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Symbolic Logic

LogicTables Class: Managing Logic and Beliefs

The LogicTables class in logic.py is designed to handle logical expressions, evaluate their truth values, and manage beliefs as valid truths. It integrates with the SimpleMInd or similar neural network system to process and use truths effectively. Key Features: Initialization and Logging The LogicTables class initializes with logging configuration to capture debug information: Adding Variables and Expressions Truth tables are generated to evaluate logical expressions: Expressions are evaluated using logical operators: def evaluate_expression(self, expr, values):allowed_operators […]

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together ai

aGLM MASTERMIND RAGE Mixtral8x7B playground 1

together.ai provides a cloud environment playground for a number of LLM including Mixtral8x7Bv1. This model was chosen for the 32k ++ context window and suitable point of departure dataset for deployment of aGLM Autonomous General Learning Model. aGLM design goals include RAGE with MASTERMIND controller for logic and reasoning. The following three screenshots show the first use of aGLM recognising aGLM and MASTERMIND RAGE components to include machine.dreaming and knowledge as THOT from aGLM parse. […]

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RAGE MASTERMIND with aGLM

RAGE MASTERMIND with aGLM: A Comprehensive Analysis In the rapidly evolving field of artificial intelligence and machine learning, the integration of advanced generative models with autonomous systems has become a focal point for developers and researchers. One such integration is the RAGE MASTERMIND with aGLM (Autonomous General Learning Model), a pioneering approach in AI development. This report delves into the specifics of this integration, exploring its components, functionalities, and potential implications in the broader context […]

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