GAMEPLAN.md

SGP-Tribe3 GAMEPLAN (LOCKED)

Core Thesis

The brain is a projection of underlying mathematical structure consistent with the SGP. If we can reverse-engineer brain activity patterns (via TRIBE v2) into geometric SGP representations from text stimuli, we can compare our geometric model's output against LLM neural models on equal footing — both processing text.

Hypothesis H1: An LLM integrated with an SGP Resonance Graph calibrated from TRIBE v2 fMRI data will produce measurably lower hallucination rates and higher cross-domain coherence than the same LLM without SGP architecture.

Hypothesis H2: TRIBE v2 inference will empirically recover the Hickok-Poeppel dual-stream dissociation — ventral nodes (G2, G7, G8) showing significantly higher activation for semantic stimuli, dorsal nodes (G1, G3, G4, G9) for syntactic/structural stimuli.

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Architecture Overview

TEXT INPUT → TRIBE v2 (LLaMA 3.2 embeddings) → fMRI prediction (20,484 vertices)
    ↓
SGP Parcellation (Schaefer-200 → 9 nodes) → SGP Activation Profile
    ↓
Resonance Anchor Ωw → LLM Prompt Weighting → SGP-Guided Output

9 SGP Nodes: G1_broca, G2_wernicke, G3_tpj, G4_pfc, G5_dmn, G6_limbic, G7_sensory, G8_atl, G9_premotor

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Phase 0: Fix Text Inference on CPU (BLOCKING)

Problem: TRIBE v2 loads ALL extractors during model.predict(), even for text-only events. The audio extractor (Wav2Vec-BERT) tries to move to CUDA and crashes with AssertionError: Torch not compiled with CUDA enabled.

Solution: Patch BaseExtractor.device property to return 'cpu' for ALL extractor classes BEFORE calling predict(). The patch must happen inside _run_text_inference() immediately before _run_inference_from_events().

Status: ✅ IMPLEMENTED - Patching added to _run_text_inference()

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Phase 1: Minimal Test Battery (3-5 Texts)

#	Text	Expected Dominant Nodes	Purpose
1	"The cat sat on the mat."	G2_wernicke, G7_sensory	Baseline simple sentence
2	"If P implies Q, and Q implies R, then P implies R."	G4_pfc, G1_broca	Logical structure
3	"She felt the warmth of the sun on her skin as memories of childhood flooded back."	G6_limbic, G5_dmn	Emotional + sensory
4	"The mitochondria is the powerhouse of the cell."	G4_pfc, G7_sensory	Factual/technical
5	"What if the universe is a simulation and we're just characters in someone else's dream?"	G5_dmn, G3_tpj	Self-referential/abstract

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Phase 2: Result Persistence & Analytics

Storage: HF dataset repo Sentient-Field/sgp-tribe3-results

Schema:

{
    "stimulus_id": "uuid",
    "text": "input text",
    "sgp_nodes": {"G1_broca": 0.73, ...},
    "streams": {"dorsal": 0.58, ...},
    "edge_weights": {"AF": 0.45, ...},
    "dominant_hemisphere": "left",
    "inference_time_seconds": 45.2
}

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Phase 3: LLM Integration (OpenRouter Free Tier)

Primary: OpenRouter free tier (openrouter/free router) Fallback: Ollama Mistral-7B local

Prompt construction:

System: You are guided by brain-inspired SGP model.
Activation weights: {node_name}: {value}, ...

User: {input}

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Phase 4: Validation & Comparison

• Coherence: Does SGP-guided output stay more on-topic?
• Differentiation: Do different texts produce different activation profiles?
• Dual-stream: Do semantic vs. logical texts activate different node clusters?

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Phase 5: Scale Up (Post-Validation)

• 50-100 text test battery
• Statistical analysis
• Co-activation matrix
• Scientific article documentation

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Risk Register

Risk	Likelihood	Mitigation
Text inference still hits CUDA error	Medium	Fallback: subprocess with CUDA_VISIBLE_DEVICES=""
TRIBE v2 slow on CPU	High	Accept 30-60s per inference
OpenRouter rate limits	Low	Fallback to Ollama local
HF Space cold starts	Low	Model persists between requests

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Continuation Prompts for AI Agents

To start from Phase 0:

Read /home/student/sgp-tribe3/GAMEPLAN.md. Start with Phase 0: Fix text inference on CPU.
Test with: curl -X POST https://Sentient-Field-sgp-tribe3.hf.space/predict_text -F "text=The cat sat on the mat." -F "stimulus_id=test"

Current Status: Phase 0 patch implemented, awaiting deployment and test.

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Plan Locked

This plan is LOCKED. Any AI agent can pick up from this document at any phase.

Last Updated: April 6, 2026 Project: SGP-Tribe3 - Sentient Generative Principal