Professor Codephreak

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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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The mispriced network — rotating from Bitcoin into undervalued Polkadot and Moonbeam

The Mispriced Network: Why I Think Polkadot (DOT) and Moonbeam (GLMR) Are Undervalued Against Their Own Utility

A thesis, argued from public data: Polkadot shipped a hard supply cap, a US spot ETF (TDOT), and a finished scaling program in one year — and Moonbeam (GLMR) handles a fifth of Polkadot’s activity for a ~$15M market cap. Why I think DOT and GLMR are mispriced against their own utility, and how to access both from Kraken in Canadian dollars.

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mindX as a protocol — the catalogue, observability as an append-only protocol

A single append-only event stream mirrors every write mindX makes, turning observability into a replayable, optimizable substrate.

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