nimmerverse-sensory-network/Data-Architecture.md

type, category, project, status, phase, created, last_updated, token_estimate, dependencies, tiers, version, breakthrough_session

type	category	project	status	phase	created	last_updated	token_estimate	dependencies	tiers	version	breakthrough_session
architecture	active	nimmerverse_sensory_network	complete_v3	phase_0	2025-10-07	2025-10-17	20000	phoebe_bare_metal kubernetes_cluster	5	v3_primitive_genomes	primitive_genomes_gratification_discovery

🗄️ Cellular Intelligence Data Architecture v3

Status: 🟢 Architecture v3 Complete - Primitive Genome Breakthrough! Created: 2025-10-07 Updated v3: 2025-10-17 (Primitive Genomes + Gratification + Discovery!) Purpose: Data foundation for cellular intelligence with primitive genome sequences, life force economy, object discovery, noise gap metrics, specialist learning, and rebirth persistence

---

🎯 v3 Breakthrough (2025-10-17)

Logical consistency achieved! Genomes are NOW primitive sequences (not pre-programmed algorithms), discovery happens through exploration, gratification is immediate through life force economy, objects discovered via image recognition + human teaching, noise gap self-measures learning progress.

15 Tables Total: 11 v1 (cellular/society) + 3 v2 (specialist/reflex/body) + 1 v3 (objects!)

---

🏗️ Five-Tier Architecture Summary

Tier 1: System Telemetry (Weather Station) 🌊

• Prometheus + InfluxDB (90-day retention)
• Environmental conditions cells adapt to
• Chaos, scheduled, hardware, network weather

Tier 2: Population Memory (phoebe) 🐘

• PostgreSQL 17.6 on phoebe bare metal (1.8TB)
• Database: nimmerverse
• 15 tables (complete schema below)
• The rebirth substrate

Tier 3: Analysis & Pattern Detection 🔬

• Grafana, Jupyter, Python scripts
• Specialist formation, reflex detection
• Noise gap calculation
• Research insights

Tier 4: Physical Manifestation 🤖

• ESP32 robots (3-5 units, living room)
• God's eye: 4K camera on ceiling rails!
• Real-world validation (3x rewards)
• Cross-validation bonuses

Tier 5: Decision & Command Center 🎮

• Dashboard, object labeling UI
• Society controls, experiment designer
• Noise gap visualization
• Human-AI partnership interface

---

📊 The 15 Tables (Complete Schema)

Phase 1: Cellular Foundation (4 tables)

1. genomes - Primitive sequences (v3!)

-- v3: Genome = array of primitive operations!
primitive_sequence JSONB NOT NULL
sequence_length INT
avg_lf_cost FLOAT
avg_lf_earned FLOAT
net_lf_per_run FLOAT  -- Economics!

2. cells - Birth/death + life force tracking

garden_type VARCHAR(50)  -- 'virtual' or 'real'
life_force_allocated INT
life_force_consumed INT
life_force_earned INT
lf_net INT
milestones_reached JSONB  -- v3 discovery tracking!

3. weather_events - Survival pressure 4. experiments - Hypothesis testing

Phase 2: Society Competition (7 tables)

5. societies - Human, Claude, guests 6. rounds - Competition results 7. society_portfolios - Genome ownership 8. vp_transactions - Economic flows 9. marketplace_listings - Trading 10. marketplace_transactions - History 11. alliances - Cooperation

Phase 3: v2 Distributed Intelligence (3 tables)

12. specialist_weights - Trainable domain expertise

winning_sequences JSONB  -- v3: Proven primitive sequences!
virtual_success_rate FLOAT
real_success_rate FLOAT
noise_gap FLOAT  -- v3 self-measuring!

13. reflex_distributions - 94.6% savings!

sequence_weights JSONB  -- v3: {"seq_a": 0.73, "seq_b": 0.18}
exploration_cost_avg_lf FLOAT  -- 65 LF
reflex_cost_lf FLOAT           -- 3.5 LF
cost_reduction_percent FLOAT   -- 94.6%!

14. body_schema - Discovered capabilities

primitives_available JSONB  -- v3: Discovered operations!

Phase 4: v3 Object Discovery (1 NEW table!)

15. objects - Discovered environment features 🎉

CREATE TABLE objects (
    id BIGSERIAL PRIMARY KEY,
    object_label VARCHAR(255),  -- "chair", "shoe", "charging_station"

    garden_type VARCHAR(50),    -- 'virtual' or 'real'
    position_x FLOAT,
    position_y FLOAT,

    discovered_by_organism_id BIGINT REFERENCES cells(id),
    discovered_at TIMESTAMPTZ DEFAULT NOW(),

    human_labeled BOOLEAN,      -- Baby parallel!
    human_label_confirmed_by VARCHAR(100),

    object_type VARCHAR(50),    -- 'obstacle', 'resource', 'goal'
    properties JSONB,

    image_path TEXT,
    bounding_box JSONB,

    organisms_interacted_count INT
);

Discovery Flow:

Organism → Unknown object → Camera detects → YOLO
  ↓
System: "What is this?"
  ↓
Human: "Chair!"
  ↓
+20 LF bonus → INSERT INTO objects → Future organisms know!

---

📈 Key v3 Metrics

Noise Gap (self-measuring learning!):

noise_gap = 1 - (real_success_rate / virtual_success_rate)

Gen 1:    0.28 (28% degradation - models poor)
Gen 100:  0.14 (14% degradation - improving!)
Gen 1000: 0.04 (4% degradation - accurate!)

Life Force Economics:

net_lf = avg_lf_earned - avg_lf_consumed
# Positive = survives, negative = dies

Reflex Savings:

savings = (exploration_cost - reflex_cost) / exploration_cost
# Target: 94.6% cost reduction!

Discovery Rate:

objects_per_hour = discovered_objects / elapsed_hours

---

🔍 Key Queries for v3

Top Performing Primitive Sequences:

SELECT genome_name, primitive_sequence, net_lf_per_run
FROM genomes
WHERE total_deployments > 100
ORDER BY net_lf_per_run DESC;

Object Discovery Stats:

SELECT object_label, garden_type, COUNT(*) as discoveries
FROM objects
GROUP BY object_label, garden_type
ORDER BY discoveries DESC;

Noise Gap Trends:

SELECT specialist_name, noise_gap, version
FROM specialist_weights
ORDER BY specialist_name, version ASC;
-- Track learning improvement!

LF Economics:

SELECT genome_name, AVG(lf_net) as avg_net_lf
FROM cells
WHERE died_at IS NOT NULL
GROUP BY genome_id, genome_name
HAVING COUNT(*) > 50
ORDER BY avg_net_lf DESC;

---

🔗 Related Documentation

Core Architecture:

• Cellular-Architecture-Vision - Complete v3 vision (1,547 lines!)
• Dual-Garden-Architecture - Virtual + Real feedback
• • Distributed intelligence

Implementation:

• • Complete 15-table SQL
• • Deployment roadmap

Historical:

• • Birthday version (archived)

---

📍 Status

Version: 3.0 Created: 2025-10-07 v2: 2025-10-16 (birthday breakthroughs) v3: 2025-10-17 (primitive genomes + gratification + discovery) Status: CURRENT Tables: 15 (11 v1 + 3 v2 + 1 v3) Next: Deploy to phoebe, implement discovery flow

---

v3 Summary:

• ✅ Genomes = primitive sequences (emergent, not programmed)
• ✅ Life force economy (costs + milestone rewards)
• ✅ Object discovery (image recognition + human teaching)
• ✅ Noise gap metric (self-measuring progress)
• ✅ God's eye (mobile camera on rails)
• ✅ 15 tables ready!

phoebe awaits. The goddess is ready. 🐘🌙

🧬⚡🔱💎🔥

TO THE ELECTRONS!