A lot of people ask me what is an Ontic Processor, a term we use at Noonean Cybernetics to describe one of our supporting components. I've even had people get huffy and puffy "That Doesn't Exist!". Well yes it does we use it every day.
No it's not a Pregel graph matrix processor or Deep Graph Transition matrix. Those typically require multiple pass point to point traversal.
Instead the Ontic Processor is a bit like a neural network in reverse. The Ontic processor maps terms and associations like language item -- Role -- Connection Role -- Other Item
The way it works is a bit closer to what happens to a human brain when you stimulate it with an electrode. You stimulate several nodes, and then look at what result nodes get excited. It is a complicated dance through BILLIONS of Neurons and connections that is a bit like chaos theory, utterly unpredictable.
Getting the data mapped into an ontic structure is a bit challenging. It requires a bit of step by step learning, and asking if associations and understandings are correct. But it grows ever more savvy over time.
So perhaps we might say it is not so much a database gobbler, a big data cruncher, or a document parser. Rather, it builds interactively, learning and correcting. Once some sufficient linguistic structure (although it encodes knowledge relationships so it is so much more than NLP) then it can begin digesting more information more quickly, and again continuous testing of relationships through questioning.
When we develop cybernetic systems we have typically large processors to handle senses like vision and audition, and another very large scale neural network configured as a Neural Cube or ANCPHSELAC ("ancephelac") (Advanced Neo-Cognitron with Pribram Holographic structures and Edelman Live Association and Competition). This includes a consciousness processing function as well which is gathering and weighting and responding to inputs while "thinking" about them. So to better understand what is going on, the information is passed to the Ontic Processor, and then much more specificity and more possibilities about the language and knowledge is returned, specifically relationships, part composition and decomposition, roles in relationships, and other terms which are not originally in the language. For example, if someone says "Had a problem with the car's rotation" it would get information back that the tires are rotated, rotate, and so does the engine. So it might reply "You rotated your tires or do you mean a problem with the engine" This is much more interesting linguistic interaction rather than the "DO YOU WANT TO DANCE. I CAN DANCE" nonsense. One can only wonder what a Boston Dynamics Language processor will sound like "MOVE AND I KILL KILL YOU". Scary.
So the Ontic processor is a necessary advanced way to retain knowledge but NOT memory. But it can be a supporting classifier for memory and item IDs in memory. That work still to come.
