What mean to AI to understand?

 What mean to AI to understand?

What mean to understand anyway? We can do many things. And we might not understand them. When we are trying to think about the question of what means understanding? We are facing an ultimate question do we still understand anything? The fact is that I can put seven years old child to read the text about quantum physics and that child might read those texts pretty well. But does that child understand those words? The fact is that I can also use the Google text-to-speech application to make that thing. And this application will make its job well. 

The AI can make many things and if that application doesn't know about things like the mark of the sum or something like that. The programmer needs to store the characters of those things on the computer. The mark of the sum will store in the database, and then there will make the text that is connected to that mark. So the sigma-mark will trigger the words that are connected to that mark. 

1) To know means: That a character knows what to do in certain situations

2) Understanding means: To realize why actors must do things in a certain way.

When we are making the robot do something it makes things what we programmed in it. If we want to make a tennis robot that plays tennis with us, we might make a robot that hits the ball. The robot might have gesture control.

If the ball is coming to the robot it will hit it. Then robot must have some algorithms for how it aims at that ball. If the referee will give the pass to the robot, it must know the gesture and then make the pass. Or movement series what makes it pass. The robot must calculate many things like the right hit point and power. But then it might have one problem does it understand anything? 

The pseudo-understanding is that the AI can give pre-programmed answers to certain questions. 

It knows how to react to the ball. And simple gestures that are making the person who sits on the chair.  But could that robot play tennis in a real match? Does it separate the referee from the audience that might show similar gestures? The robot must "know" that it should not follow any other than the referee's marks. So the robot knows how to punch a ball. 

The ball acts as a trigger that activates a certain series of movements. The robot might have orders where the punch must and where the ball should not go. The robot would not strike outside the field, because it's programmed in there. And if somebody asks about why the robot doesn't hit the ball outside the field area, it can answer: "that's dangerous". 

If the programmer is put that answer to robot's computer. Or it might have an answer "that's prohibited" whenever the person asks it to make something that is not programmed in its memory. If somebody asks a robot to punch a ball to humans or vehicles robot might say "it's prohibited" and make a report to its operators. 

The reflex robot recognizes that some action is filling the notes that are stored in the database. After that, the action triggers the database. And then that database begins the response to that action. 

Those actions are programmed in the program of the robot's programs by programmers. The robot does all the time same things. There is a series of triggers that are activated by certain actions. So that robot has a reflex. A certain action activates certain types of reactions. 

The reflex automation is simple to make. When somebody says "good morning" to the computer, it might answer by saying "good morning". And then that computer might have a voice or image scanner that connects a certain workspace to it. If the computer uses an infrared camera or ultrasound-based system. It can also recognize a person. Even if that user has a beard or is in flu. The idea of those deeper-than-surface systems is to benefit the static components of the human body. 

Of course, the system can ask the person to identify self. The command that the operator gives for access to the workspaces. Might be "I'm Eric, open my workspace". In the place of that name is the operator's name. That means the system can also recognize if somebody tries to play as that operator. The system recognizes the face but asks the name of the operator. That uncovers if the person tries to use some other user's accounts. This is one version of artificial intelligence called "reflex automation". 

The thing is that the machine has some kind of model in its memory. When some action fits some models. That thing activates certain actions in the system. This type of system is effective. Artificial intelligence-controlled robots might make many things like activating traffic lights or bringing tea or coffee to certain persons. They know how to respond to some kind of command or action. But those computer programs don't know why that response is given. 

A robot or computer program has a series of reactions to how to react to something. And if something that is outside its databases is asked robot might say "I cannot do that thing". Or it can say that it transmits the problem to the system supervisor who is making an algorithm for that thing. And the time for machine learning starts to dawn. 

 What mean that AI understand?

Understanding is the answer to the question "why"? So that means that we should know how to make something. And then we should know why we should do things exactly some way. 

When we are turning our car to somewhere. We must follow certain rules. But then we must realize that those rules are made. That also other people who are outside our vehicle know what we are going to do. 

When we are researching AI we are facing the question. Does the computer understand things what it does? The thing is that understanding is something that even humans don't understand. When somebody asks "do you understand what material is"? 

Everybody can say. That material is consisting things like protons, neutrons, and quarks. Some person who has read a little bit more about the material. Can say that there are subatomic particles like quarks inside protons and neutrons. So that person is mainly right. Most of the mass of the atom is in protons and neutrons. But the contact layer of the atoms is in the electron core. 

The most out electron cores are in the main role in chemical reactions. But most of the atom is inside the electron cores. And that means the person who is saying that material is forming of protons and neutrons is same way wrong. The fact is that even 8 years child can tell about things like electron cores and quantum interactions if that person has some book about those things. The thing that is needed is the skill of reading. And then we have the person who knows everything. 

But then that answer of the electrons and protons can be wrong. The material can be written text that should publish on the net. So when we are asking about the material we should describe what that thing means today. The material can be protons or neutrons. But it can be something virtual like data that is collected from somewhere. 

Knowledge is:

How the actor does something? 

And understanding is:

Why the actor does something?

And if we are thinking about understanding it's simply putting data units one after one. The data unit is like a frame in the film. And they can connect to the endless film. That film can show some certain processes very accurately, but we know that projector doesn't know anything about things that it introduces. 

So if we have artificial intelligence that can read it can read every single article from the databases. We can use keywords and then the AI is searching an article. That connected to those keywords. Then the AI can read those articles to us. Of course, there can be some kind of parameters that the AI can use. Those parameters can be how many times a certain word is repeated in the texts. That thing helps to filter the searches. 

So what makes artificial intelligence maximize the number of clicks is filling your homepage with swear words and highlighting those words. It will bring in clicks. But perhaps the publicity of such a website would bring all sorts of sales to online stores

The thing is that when the AI creates some articles it can simply find texts. And then it can connect the parts of those texts. When the AI helps the writer to make more addictive texts. It can search things like what kind of words are the most clicked homepages include. It can use things like internet search indexes and find out what are the first words of the most clicked homepages. 

This is how the AI makes sure that is the homepage or text is interesting. That is written on the net will get the maximum number of clicks. And the clicks are the thing that is used indexing the interest of the text or homepages. For AI the maximum number of clicks is that people are interested in things. Those are published on the homepages. And we know that this is not true. The clicking of some homepage doesn't mean that somebody cares what there read. 

We can click on millions of homepages and spend about a second on those pages. So to make real analyzes of the information about interesting websites, artificial intelligence needs more information. It requires information on how many minutes or seconds each person will spend on this website. In the case of online shopping, the measurement of interest can be measured using the number of sales transactions as an index. When someone buys something. It is an expression of interest.

But when we are going to think about the understanding. We don't know does the AI knows anything. About the things that it does. The thing is that understanding is an interesting thing. It should be a simple thing to explain. But it's really hard to understand.