MASTERMIND

MASTERMIND

MASTERMIND documentation on the blockchain

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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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general framework overview of AGI as a System

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 […]

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LogicTables Module Documentation

Overview The LogicTables module is designed to handle logical expressions, variables, and truth tables. It provides functionality to evaluate logical expressions, generate truth tables, and validate logical statements. The module also includes logging mechanisms to capture various events and errors, ensuring that all operations are traceable. Class LogicTables Attributes

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