Synthetic Cortex

Synthetic Cortex is an AI architecture that models human brain cortical functions as modular layers, integrating neurochemical processes (hormones and neurotransmitters) into reasoning mechanisms of open-source LLMs. Rather than scaling through massive data volumes, the project demonstrates how human brain principles—emotional decision-making, parallel processing, episodic memory, and context-sensitive reasoning—can be mathematically modeled to create more efficient, interpretable, and capable AI systems. The architecture operates through seven reasoning phases, currently completing phases 1-4, with hallucination rates significantly reduced, energy efficiency substantially improved, and higher performance achieved with lower-parameter models. The project addresses critical issues in current LLMs: the black-box problem, hallucination, centralization barriers, computational costs, and static knowledge limitations. By making advanced AI accessible to smaller institutions without massive GPU requirements, Synthetic Cortex provides efficient, interpretable alternatives to centralized AI systems.