Extrapolating a Hierarchy of Building Block Systems Towards Future Neural Network Organisms

摘要

It is possible to predict future life forms? In this paper it is argued that the answer to this question may well be positive. As a basis for predictions a rationale is used that is derived from historical data, e.g. from a hierarchical classification that ranks all building block systems, that have evolved so far. This classification is based on specific emergent properties that allow stepwise transitions, from low level building blocks to higher level ones. This paper shows how this hierarchy can be used for predicting future life forms.