Are we intelligent enough to see the intelligence of our creatures?

When we think that machines are not intelligent, we must find something that supports this thesis. The most usual argument is that we are putting limits on those machines. We are regulating the data what the machine gets and how it uses that data. So the machine cannot become more intelligent than we are, because we can stop it if it gets too much data for use. And that thing could be the worst mistake ever made. 

The creator of that idea didn't probably know about the internet and autonomous machine learning. Nowadays is possible that some algorithm is searching the data and store it. Without the user don't recognize it. And that thing makes the possibility that the machine knows things that the users and programmers are not stored in that system in purpose. 

Can computers be more intelligent than humans? Sometimes people are arguments that the machine cannot be more intelligent than humans by using the argument that humans are created machines, and that's why the machine cannot be more intelligent or smarter than their creators. The case is like can the descendant be more intelligent than their parents. 

Sometimes we are asked, "are we intelligent enough to see the intelligence of other species?". We are living in the "sapiens centric world". That means that we are thinking that there cannot be another intelligent species in the world or even the universe. The SETI program and search for extraterrestrial civilizations is accepted as science. Before that those things were just stories. 

Does the ability to win humans in chess make AI more intelligent than humans?

The thing is that artificial intelligence is winning humans in chess very easily. The new learning machines that can create new tactics and strategies on the chessboard are invincible. Those systems are calculating every each movement of those buttons very effectively. But those systems are also recording tactics that other players are using. That system makes the database by using the game records, and then it can mix those databases for selecting the most effective movements. 

But does that ability make the AI smarter than humans? Are the things like chess the description of intelligence? Or how we are describing the intelligence? The things like making the mathematical or some other formulas or modeling the quantum mechanical rules are sometimes described as "intelligence".

But the people who are working with those kinds of things might not even have a driver's license. That means those people cannot do everything in the world. Even the smartest mind in the world has a limit, is the thing, how we are thinking. Or is there some kind of limit? The theoretical knowledge doesn't necessarily mean. That there is some kind of possibility to make practical solutions to every problem modeled by theorists. And being a good quantum physicist or artificial intelligence researcher doesn't mean that those people are good chess players. 

()https://visionsoftheaiandfuture.blogspot.com/2021/08/are-we-intelligent-enough-to-see.html

How ERP learns things?

How ERP learns things?

The ERP (Enterprise Resource Planning) is the modified or expanded spreadsheet, what mission is to automatize things like storage bookkeeping. The way how ERP is interacting with databases is that when something is sold out from the storage or moved to another room, the system makes the automatic markings in the database, and the system can be acted as fully automatized.

If every single particle in a warehouse or building is equipped with an RFID system, the system would locate every single item in the building. That means that the controller would see the position of the video cannons or computers by searching, and if the system would be perfect, it would also see the reservations of that thing. This is one version of the fully automatized ERP-system, and that would be the advanced version of traditional ERP, where computers would make marking to the database whenever some item is sold from storage.

But what the learning ERP can make? If we would use an intelligent ERP-system, that means that if the ERP would allow locating every particle, while they are moving in some building, it can keep a record, where are the problems. If some particles would be destroyed very much, the system can also use cameras to find out where is the thing, what brakes things like insulators or clips. And that thing can cause momentum tools or something like that can impose again, what denies the damages of the parts.

The ERP system can also see if there are problems with physical movements in someplace, and that thing can be told to the managers, and they would see, is there some tight spot in the warehouse, that the material would not fit to go through that point. And that would cause the items, what dimensions, what will across certain value guide to some other route, and that would make working more flexible and effective because there is no need to wait for things in the work points.

The thing that makes the learning ERP-system more effective is that it would make orders when the storages are low. That makes possible to make things effectively and minimize the need to store things. The intelligent system will notice the real level of storage and also things like, how long those deliveries would take. And it minimizes the breaks of the production and the mixing of the storage. That means that the system will make sure that all old parts are used when the new ones are coming to storage.

And the system can also see, what kind of merchandise would be used mostly, and that means that the storages can be sizing for that kind of thing. If some merchandise is used mostly, that kind of stuff must be ordered lots of more than something, which is not used as much. And when the storages are running low, the system can send the ordering letter automatically to the merchandise deliverer. In this case, the artificial intelligence can fill the order form, when there is a need for more merchandise, and that thing makes it possible to make the work of human workers lighter because the system would make routine operations automatically.

How to teach robots to follow spoken orders?

How to teach robots to follow spoken orders? 

The idea of machine learning is the same as the people way to learn things, and that's why computer game-style platforms are very interesting things to teach robots. The action or learning process is similar, what is used to teaching dogs. The robot must connect spoken words to some actions, what the programmer can do with it. 

And this makes possible to make robots, which are understanding spoken language. This method is suitable for every kind of robot, and the idea is that the words are connected to recorded actions, so when the programmers are teaching the robot to open the door, they might say "open the door" and then they would transfer to use the virtual workspace, where they can use data gloves and probably Virtual Reality glasses, and make the action by using the virtual movements by using character, what is similar what is seen in the computer games. After the system has been successfully recorded the action, that means that the command "open the door" would activate this kind of movement series. 

The machine learning means that the character, what is the thing that is controlled by a computer would say some words, then the character is moving and acting as the programmer would want. And then those words are connected to the actions, what the programmer has made for the character. 

Moving of the character can be done by using the game platform, and then the virtual character would be used to test the effectiveness of the movements, and then they can transfer to the robot, which will connect those movements and other actions to the words, what the person says. This kind of technology can also be used with combat robots. And those robots can follow the orders, what the commander says without excuse. 

This kind of robot would be very interesting in the many dangerous actions. And thing what makes character dangerous is that some game character would get the physical form. When we are thinking about computer games the programmer, who will make commands to those systems could use the computer games to selecting the most suitable series of movements, and then the commander must just select the most suitable movements and connect the voice command to that series of movements. 

When we are thinking about the actions of robots every kind of action is a series of movements. That means the system would just connect the movements to the command, and that makes that kind of robot very dangerous. The robot itself would not care, what kind of commands it would get, and if the voice recognition or other safety system accepts the command, that allows the operator to give the command "sweep that area", and then the robot will do everything, what includes in that action. So this kind of thing can be used in the Pentagon's terrifying new robot army. 

Image.

https://upload.wikimedia.org/wikipedia/en/5/50/Cylon.jpg

How to teach character in computer games?

How to teach character in computer games?

When we are thinking about machine learning, computer games would be the right place to test and innovate that kind of thing. Computer games are one of the biggest parts of the world of computers, and when we are thinking about artificial intelligence, what would be an effective tool for making those games more realistic, interesting and difficult, we must think the method, what the programmer would use when that person would make the character learning things, what are important in the game. The thing is that the learning of the character would happen by a very effective method, where the movements of the most successful player would be recorded, and then that data would transfer to the automatized characters. That means that the system might copy the master player to the virtual characters.

And then somebody would ask, how the master player would be selected. The answer is simple, in every scenario of the computer game are the character, what is controlled by a human, and the character, what is controlled by the computer against each other. Then the master would be selected by a very easy method. If the character, what is controlled by the computer will win, that means that the computer is master, but if the human player is winning, the character, what is controlled by a human is master. And the code of the game would order the system to use the movements of the master.

This means that the movements, that are recorded from the human users are transferred to the character, which is lost in the battle. When we are thinking about this way to increase the skills of the computer-controlled characters, we might think, that when the player would step in the virtual game board, and start to play, the artificial intelligence would record the things, what the player makes, and then transfers those actions to the characters, what are coming after fallen characters.

That means that the computer-controlled figures, what are coming later would have more complicated movements, than the characters what the gamer faces in the first moment. In this scenario, the gamer would use more complicated movements every time, when that person would be advanced in the game, and the idea is that the gamer would teach the solution, how to fight against the player.

This would make possible to create harder and harder computer games. The machine learning is one of the key elements in computing, and by using this kind of method, computer games would become very difficult. When the gamer would play the game, the movements and actions would be recorded, and transfer to the next characters, until the computer would win. This is one version of using machine learning.

https://upload.wikimedia.org/wikipedia/en/thumb/e/e4/Tetris_DOS_1986.png/250px-Tetris_DOS_1986.png

About learning methods and active learning

About learning methods and active learning

In the beginning, I must say, that the best ways in the studying process are not the easiest way. And during studies, there is no easy way to pass courses. If we think effective learning, we must work hard, and in the case of learning, we must take as many brain cells or neurons involving this process.

The thing in the learning process is that we should use as many neurons as possible in that period. So how we could maximize the number of neurons, what is taking part in this process. This is the question of effective learning.

Traditionally, we have learned that there are three types of learners. Visual, auditory and kinetic persons. And only the last one would need to make notes. This idea is very wrong because every people need notes. Kinetic people are not stupid, they just learn by using different nerve tracks. And actually, we should use as many nerve tracks as possible.

This is called "active learning". That thing means that a person makes something while the lecture is going on. And also active notes helps people stay awake, even if a person is tired. If we would just sit and listen to things, we must realize, that in that passive situation, we might get sleep. And that thing means that we would miss the entire lecture.

The easiest way is to say, that I'm an auditory or visual learner, who must not make notes. And here we must notice, that nobody wants to be a kinetic learner. That would feel the easy answer when the teacher asks about this thing.

So in the learning methods, the most important thing is that we should not think about the traditional way, that we are a kinetic, auditory or visual learner. The idea is that we should learn to make notes about lectures and other cases when we should learn something.

If we would want to maximize the learning experience, we should listen to the worlds, what lecturer uses, make notes and take photographs of the material at the same time. The idea in this method is that maximizes the number of neurons, what are used in the learning situation.

But how we should make those notes? That is a very interesting question. And the answer is that we should follow the speech, what lecturer keeps, and then make notes by following the spoken words. That would maximize the audition- kinetic experience, and then we should look at the screens by using fast sights. That would make possible to connect the visual experience to the learning.

The thing is that we should remember that the material of the lecture is many times delivered to students. But the thing is that using active methods, even boring things might start to feel interesting. And the active touch will keep people awake. If we have something to do, being awake is easier, and time moving faster. Even the most interesting studies contain things, what people don't like. And this is the thing, what we must realize while studying things.

Artificial intelligence can be taught by using games

Artificial intelligence can be taught by using games

Artificial intelligence can work with console- and computer games. The thing is that the movements of the gamer are collected to the database, and the computer would calculate, what mistakes every character, what it moves makes. Then it would simulate the choices, what the character must do, that its action would be more effective. The thing in artificial intelligence is that it can analyze things like the direction of sight and another kind of things.

And then the system would have parameters how to close the opponent, and what kind of things must be done. And the action of this system would be, that if some action would not be done again if the character fails. This kind of simulations can be extremely realistic because modern supercomputer technology can use multiple parameters, like simulated flight trajectories, and the thing is that the virtual world can be more difficult than the normal world.

There is claiming that the multiple net games are used to teach artificial intelligence to act as the military commander. In the world of the military, artificial intelligence would allow something, what we ever created before. The commander, who would not have emotions. The thing what artificial intelligence needs, when it will send the men to the mission is the tolerated level of own and civilian casualties. And that is the point, why this kind of solutions fascinates the national leaders. The feelings are a bad thing for the commander and that's why they wanted to cut off from the commanding system.

The target drones can be used to collecting data for artificial intelligence.

As you know, the difference between robots and human is that robot ever excuses the orders, and that means that the robot aircraft would just operate as the "kamikaze". That means the aircraft can operate as the regular fighter-bomber, but it can just impact with other things. There is a possibility, that the targets are pointed in the memory of the computer.  And if the target has enough points, which means that it would be the aircraft carrier or some other key unit, that aircraft can just collide with the target.

That system is mentioned for saving the aircraft for the most important targets, and if we would think the aircraft like QF-16 Robo-Falcon, that aircraft would be thought only the advanced missile. But it has more usages than with the normal missile. That aircraft can operate like normal aircraft, but it can also act as the missile if it sees the suitable target for that mission. During the exercises where the remote controllers operate with target drones, there is a possibility to collect the data, what can be used to train the artificial intelligence for the independent operations.

But those drones can also be used as the attack aircraft if they are equipped with the same systems with "Predator" drone, and the operator could fly that aircraft in the hangars of the targeted airbase. There is a possibility, that somebody would use "Troy horse" which means remote-controlled aircraft, what is made from the same fighter or some other aircraft, what is used by the enemy. That aircraft would just be flown in the hangars of the enemy airbase, or another important target like an oil refinery and ammunition factories. This can be the future of the battlefield.

Why the brains of insects are so fascinating?

Why the brains of insects are so fascinating?

https://controllingsociety.blogspot.com/

The power of brains of insects is the reason for one very simple thing, and that thing is the neurons of the insects have connections with themselves. Those round or circle connections would allow that one neuron can do many things, and that thing makes most of the insects immune against VX-nerve gas. The reason why VX doesn't affect the bugs is that the bugs don't have synapse slit between neurons and muscle cells, and this would make impossible to get the effect in the synopsis slit, and the effect of the VX-nerve agent is that chemical denies the operate of the enzyme, what will break the neurotransmitters.

And if the human would have a nerve system, where the neurons would have contact with together only with electricity, which means that the neurons must connect straight together without slits, would the neurotoxins like VX lose the effect against that kind of species. The reason, why the wings of the insects are acting so fast is that every muscle cell has one neuron, what is connected to them, this makes possible to react extremely fast because in the emergency situations is only one way to act, and that is jumping to some direction before starting to flap, and the direction is ordering the neuron, what first activates. The order is given by the eye or another sensor, what first activates the neuron.

Learning makes neurons slow

The reason, why the neuro-agent would cause death is that the nervous system simply overexcites, and the reason is that the cell must handle multiple things at the same time. But when we are thinking about the overexcitement of the neurons in the point of view of insects, the situation that bugs would be exposed by nerve gases would make those insects more intelligent and allow them to learn more things than in normal circumstances, because those neurons would let more information to go thru them.

When the insect is young the operation of the neurons would be extremely fast because there are fewer connections to the neurons. And that means that the neurons would act like RISC-processors. They have only one way to act, and that thing makes also the people, who live in the extremely low stimulus field are handling things, what are thought to them very well, but they have problems with things, what are happening in the field, where the level of secondary stimulus is high.

And in those cases "unnecessary data" would cause that the number of connections in that neuron would increase, and it makes them slow.  The thing, what would make neurons slower is that even insects like flies are learning things. And the learning process would cause the neurons would get more connections, which means that the neurons must choose the connection, what it uses.

The thing is that there are some ideas, that by using nanotechnology the number of connections of the neurons would be increased. The idea is that the internal communication of the neurons would happen by using electricity, and the neurotransmitter used only in the communication between cells.  In real life, there would be no limit for the connections of one neuron, except the area on the surface of the neuron is limited. That means that the synopsis, what is connected to the surface of neurons must be very thin if there would be wanted to create many connections, but otherwise, one neuron can have billions of connections, if those synopses are small enough.

The nanotechnology would allow creating the very thin wires, which are made by using fullerenes or in the extreme visions by using the chain of the carbon or some metal atoms, what would create the synthetic connections for those neurons. Those artificial synopses can inject to the body, and then they would be inside the nano submarines in the tiny reel. Then the submarine would travel in the nervous system, and start to make new connections for the neurons.