Building something wild: an AGI Detector that could spot the first signs of artificial general intelligence emerging. Developed using the SPARC framework via sparc CLI by Reuven Cohen.
A real-time monitoring system to detect early signs of emerging artificial general intelligence through various indicators and patterns across the AI landscape.
- Real-time Monitoring: Track AI breakthroughs across major research labs
- Performance Analysis: Auto-detection of unexplained AI performance jumps
- Software Surveillance: Track unattributed software releases that seem too advanced
- Social Pattern Analysis: Monitor social media patterns for signs of AGI influence
- Alert System: Multi-indicator warning system for potential AGI emergence
Currently in early development phase. Not live yet.
- Next.js 14 + React
- TypeScript
- Prisma ORM
- TailwindCSS
- Web Crawling Infrastructure
- LLM Integration
- Clone the repository:
git clone https://github.com/bencium/agi-detector.git
cd agi-detector- Install dependencies:
npm install- Set up environment variables:
cp .env.example .env.localEdit .env.local with your API keys and configuration.
- Set up the database:
npx prisma generate
npx prisma db push- Run the development server:
npm run devOpen http://localhost:3000 to view the application.
Run the test suite:
npm testWe welcome contributions! Please see our Contributing Guidelines for details.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
Bence Csernak
- Website: bencium.io
- GitHub: @bencium
- Reuven Cohen for the SPARC framework
- All contributors and supporters of this project
Note: This project is in active development. Features and documentation will be updated regularly.