FalahMsi/neurocode: A Cognitive Framework for Simulating Neural Memory in Code Comprehension

NeuroCode is an open intellectual initiative designed to enhance machine comprehension of coding by mimicking the human brain. It introduces a cognitive framework that simulates a neural memory system through “code neurons,” which are lightweight components extracted from source code, documentation, and usage patterns. These code neurons operate selectively: they activate only when relevant, are forgotten when unused, and organize data based on contextual cues—resembling human cognitive processes like contextual recall and associative memory. The initiative aims to lessen reliance on large language models (LLMs) by enabling machines to emulate selective memory recall similar to human thought processes. The project provides resources such as a full concept document, modular analyzers, and example components for context-aware recall. Although development is paused due to personal limitations, contributions from interested developers or researchers are encouraged.

Source link