Machine learning can peer to the future.

We live in an environment that is the singularity of natural and artificial actors. Things like the internet are full of information that can be virtual or it can be real. But the internet has not removed our need to go out for work and keep our wealth at a good level.  While we use things, like activity sensors or GPS the internet collects information on how we act. 

Making a data matrix is an easy thing. If the data collector is the Ai. The system can simply follow the crossroads. And it can observe which way people are turning more often. 

By using AI, is possible to turn things like cell phones into speed-measuring tools. The system must know the distance between two landmarks like traffic lights. Then it must know what object it must follow. The AI can calculate the time that the device uses in that range. And that thing is telling the speed of the vehicle. If there are two cameras at a certain distance from each other. 

The system can connect data that those cameras are sending. When the car passes the first camera the system stores its registration number in the database. And when the second camera takes the picture the time between those two pictures is telling the speed of the car between those measurement points. 

The internet can connect that data as the matrix. That system can use that matrix to predict how we will react in some cases. When somebody says that AI is the most powerful thing in the business environment, I would say that the person is wrong. The most powerful tool is networked AI which can interconnect many systems like the spider's net. 

The AI can collect things like what kind of books person loans from the library. And then AI can compare that data with other customers. If there are very certain types of actors. That thing makes it the AI possible to make a profile of what kind of books, for example, typical economists are reading. 

If the AI has to access those person's working files. It can make the profile of what kinds of abilities have people, who are reading certain types of books. 

When we are using the net, everything that we are doing will store in databases. The information matrix that the networked AI can use is enormous. This makes it possible that AI can create the behavioral matrix of certain people like economists and military personnel. And then the system can create a model of how the average representative of that group acts in certain situations. 

The fact is that if some person would be a military man at a young age, and go to study things like economics when that person is older. That thing allows for making an information matrix of how the person will react to some situations. 

By using this method, where AI collects data during the entire human life, the system can make a model of what kind of solutions, as an example in military service economist makes. The same thing can use to hunt serial killers from the net. 

And, if those people make successful businesses or any other actions. That thing makes it possible to select the most capable people for company and military operation leaders. The system can calculate the average success of a person with certain background and education in every type of environment. 

https://scitechdaily.com/scientists-use-machine-learning-to-peer-into-the-future/

https://fromplatoscavetoreality.blogspot.com/

The new type of quantum computer is basing photon magnetic interaction.

Photons can use to manipulate magnetic fields. 

One version of quantum sensors is the nanotube there is ionized gas or laser rays. The magnetic field senses the changes in the position of the ionized gas.

Or it can sense the changes in brightness of the laser rays. The magnetic field can manipulate by using photons. And that thing makes it possible to create more accurate sensors. 

But it can make a revolution in nanotechnology. The particle that will be moved can magnetize. And then that magnetic field can manipulate by using photons. If that ability can connect with scanning tunneling microscope. It can move single atoms on the layer. 

That kind of ability is making the new type of quantum computers possible. A single electron can take under the stylus. And then the photons can pump data in those electrons. And that is making it possible to make the new type of quantum computers. 

The new type of quantum processors can base the material there are tunnels. 

The laser rays will shoot through those tunnels. And the magnetic fields are sensing their brightness. If the magnetic field can affect the brightness of laser rays. That thing makes it easier to input data to photon rays. And that makes it easier to create a communication layer between electric and photon-based binary systems and connect keyboards and screens straight to quantum computers.

The new materials. And the new types of ideas. These are the tools for a new type of quantum computer. The image above this text is introducing a new type of nanomaterial. That material is full of tunnels. And those tunnels make it useful for new quantum computers. 

The photons can affect magnetic fields. And that thing makes it possible to drive data between photon-based computers to regular electric binary systems. That allows connecting the quantum computers to keyboards and screens. The electric impulses from keyboards will transfer to that structure. The magnetic field will also interact with photons or superpositioned and entangled particles. And that thing allows using the quantum computers by using regular keyboards. 

The idea of that kind of system is that through those quantum tunnels will be shot the photon beams. There is a magnetic field in that structure. And then the photons would shoot in those laser rays. Another way to make that thing is to pull the quantum entanglement through those tunnels. The idea is that the energy in that particle pair is symmetrically identical. 

The photons will shoot to the channel that connects those particles. And then those photons are used to anneal those particle pairs. Because data is traveling in both directions. That allows creating the error detection system. That kind of system uses two lines there identical data flow. And if there are differences in solutions there is a mistake or error. 

The idea is that the anneal of those superpositioned and entangled particles affects the magnetic fields. That allows the system can transform photonic dataflow to the magnetic field. The magnetic fields can detect the changes in annealing. And that allows driving data to binary systems like keyboards and screens. 

https://phys.org/news/2022-01-scientists-atomically-thin-wires-ribbons.html

https://scitechdaily.com/physicists-manipulate-magnetism-with-light-playground-created-for-observing-exotic-physics/

Image: https://phys.org/news/2022-01-scientists-atomically-thin-wires-ribbons.html

Deep learning algorithms are like the expanding network of connections between databases. 

The data is traveling in the forms of X and Y. The system can connect the data handling units to the form (XY). The thing is, how the system would need the orders is how to sort the databases. There is "X" that makes it deep learning. 

The AI can search all databases where is "X", and then it tries to solve the problem (*X). If there is some actor that is commonly predicting Y. That term is in the position of an asterisk (*) that allows the computer to connect that thing with "Y". So if that thing is "X" the form of the data unit is (XY). 

And then the AI can turn to search the data unit that comes before the "X". Then that asterisk (*) is before "X". So the form of filling data unit is (*XY). And if that thing that is the most common is the "W" the form of data is (WXY). And then the system will try to follow the next data module. It must replace the asterisk (*WXY) by using the next letter. Until it has made the network of the entire data. 

The letters (XYZ) and others are the data units. The data units are databases that involve some kind of data. The data can be the movement series of the successful operation. But that kind of data handling tool can use to predict how some person would act in some polls. The system can mark is their differences in answers depending on the sender of the form. And also the system can detect things how the problems are solved. 

The fact is that in this kind of system. The key element is fuzzy logic. There is no way that there is always letter or data handling unit W before the XY. But there is an error level that will make the solution acceptable. When the system finds some other than the most usual data handling unit before the "(XY)". That thing means. 

That the human operator can check the thing why there is some other data handling unit. One thing that can make the case look like this (MXY) is simple. The operational area of the AI is different than in the case (WXY). The normal solution (WXY) might be meant for city area operating robots. And the (MXY) might be meant for the mountain area-operating robots. 

https://thoughtsaboutsuperpositions.blogspot.com/