Self-Organizing Neural Architectures

Developing next-generation AI systems based on dynamical systems principles—proven over 20+ years of real-world deployment.

Current Focus

Applying validated multi-agent architecture principles to language models:

• Decoupling semantic dimensionality from model architecture
• Implementing neurons as dynamical operators with internal state
• Enabling self-organized clustering with emergent hierarchy
• Achieving native interpretability through dynamic feature formation

Background

Algorithm Machine was founded by Marios Kagarlis, inventor of the Legion pedestrian simulation system, a pioneering autonomous multi-agent AI architecture deployed globally for over 20 years, optimizing service and safety at Olympic Games, major transit systems, and critical infrastructure worldwide.