Technology & Architecture

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Overview

The Global Forecasting System (GFS) is built on a production-ready technical architecture that combines advanced AI/ML technologies, distributed systems, and real-time data processing capabilities.

System Architecture

Multi-Pass Analysis Pipeline

GFS uses a sophisticated 7-pass analysis pipeline to process dream narratives:

Pass 1: Event Extraction

• Purpose: Extract concrete, real-world events from dream narratives
• Technology: Advanced LLM processing (OpenAI, Google, Anthropic, Theta)
• Output: Structured events with temporal information

Pass 2: Sphere Classification

• Purpose: Classify events into economic, social, or geopolitical spheres
• Method: Multi-class classification with confidence scores
• Output: Categorized events with sphere assignments

Pass 3: Economic Mapping

• Purpose: Map economic events to NAICS industries
• Technology: Industry classification algorithms
• Output: Industry codes and related stock tickers

Pass 4: News Verification

• Purpose: Verify predictions against real-world news
• Data Sources: GDELT, Google Custom Search Engine
• Temporal Windows: 1, 3, 7, 21 days before/after events
• Output: Verification status and evidence links

Pass 5: Similar Dreams Search

• Technology: FAISS vector search with BGE embeddings
• Method: Hybrid representation (Dream + Events)
• Performance: 0.5-2 seconds for search
• Features: Group-based search (2-1000 users)

Pass 6: Causal Reasoning

• Backend: JanusGraph (production) or NetworkX (development)
• Method: Multi-hop causal chain discovery
• Domains: Military, Academic, Regulatory, Economic, Financial
• Performance: <1s cached, ~20-30s discovery (max_hops=3)

Pass 7: Polymarket Betting

• Purpose: Automated betting on prediction markets
• Components: BetExecutor, RiskManager, MarketScanner
• API: 38 endpoints for market interaction
• Storage: PostgreSQL for bet tracking
• Account Integration: Connect your Polymarket accounts for automated asset management
• Features:
  • Automated bet placement based on GFS predictions
  • Risk management and portfolio optimization
  • Real-time market scanning and analysis
  • Account balance tracking
  • Trade history and performance analytics

Technical Stack

Backend Infrastructure

• Framework: FastAPI (Python)
• Database: PostgreSQL (metrics, predictions, bets)
• Graph Database: JanusGraph + ScyllaDB + Elasticsearch (knowledge graphs)
• Vector Search: FAISS/HNSW (similar dreams search)
• Containerization: Docker & Docker Compose

AI/ML Technologies

• LLM Providers:

  • OpenAI (GPT-4, GPT-3.5)
  • Google (Gemini)
  • Anthropic (Claude)
  • Theta EdgeCloud

• Embeddings:

  • BGE embeddings (BAAI/bge-large-en-v1.5)
  • Custom neural networks for dream analysis

• NLP Technologies:

  • PropBank Semantic Role Labeling
  • Named Entity Recognition (NER)
  • Event extraction and classification

Monitoring & Infrastructure

• Monitoring: Prometheus + Grafana
• Search: Elasticsearch
• Caching: Redis (for performance optimization)
• API Gateway: FastAPI with async processing

API Capabilities

Core Analysis Endpoints

• POST /analyze - Full multi-pass analysis (15-25s)
• POST /events - Quick event extraction (Pass 1 only, 3-5s)
• POST /similar - Similar dreams search

Verification Endpoints

• GET /prediction/verify - Prediction verification
• GET /prediction/{dream_id}/verification - Verification with pagination

Financial Data Endpoints

• GET /naics/{code}/tickers - Industry to tickers mapping
• GET /quote/{ticker} - Real-time stock quotes
• GET /history/{ticker} - Historical price data

Clustering Endpoints

• GET /cluster/{cluster_id} - Cluster summary
• GET /clusters/stats - Aggregated statistics
• POST /cluster/{cluster_id}/analyze - Cluster analysis

Fact-Checking Pipeline

Multi-Stage Verification

1. Decomposition: Break down predictions into verifiable claims
2. Hybrid Retrieval: FAISS + BM25F for document search
3. NLI Verification: Natural Language Inference for claim verification
4. Aggregation: Combine verification results
5. Synthesis: Generate comprehensive verification report

Caching

• Global Cache: 12h TTL for verification results
• Performance: Significantly reduces API response times

Performance Metrics

Response Times

• Quick Analysis: 3-5 seconds (Pass 1 only)
• Full Analysis: 15-25 seconds (all 7 passes)
• Similar Dreams: 0.5-2 seconds
• Causal Reasoning: <1s cached, ~20-30s discovery

Scalability

• Concurrent Requests: Handles multiple simultaneous analyses
• Group Support: 2-1000 users per group
• Distributed Processing: Scalable architecture

Data Sources

Real-Time Data

• News: GDELT, Google Custom Search Engine
• Financial: Real-time stock quotes and historical data
• Events: Real-world event databases

Knowledge Bases

• Knowledge Graphs: JanusGraph with multi-domain data
• Vector Databases: FAISS for semantic search
• Research Data: Peer-reviewed publications and studies

Security & Privacy

Data Protection

• Encryption: All data encrypted in transit and at rest
• Access Control: Role-based access control (RBAC)
• Privacy: User data anonymization options

Compliance

• Data Privacy: GDPR-compliant data handling
• Research Ethics: IRB-approved research protocols
• Security Standards: Industry-standard security practices

Integration Capabilities

API Integration

• RESTful API with comprehensive documentation
• Webhook support for real-time notifications
• SDK support for popular programming languages

Third-Party Services

• Prediction Markets: Polymarket integration
  • Account connection and authentication
  • Automated bet placement
  • Asset management and portfolio tracking
  • Real-time market data access
  • Trade execution and monitoring
• Consciousness State Trading: ASRP.Exchange Platform
  • Tokenization of consciousness states
  • Blockchain-based trading (Quantum Resistant Ledger)
  • Neurointerface integration (EEG, fMRI, MEG, fNIRS)
  • AI-powered analysis and valuation
  • Rights and licenses transfer
  • Buyer-seller matching marketplace
• Financial Data: Stock market APIs
• News Sources: GDELT, Google CSE

Development & Deployment

Development Tools

• Version Control: Git-based workflow
• CI/CD: GitHub Actions for automated testing and deployment
• Testing: Comprehensive test suite

Deployment

• Containerization: Docker images for easy deployment
• Orchestration: Docker Compose for local development
• Cloud Ready: Compatible with major cloud providers

Detailed Documentation

For comprehensive technical details, see:

• GFS Comprehensive Analysis - Full technical documentation
• API Documentation - Complete API reference

Related Pages

• Research Overview - Scientific foundation
• For Users - API access and integration
• Publications - Research papers

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