core choice logging and self-improvement readiness Current state To show that mindX is or is not a Gödel machine, we need a single, accurate log of core choices: what was perceived, what options were considered, what was chosen, why, and (when available) outcome. 1. Gödel choice schema and global log 2. Instrument core decision points 3. Ollama-driven self-improvement readiness 4. API and UI (optional) 5. File and dependency summary Area File(s) Change Core directive docs/survive.md […]

funAGI Objective: Develop a comprehensive Autonomous General Intelligence (AGI) system named FundamentalAGI (funAGI). This system integrates various advanced AI components to achieve autonomous general intelligence, leveraging multiple frameworks, real-time data processing, advanced reasoning, and a sophisticated memory system. Design will be modular for dynamic adaptation using modern object oriented programming technique primary in the Python language. Components of funAGI: the big picture Detailed Architecture and Implementation Plan 1. Cognitive Architecture 2. Multi-Modal and Multi-Model Integration […]

Building a rational Autonomous General Learning Model with Retrieval Augmented Generative Engine to create a dynamic learning loop with machine.dreaming for machine.learning as a self-healing architecture. MASTERMIND uses the Autonomous General Learning Model (aGLM) enhanced by the Retrieval Augmented Generative Engine (RAGE) to create a sophisticated AI system capable of intelligent decision-making and dynamic adaptation to real-time data. This combination leverages the strengths of both components to ensure that responses are not only based on […]