We basically build a space/time model of the world, where systems are performing functions in events that take input states and change them into output states such that those events either causally trigger each other or the causal link that the input states to an event means that the event outputting that states is the cause of the current event.

The conceptual AI models operational concepts based on an understanding on how human concepts work, inference and automatic classification using those concepts, and then learning new concepts. The operational side of the digital twin uses functional specifications held elsewhere, which is also true of the operational concepts which use specifications in the form of conceptual definitions.

And the technology takes in RDF graph as data for input, builds the digital twin model from that data with extensive infererence, then expresses itself back out with RDF graph data. (Making https://solidproject.org/ the ideal protocol for us where each pod is a digital-twin of something)