As to the AI plans and progress so far, here's a little primer on what I decided on in a simple, surface level way.
So first I realized meaning can be derived by taking parts of speech in a sentence or phrase and thereby establishing some context and connection between words which is what gives the words meaning by combining them. So I can create a bunch of rules whereby the AI can parse out meanings from sentences it reads in based on parts of speech and the context this forms. Then rules on how it is to respond and how it is to store away facts it gleaned from what it read for future use. So if it is being spoken to and the sentence is a question, it can know it is to answer the question. And the answer can be derived based on a knowledge base it has. So if someone asks it "what color is the car?" and supposing we've already established prior in the conversation what car we are referring to, the AI can determine that it is to answer "the car is [insert color here]" based on rules as to how to answer that type of question. And to know it is white, supposing it's not actually able to look at it presently, it would look up in a file it has made previously on this car to see a list of attributes it recorded previously about that car and find that its color attribute was "white" and so it would be able to pull that from its knowledge database to form the answer. I realized it can keep these files on many topics and thereby have a sort of memory knowledge base with various facts about various things and be able to form sentences using these knowledge databases using rules of sentence structure forming based on parts of speech and word orderings and plug in the appropriate facts into the proper order to form these sentences. Then various misc conversational rules can supplement this like if greeted, greet back with a greeting pulled from this list of potential greetings and it can select one either at random or modified based on facts about its recent experiences. So for example, if somebody's manner of speaking to the robot within the last half hour was characterized as rude or inconsiderate, the robot could set a emotion variable to "frustrated" and if asked in a greeting "how are you?" it could respond "doing okay but a bit frustrated" and if the person asked why are you frustrated, it could say that it became frustrated because somebody spoke in a rude manner to it recently. So it would be equipped with this sort of answer based on the facts of recent experiences. So basically an extensive rule based communications system. Most of how we communicate is rules based on conventions of social etiquette and what is appropriate given a certain set of circumstances. These rules based systems can be added to over time to become more complex, more sophisticated, and more nuanced by adding more and more rules and exceptions to rules. This limitation of course is who wants to spend the time making such a vast rules system? Well for solving that dilemma, I will have the robot be able to code his own rules based on instructions it picks up over time naturally. So if I say hello, and the robot identifies this as a greeting, supposing he is just silent, I can tell him "you are supposed to greet me back if I greet you". He would then add a new rule to his conversation rules list that if greeted, greet that person back. So then he will be able to dynamically form more rules to go by in this way without anybody painstakingly just manually programming them in. We, my family, friends etc would all be regularly verbally instructing the robot on rules of engagement and bringing correction to it which it would always record in the appropriate rules file and have its behavior modified over time that way to become more and more appropriate. It would grow and advance dynamically in this way over time just by interacting with it and instructing it. It could also observe how people dialogue and note itself that when people greet others, the other person greets them back, and based on this observation, it could make a rule for itself to do the same. So learning by observing other's social behavior and emulating it is also a viable method of generating more rules. And supposing it heard someone reply to "how's the weather" someone replied "I don't care, shut up and don't talk to me". The robot lets say records that response and give the same response to me one day. I could tell it that this is rude and inappropriate way to respond to that question. And then I'd tell it a more appropriate way to respond. So in this way I could correct it when needed if it picked up bad habits unknowingly - but this sort of blind bad habit uptake can be prevented as I'll explain a bit later below.
I also realized a ton of facts about things must be hard coded manually just to give it a baseline level of knowledge to even begin to make connections to things and start to "get it" on things when interacting with people. So there is a up front knowledge investment capital required to get it going, but then from there, it will be able to "learn" and that capital then grows interest exponentially. Additionally, rather than only gaining more facts and relationships and rules purely through direct conversation with others, it will also be able to "learn" by reading books or watching youtube videos or reading articles and forums. In this way, it can vastly expand on its knowledge and this will equip it to be more capable conversationally. I also think some primitive reasoning skills will begin to emerge after it gets enough rules established particularly if I can also teach him some reasoning basics by way of reasoning rules and he can add to these more rules on effective reasoning tactics. Ideally, he'll be reading multiple books and articles simultaneously and learning 24/7 to really fast track his development speed.
