ezAGI fundamental Augmented General Intelligence draw_conclusion(self) method The draw_conclusion method is designed to synthesize a logical conclusion from a set of premises, validate this conclusion, and then save the input/response sequence to a short-term memory storage. This function is a critical component in the context of easy Augmented General Intelligence (AGI) system, as it demonstrates the ability to process information, generate responses, validate outputs, and maintain a record of interactions for future reference and learning. […]

putting the fun into a fundamental augmented general intelligence framework as funAGI funAGI is a development branch of easyAGI. easyAGI was not being easy and SimpleMind neural network was proving to not be simple. For that reason is was necessary to remove reasoning.py and take easyAGI back to its roots of BDI Socratic Reasoning from belief, desire and intention. So this back to basics release should be taken as a verbose logging audit of SocraticReasoning […]

Overview This document provides a comprehensive general explanation of an Augmented General Intelligence (AGI) system framework integrating advanced cognitive architecture, neural networks, natural language processing, multi-modal sensory integration, agent-based architecture with swarm intelligence, retrieval augmented generative engines, continuous learning mechanisms, ethical considerations, and adaptive and scalable frameworks. The system is designed to process input data, generate responses, capture and process visual frames, train neural networks, engage in continuous learning, make ethical decisions, and adapt to […]