GENESIS - Cognitive Computing Platform - World's First Multi-Technology Cognitive Computing Platform
Production Ready
100%

Semantic tokenizer complete, HDC system in research phase

GENESIS - Cognitive Computing Platform

World's First Multi-Technology Cognitive Computing Platform

Project Overview

Breakthrough innovations in semantic-guided tokenization, quantum-enhanced HDC systems, and neural-symbolic integration. Combines multiple cutting-edge technologies for zero-hallucination AI with real-time knowledge transfer capabilities.

Key Metrics

20,000
Vector Dimensions
Hyperdimensional vector space
8.8GB
HDC Lexicon
Semantic knowledge base
23+ GFLOPS
Performance
Computational throughput
<100MB
Memory Usage
Runtime memory efficiency

Technology Stack

Julia Rust Neural-Symbolic AI Quantum Computing

Key Features

  • World's first semantic-aware BPE tokenizer with breakthrough architecture
  • S-P-A framework: Subject-Predicate-Attribute semantic roles
  • 20,000-dimensional hypervectors with quantum enhancement concepts
  • Zero-hallucination framework through symbolic reasoning constraints
  • Real-time knowledge transfer during training (71.6% complete)
  • Local deployment optimized for consumer hardware (<100MB memory)
  • Cross-lingual native understanding (German/English/Romanian)
  • 2,088 protected German legal terms preserved during training
  • Neural-symbolic integration for explainable AI decisions

Project Timeline

Started: 2025-06 Last Updated: 2025-11-09

Semantic Tokenizer Development

2025-06 - 2025-08

World's first semantic-aware BPE tokenizer

Julia Performance Optimization

2025-07

Achieved 23+ GFLOPS throughput

HDC System Architecture

2025-08

20,000-dimensional hypervector design

Quantum Enhancement Framework

2025-09

Quantum-inspired optimization techniques

Neural-Symbolic Integration

2025-10

Hybrid reasoning system development

Live Training Dashboard

2025-11

Real-time metrics at 71.6% progress (2,088 terms)

Technical Details

Tokenizer:
Semantic-guided BPE with S-P-A framework
Languages:
Julia (performance), Rust (system components)
Hdc System:
20,000-dimensional hypervectors with quantum enhancement
Data Size:
8.8GB lexicon integration (5.0GB + 3.8GB)
Performance:
23+ GFLOPS on AMD Ryzen systems
Memory:
<100MB runtime with enterprise pooling
Specialization:
German legal terminology + cross-lingual coherence
Deployment:
Local-first architecture for consumer hardware