OBJECT - CONCEPT - SYMBOL
I think this is actually the starting point for any theory or practice of true artificial intelligence. Any system or algorithm (set of algorithms) for object detection and the related concept formation must take elemental sensory data that is essentially time and location data for real objects as input and build up a hierarchy of 'objects' by composition. I'm focusing on entropy as the fundamental discriminator for all data (signals). Detectable persistence in time and place together with stability of relationships between data points is my approach. I started this as a technique for natural language understanding, but realized it is fundamental and general to all sensory signals.
It should be mentioned that there is the same topic in Math Logic discipline Model theory [1, 2]. Where we have a) structures b) theories with concepts, relations, constants - primary and defined. And concept grounding may be treated as calculation of concept definition on particular structure.
So the main question may be What kind of structures AGI creates inside and what kind of manipulation (knowledge processing) it is doing?
It seems the main feature of the mind is processing of colored 3D figures, particulaly in motion.