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MASELKO-95 edited this page Nov 28, 2025 · 1 revision

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Welcome to the Collatz AI Research System documentation!

🎯 Quick Navigation

πŸ“Š Project Overview

This project combines AI-guided pattern recognition with parallel brute-force search to investigate the Collatz Conjecture.

Key Statistics

Metric Value
Training Steps 100,000+
Numbers Analyzed 54,000,000+
Model Accuracy 99.97% (stopping time)
GPU Utilization 90%
CPU Utilization 85%

Latest Results

  • βœ… No non-trivial cycles found in range [2^68, 2^68 + 54M]
  • πŸ“ˆ Stopping time prediction: 0.0003 log-space error
  • 🎯 Sequence accuracy: ~70% per-step prediction

πŸš€ Quick Start

git clone https://github.com/MASELKO-95/Collatz-AI-Research-System.git
cd Collatz-AI-Research-System
chmod +x run.sh
./run.sh

πŸ“š Documentation Structure

This wiki is organized into the following sections:

  1. Getting Started - Setup, installation, and first run
  2. Architecture - Technical details of the AI model
  3. Training - How to train and customize
  4. Analysis - Understanding results and metrics
  5. Advanced - Distributed training, optimization tips
  6. Contributing - How to help improve the project

🀝 Contributing

We welcome contributions! See the Contributing Guide for details.

πŸ“§ Support


Last updated: 2025-11-28

Home

Welcome to the Collatz AI Research System documentation!

🎯 Quick Navigation

πŸ“Š Project Overview

This project combines AI-guided pattern recognition with parallel brute-force search to investigate the Collatz Conjecture.

Key Statistics

Metric Value
Training Steps 100,000+
Numbers Analyzed 54,000,000+
Model Accuracy 99.97% (stopping time)
GPU Utilization 90%
CPU Utilization 85%

Latest Results

  • βœ… No non-trivial cycles found in range [2^68, 2^68 + 54M]
  • πŸ“ˆ Stopping time prediction: 0.0003 log-space error
  • 🎯 Sequence accuracy: ~70% per-step prediction

πŸš€ Quick Start

git clone https://github.com/MASELKO-95/Collatz-AI-Research-System.git
cd Collatz-AI-Research-System
chmod +x run.sh
./run.sh

πŸ“š Documentation Structure

This wiki is organized into the following sections:

  1. Getting Started - Setup, installation, and first run
  2. Architecture - Technical details of the AI model
  3. Training - How to train and customize
  4. Analysis - Understanding results and metrics
  5. Advanced - Distributed training, optimization tips
  6. Contributing - How to help improve the project

🀝 Contributing

We welcome contributions! See the Contributing Guide for details.

πŸ“§ Support


Last updated: 2025-11-28