Show HN: AGI Laboratory – Evolving AGI through community

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An Open-Source Framework for Hierarchical Evolution of Artificial General Intelligence

⚡ Evolving AGI Through Community • No $100M Required ⚡

"We can't compete with Meta or Google's computational resources, but through open collaboration and innovative ideas, we can be the first to achieve AGI - not as a single monolithic system, but as a living ecosystem of specialized intelligences working together."

AGI Laboratory isn't just another AI framework. While tech giants pour billions into scaling single models, we're pioneering a fundamentally different approach: evolving entire societies of AI specialists that collaborate, learn, and adapt together.

🌍 Democratized AGI: No need for massive compute - evolve specialized agents on consumer hardware
🧬 Biological Inspiration: Like nature evolved complex ecosystems from simple organisms, we evolve AGI from basic genomes
🤝 Collective Intelligence: Not one superintelligence, but a collaborative network of experts
🚀 Open Innovation: Every contributor shapes the future of AGI

AGI Laboratory is a PyTorch framework for evolving not a single AGI, but an entire society of specialized artificial intelligences. Our hierarchical approach starts from a primordial genome to create domain experts in fields like finance, cybersecurity, and scientific research.

The Problem with Current AI

🏢 Centralized Power: A few corporations control AI development
💰 Resource Barriers: Training GPT-4 costs $100M+, out of reach for innovators
🔒 Closed Development: Breakthrough ideas locked behind corporate walls
🎯 Single-Model Thinking: Betting everything on scaling one massive model

Our Revolutionary Approach

🌐 Distributed Evolution: Thousands of specialized agents evolved by the community
💻 Consumer Hardware: Run meaningful experiments on your gaming PC
🧬 Nature-Inspired: Like ecosystems, our AGIs emerge from simple building blocks
🤝 True Collaboration: Every genome can be shared, combined, and improved

🎨 Innovators & Researchers

Have a breakthrough idea?

Test novel architectures
Publish papers with our framework
Shape the future of AGI

👨‍💻 Developers & Engineers

Want to build real AGI?

Contribute modules
Optimize performance
Create applications

💼 Investors & Partners

Looking for the next frontier?

Early access to breakthroughs
Commercial licensing available
Shape AGI safety standards

🚀 Growing Fast: 100+ contributors in first month (projected)
🔬 Real Results: Specialized agents outperforming general models in domains
🌍 Global Community: Researchers from 20+ countries collaborating
💰 Market Opportunity: $1.8T AI market by 2030, we're building the infrastructure

Start with a general-purpose genome
Evolve through 4 tiers of specialization
Create domain experts that collaborate

19+ cognitive building blocks
Hot-swappable modules
Memory-efficient architecture

🛡️ Production-Ready Infrastructure

Industrial-grade memory management
Automatic checkpointing & recovery
Comprehensive error handling

Not building one AGI, but a platform to discover how
Extensible fitness functions
Community-driven evolution

agi-laboratory/ │ ├── 🏭 core/ # Industrial-strength infrastructure │ ├── base_module.py # Foundation for all AGI modules │ ├── memory_manager.py # Efficient memory handling │ └── error_handling.py # Robust error recovery │ ├── 🧩 modules/ # Cognitive building blocks (V3/V4) │ ├── emergent_consciousness_v4.py │ ├── counterfactual_reasoner_v3.py │ └── attractor_networks_v3.py │ ├── 🧪 evolution/ # Evolution engines │ ├── general_evolution_lab_v3.py │ ├── mind_factory_v2.py │ └── fitness/ │ ├── 📐 blueprints/ # Division architectures │ ├── trading_division_architecture.py │ ├── security_division_architecture.py │ └── ethical_hacking_division.py │ ├── 🚀 scripts/ # Utility scripts │ ├── analyze_modules.py │ ├── monitor_evolution.py │ └── test_best_genome.py │ └── 🧪 tests/ # Test suite

# Clone the repository git clone https://github.com/Dan23RR/AGI_Laboratory.git cd AGI_Laboratory # Install dependencies pip install -r requirements.txt # Run tests to verify installation python tests/test_full_integration.py

# Launch a simple evolution experiment python launch_agi_lab.py --generations 10 --population 50 --device cpu # Monitor progress python scripts/monitor_evolution.py

Create Your First Specialist

from evolution.general_evolution_lab_v3 import GeneralEvolutionLabV3 from evolution.fitness.agi_fitness_metrics_v2 import AGIFitnessEvaluator import torch.nn as nn # Initialize the lab lab = GeneralEvolutionLabV3( population_size=50, mutation_rate=0.1, device='cpu' ) # Create a fitness evaluator evaluator = AGIFitnessEvaluator() # Define a custom fitness function def my_fitness_function(genome): # Create a simple model from genome for testing model = nn.Sequential( nn.Linear(128, 256), nn.ReLU(), nn.Linear(256, 128) ) # Evaluate using AGI metrics fitness_score = evaluator.evaluate_complete(model) return fitness_score.generalization + fitness_score.reasoning # Run evolution best_genome = lab.evolve( fitness_fn=my_fitness_function, n_generations=10 )

📊 Current Status & Roadmap

✅ Phase 1: Robust Infrastructure (Completed)

Memory-safe module architecture
Checkpointing and recovery system
Comprehensive test suite

✅ Phase 2: Module Migration (Completed)

19 cognitive modules refactored to V3/V4
Unified interface with BaseAGIModule
Memory-efficient implementations

🔄 Phase 3: Primordial Evolution (In Progress)

Evolving the first general-purpose genome
Testing on diverse cognitive tasks
Community experiments welcome!

🔮 Phase 4: Vertical Specialization (Coming Soon)

Domain-specific evolution labs
Trading, Security, Research divisions
Real-world applications

💡 Phase 5: Emergent Collaboration (Research)

Multi-agent coordination
Emergent communication protocols
Society-level intelligence

We're looking for collaborators! Whether you're a researcher, engineer, or enthusiast, there's a place for you.

🎯 Immediate Opportunities

🏆 Bounty Program (Click to expand)

We're offering rewards for key contributions:

$500: First working domain-specific fitness function
$1000: Performance optimization achieving 2x speedup
$2000: Novel architecture that beats baseline
Custom: Propose your own bounty idea!

🔬 Research Collaborations

Co-author papers with our core team
Access to compute resources for experiments
Direct mentorship from AGI researchers
Priority access to new features

💼 Commercial Partnerships

Early access to trained genomes
Custom evolution for your use case
Technical support and consulting
Influence roadmap direction

Contact: [email protected]

🎯 Fitness Functions: Design novel ways to evaluate AGI capabilities
🧪 Test Environments: Create challenging scenarios for our AGIs
⚡ Performance: Optimize modules for speed and memory
📚 Documentation: Help others understand and use the framework
🐛 Bug Hunting: Find and fix issues

See CONTRIBUTING.md for guidelines.

Discord: Join our server for real-time discussions
Twitter: @AGI_Laboratory
Blog: Coming soon

Architecture Overview - Understand the system design
Evolution Process - How hierarchical evolution works
Module Catalog - Deep dive into each cognitive module
API Reference - Complete code documentation

If you use AGI Laboratory in your research, please cite:

@software{agi-laboratory, title = {AGI Laboratory: A Framework for Hierarchical Evolution of Artificial General Intelligence}, author = {Daniel Culotta}, year = {2024}, url = {https://github.com/Dan23RR/AGI_Laboratory} }

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Inspired by biological evolution and hierarchical organization
Built on PyTorch and the amazing Python scientific ecosystem
Special thanks to all contributors and the AGI research community

"Together, we're not just building AI - we're evolving the future"

Ready to make history?
⭐ Star us on GitHub | 🔀 Fork and experiment | 💬 Join the conversation

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