MASTERMIND

MASTERMIND

MASTERMIND documentation on the blockchain

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Gödel

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 […]

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aGLM

aGLM, or Autonomous General Learning Model, is designed to operate as a core model for autonomous data parsing and learning from memory in the context of artificial intelligence systems. It’s a pivotal element within a broader system called RAGE (Retrieval Augmented Generative Engine). Key aspects and functionalities of aGLM: Autonomous Learning: aGLM is built to learn autonomously from interactions and data retrievals. It continuously updates its knowledge base, refining its capabilities based on new data […]

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fundamental augmented general intelligence

funAGI workflow fundamental autonomous general intelligence framework

The funAGI system is designed as a modular framework for developing an autonomous general intelligence. The workflow integrates several components and libraries to achieve adaptability, dynamic interaction, continuous optimization, and secure data management. Below is a detailed explanation of the funAGI workflow based on the provided files and documentation. 1. Component Initialization 2. Core AGI Logic 3. User Interaction 4. Reasoning and Logic 5. API and Integration 6. Communication and Interaction 7. Installation and Requirements […]

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