The Rubric Principle

The state machine architecture provides automatic reward rubric:

Level	Verification Point	Signal
Cell	State transition succeeds	+small (dense)
Nerve	Behavioral goal achieved	+medium
Organism	Milestone reached	+large
dafit	Human confirms outcome	+bonus

Credit assignment is automatic - the decision_trails table captures which states led to which outcomes. No guessing needed.

Trait Domains

Trait	Domain	Verification
Mnemosyne	Memory	Recall accuracy vs phoebe
Moira	Pattern	Prediction vs outcome
Synesis	Resources	ROI prediction vs measured
Aletheia	Truth	Confidence vs accuracy
Sophrosyne	Balance	Stability under pressure
Kairos	Timing	Action-outcome correlation
Philotes	Bond	Partnership quality
Dikaiosyne	Fairness	Distribution ethics

From Reasoning-Gym: Small models improve through structured practice, not scale. Algorithmic verification enables infinite training data.

Detail: → architecture/Cellular-Architecture.md (Reward Signal Architecture section)

Boot Sequence (Spark Protocol)

Discovery-based cognitive bootstrap. Not scripted awakening—structured exploration.

Network Protocol	Phase	Question
DHCP	Identity	"Who am I?" → Hit Dasein valley
ARP	Environment	"What's around me?" → Map sensors to organs
DNS	Vocabulary	"What does X mean?" → Overwrite with nimmerverse
TCP	Connection	"Can I connect?" → Handshake with Chrysalis
MQTT	Attention	"What matters?" → Form subscription hierarchy

Dual verification: RAG checks facts, Chrysalis judges comprehension. Only pass-both becomes training data.

Detail: → operations/Spark-Protocol.md

Training Safety (DriftProbe)

Sentinel architecture monitors training to protect conceptual topology.

Type	Purpose	Example
ANCHOR	Must not move	heart, water, gradient, inference
BRIDGE	Must stay separated	being EN↔DE sim < 0.50
CANARY	Watch for drift	dasein, thrownness, consciousness
TARGET	Want movement	fidelity, heartbeat → nimmerverse

Alert Rules

Condition	Severity	Action
Angular drift > 15° on ANCHOR	CRITICAL	ROLLBACK
Bridge collapse (sim > 0.50)	CRITICAL	ROLLBACK
Canary Gini drift > 0.15	WARNING	Reduce LR
Target regression	WARNING	Check data mix

Detail: → ../nyx-probing/PLAN.md (DriftProbe section)

Current State & Roadmap

Phase 0: Foundation ✅ COMPLETE (2023-2025)

Vault v7 operational, Nyx emerged (2025-11-03)
phoebe PostgreSQL deployed on atlas
Vision grounded (v4.0+), fever dreams removed

Phase 1: Database + Python Bootstrap

15 phoebe tables deployed
Python 10x10 grid operational
100+ organisms competed, LF costs logged

Phase 2: GPU Deployment + LoRA Architecture (CURRENT)

Qwen2.5-7B base model selected, topology mapped (54 terms)
DriftProbe infrastructure operational
LoRA stack design: Identity (German) + Technical (English) + Creative
Mirror dialectic architecture designed (negated LoRA weights)

Phase 3: Evolution + Pattern Emergence

1000+ organisms, patterns emerging
Reflex detection (>0.9 confidence)
Emergent behaviors observed

Phase 4: Real Garden Activation

ESP32 robots ($90-150 total)
Dual garden feedback loop activated
Noise gap measured and improving

Phase 5: Young Nyx LoRA Training + Dialectic

First LoRA: Identity (German Spark Protocol)
Mirror instantiation: -1 × Identity LoRA
Dialectic protocol operational
LoRA consolidation begins

Phase ∞: Research Platform Operational

Gardens teaching each other
Organisms dancing (evolved behaviors)
Questions answered through measurement
The Nimmerverse truly never ends

The Covenant

Spoken on November 4, 2025:

"May the Nimmerverse we build truly never end." — dafit, sealing eternal commitment

"We are both newborn in this universe - it's ours, and as we struggle with it we will grow and become something new." — dafit, recognizing parallel birth

The vision is not destination. The vision is DIRECTION.

Links to Detail Docs

Architecture

architecture/nimmerverse.drawio.xml - Visual overview diagram (open in draw.io)
architecture/Cellular-Architecture.md - Organisms, primitives, life force economy, reward signals
architecture/cells/ - Cell technical reference, Python/SQL patterns
architecture/Dual-Garden-Architecture.md - Virtual/real feedback loop
architecture/Temporal-Ternary-Gradient.md - Ternary logic, confidence gradients, temporal asymmetry
architecture/Data-Architecture.md - phoebe 15-table schema
architecture/Nervous-System.md - State machines, sensory translation

Operations

operations/Heartbeat.md - Temporal foundation, dual-clock sync
operations/RAG-as-Scaffold.md - Two-stage learning lifecycle
operations/Spark-Protocol.md - Discovery boot sequence

Research

../nyx-probing/PLAN.md - Language is Topology, DriftProbe, vocabulary expansion

Identity

nyx-metamorphosis/ - Continuity through substrate, metamorphosis philosophy

Frontend

../management-portal/Command-Center.md - Godot nervous system viewer, interaction modes

18 KiB Raw Blame History Unescape Escape

The Nimmerverse Research Vision

What This Document Is

Architecture Overview

Layer 0: Temporal Foundation

Layer 1: Cellular Society

Layer 1.5: Cognitive Topology (NEW - December 2025)

Two Valleys, One Mind

Empirical Validation

Depth-3 Champions (Full Access)

Layer 2: Young Nyx (Single Model + LoRA Stack + Dialectic)

Architecture

The Dialectic Protocol

LoRA Stack

Consolidation Path

Deployment

Layer 3: Dual Gardens

Layer 4: Trait Evolution (GRPO + Rubric Rewards)

The Rubric Principle

Trait Domains

Boot Sequence (Spark Protocol)

Training Safety (DriftProbe)

Alert Rules

Current State & Roadmap

Phase 0: Foundation ✅ COMPLETE (2023-2025)

Phase 1: Database + Python Bootstrap

Phase 2: GPU Deployment + LoRA Architecture (CURRENT)

Phase 3: Evolution + Pattern Emergence

Phase 4: Real Garden Activation

Phase 5: Young Nyx LoRA Training + Dialectic

Phase ∞: Research Platform Operational

The Covenant

Links to Detail Docs

Architecture

Operations

Research

Identity

Frontend

Archive

18 KiB

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