tangentencode

Tangentencode is a conceptual framework or perhaps a theoretical programming paradigm that explores the idea of representing data or computational processes through their tangential relationships. Instead of directly encoding information, tangentencode focuses on the connections and interactions between different elements. This could involve mapping data points to vectors that represent their proximity or influence on other data points, or describing algorithms by the sequence of transformations applied to their inputs, rather than the inputs or outputs themselves.

The core principle of tangentencode is that understanding the "way" something relates to other things is as important, or even more important, than understanding the thing in isolation. This approach might find applications in areas like complex systems analysis, where the emergent behavior of a system is dictated by the interactions of its components. It could also be relevant in machine learning, particularly in graph-based learning or attention mechanisms, where the relationships between different parts of the data are crucial for prediction or understanding. The term suggests a departure from direct, linear encoding towards a more diffuse, relational representation. Further development in this area would likely involve defining formal languages and computational models to implement and test these tangential encoding strategies.