AI predicts human behavior with stunning accuracy.

Artificial intelligence can predict human behavior with startling accuracy. This is the result of comprehensive research. If the AI can create a model of the behavior of certain individuals, that model can be expanded to larger groups. Every kind of behavior in groups begins with individuals. The mathematical formulas that are based on Ludwig Boltzmann’s theorems make it possible to create models of how certain people and people groups behave. That ideal gas model is the thing that inspired SciFi novelist Isaac Asimov to create the model of psychohistory. In Asimov’s novels, psychohistory is a tool used to model and predict how human groups behave in certain situations. 

The AI that can predict human behavior accurately can act as a tool that assists humans in war and peace. The AI that can predict how humans behave and how they act can be an ultimate tool in work interviews. That tool can be ultra-powerful in the military. And the system’s accuracy rises when the group that the AI tries to predict is homogenous. That thing makes those AIs scale their behavior models through the entire group. This thigh makes it possible to predict how things like jet fighter pilots operate. The ability to collect and process data makes it possible to create models for every possible situation. The ability to predict behavior can decrease traffic accidents. 

Ludwig Boltzmann (1844-1906)

Psychohistory is here more accurately than Asimov ever could imagine. 

"Psychohistory is a social science that analyzes human behavior by combining psychology, history, and other social sciences, while also being an amalgam of psychology, history, and related social sciences and the humanities. Its proponents claim to examine the "why" of history, especially the difference between stated intention and actual behavior. It works to combine the insights of psychology, especially psychoanalysis, with the research methodology of the social sciences and humanities to understand the emotional origin of the behavior of individuals, groups and nations, past and present. Work in the field has been done in the areas of childhood, creativity, dreams, family dynamics, overcoming adversity, personality, political and presidential psychobiography. There are major psychohistorical studies of anthropology, art, ethnology, history, politics and political science, and much else." (Wikipedia, Psychohistory) 

There is also the possibility to include things like statistics, and other mathematical models into those sciences. 

Psychohistory should be a SciFi tool that makes it possible to calculate and predict the behavior of large human groups. The novelist Isaac Asimov introduced that tool in his Foundation novel series. Then researchers started to investigate that tool. And maybe psychohistory is reality sooner than we expect. Or maybe it already exists.  

However, researchers created a model that makes the psychohistory possible. The system uses historical databases to model how people act in certain situations. Then the algorithms search for similarities in the modern environment. The psychohistory is based on Boltzmann’s NTP formulas and models that are used to calculate ideal gas and its flow in galaxies. The idea is that it's easier to calculate and predict the behavior of large groups than one individual. This is why the big entity's behavior is easier to calculate than one gas molecule. The problem is that in the time when 

Asimov created his idea of a tool that can calculate. The behavior of the large human groups, quantum computers, and neurocomputers was not predicted. When people believed that psychohistory could ever be created they were wrong. The modern internet makes it possible to collect data from people’s behavior. And that model makes it possible to create the macro-model that helps to predict the behavior of a large human group. The system that handles a very big data mass can calculate the behavior of the individual people and then make a matrix about that thing. The system can create millions and billions of data matrixes that can unite into one entirety. That makes it possible to predict: how society reacts and behaves in certain situations. And that can be the tool that can turn entire society to a new level. 

https://en.wikipedia.org/wiki/Foundation_universe#Psychohistory

https://en.wikipedia.org/wiki/Ludwig_Boltzmann

https://en.wikipedia.org/wiki/Psychohistory

What separates us from AI?

Today we use lots of time to think, why does AI decrease our IQ? The answer is this: this modern time where we live benefits superficial people. Our working life encourages us to have maximum velocity. There is nothing wrong with the velocity-based working life. But the problem is that the measurement tools for velocity are things like how many executions we make during our working day. The measurement tool can be how many screws we tight. Or how much money we bring to our employer. 

Deep thinking is not encouraged in our working life. When somebody sits in a coding company, that person should use the AI assistant. Can you even seriously imagine that you would go to the library and borrow a book about the problems? And would you have time to stop deeply thinking about things that something really means? How often in the week, do we discuss philosophically and think deeply about things that we really see? We can do many things without deep thinking and logic. 

And when we think about things like some 1970s chess simulators, we must ask ourselves are those things really thinking? Do some ATARI, or Commodore 64 really think? It can drive a car on screen, but does it think? The system can move chess buttons and win chess games or some formula games against humans. But is that a mark of advanced thinking? Or does the horse, who sees three fingers and knocks the floor three times using its hoof, be some doctor of philosophy? Is a chess simulator with 64 kb memory more intelligent than some university professor? Maybe that thing is not as versatile as a professor. 

The IQ is something only if we compare it with something else. If we play chess alone or make something else, we don't need to be intelligent. If we are surrounded by people who have an extremely high IQ, in that case even a high IQ doesn't mean impressive. Same way. If our only opponent in a chess game is Garry Kasparov. That makes all of us seem like very bad chess players. Then we can think how ordinary chess player Kasparov is. Did an ordinary player play 2533 matches at the world champion level and win 1371 of those games? That means 54,13% winning games. But that happened at the highest possible level of the chess game. So does an ordinary player ever reach that level? 

But if the professor wins the AI in chess that is not news. The news is that the professor, some AI chatbot, or quantum computer loses a chess game against that machine. Nobody cares how many things the professor made before that chess game. Nobody even cares if the professor plays that person’s first chess game. And nobody even asked if the AI played chess before, or did the AI even knew how to move buttons. In the same way, a professor might not necessarily play chess at all. The fact is that all geniuses don’t even play chess. And if AI learns like humans, there must be something there that gets things like button movements. The computer can play chess but it might not do anything else. 

Normally we say that AI simply mimics things and then it doesn’t have a deep knowledge of things that it makes. When I read about that kind of thing, I sometimes remember one question from philosophy exams. That question is: “What separates philosophical thinking from the every day, or regular thinking?”. The answer is that philosophical thinking is deeper and more analytic than regular thinking. And that brings new questions into my mind. That is when we last exercise philosophical, deep thinking?”. When we do something, like turn screws in workplaces, do we really think about the purpose of that action? 

How deep out thinking? And how deeply do we think about things that we do in everyday life? The thing that’s enough is that we do what we must and that’s it. We have no time to think deeply about what some screw or other things can do. We simply do our job and that’s it. The thing is that humans learn through mimicking. We know many things. We know how to drive cars and use computers. We know how to fly airplanes and still, we don’t know anything about those things. We can drive cars. But we don’t need to know what happens in the car when we pull the gas pedal. We know that cars accelerate, but we must not know how cars make that thing. 

We could put the car to react with the gas pedal two ways. We can make physical contact between the gas pedal and the engine. Or we can use a camera that registers the gas pedal’s position. Then the AI accelerates or brakes the vehicle. For that system, the AI doesn't need any deep knowledge of things that it does. The system must simply accelerate the electric engines if we use electric cars. And the fact is that the AI must not even know what an electric engine is. When a car accelerates the system can involve code there is the word “engine”. Then some control circuits have a code that makes it react to the signal that is meant for the engine. 

Same way, if we hear the word that is our name, we automatically react to that thing. Our name is the thing that activates our attention. Sometimes we think about our names. But we forget that we learn that thing. Why cannot our name be C3PO? Because our parents didn’t give that name to us. Our names are “Jacks” and “Jills” because our parents gave those names to us. But have we ever wondered why some names are reserved for girls and others for boys?  And then we learn that those words are our names. 

But if our parents would give the name C3PO to us. We would react to that as our name. But do we ever imagine, why cannot our name be C3PO? Because we never thought that before. Then we can go back to begin, and ask how to describe thinking. Does thinking mean that we think how many times we hit some nails? Or does thinking mean how many chess games we learn? 

The thing is this: if we drive about 10000 kilometers without accidents or we win millions of chess games in our life that is not news. The news is that if some robot car drives off the road. Or if some supercomputer loses a chess game to some ATARI chess machine. Those things can be translated into that maybe the ATARI chess machine is more intelligent than humans and supercomputers. 

The AI that beats humans is at the door.

 

Mark Zuckerberg says that he wants to create an AI that is more intelligent than humans. The AI can have better cognitive skills than humans because they learn differently. Every skill that the AI has is like a macro in its memory. There is no limit for the number of those macros, or automatized actions that the computer stores into its memories. The limit is the memory storage. The AI will not forget humans. That makes it possible for the same robot can cook. 

Clean and make almost limitless numbers of operations without errors. If we want to make the AI that makes food for us we must create a huge number of variables for that thing. But there can be a shortcut to that problem. The AI can involve certain modules. So, if the user wants meatballs that AI downloads the meatball algorithm and databases to the robot. That makes it possible to make the system operations lighter. The databases or datasets can be created separately. 

Cognitive AI means that it can create a dataset independently. And for computers, each dataset is a certain skill that it has. 

The AI is the man-created alien. Are aliens already here? The fact is that if Mark Zuckerberg wants to build AI that is more intelligent than humans that thing is an alien. Human-made aliens are things like genetically engineered species and artificial intelligence. And then we can ask is artificial intelligence really intelligent? Can it think? The AI can do many things. It can advance its skills and it can learn from other AIs and from films. Turing’s test is the thing that measures the AI’s ability to think. 

The AI can mimic humans. It can transfer all movements that humans make to the human-shaped robot. That thing is the thing that makes the system seem intelligent. The cognitive skills that AI has made it possible to create learning systems that can control robots on the ground following certain parameters. When a robot fails in its mission the system also knows what it should not do next time. The physical robots are good subjects for modeling the cognitive systems. 

The AI can learn autonomously by using the same methods as humans. If it fails some mission that means there is an error. The cognitive system learns by using a method there failure means that the system must not try that thing again. Learning by mistakes is easy to explain by using a model where the AI controls a robot group. There are let’s say 5 paths that the robots can use for traveling from point A to point B. That AI sends a robot to make its mission. When a robot fails like falling into a canyon the system learns what it should not do with the next robot. 

The system creates the model of the landscape and then it creates the model of the path that the AI selects for the robot. When a robot succeeds in its mission the AI stores the data about the environment for the next time use. The system can also store the data about failures so that it knows what it should not do. Failures are also important for developers. The robot makers need knowledge about what caused their product failure. 

The robot should know how steep the slope the robot can rise. When we talk about robot success and things that the robot should not do, we must realize that the robots cooperate. The human-shaped robots can cooperate with flying quadcopters that send data about the landscape and other things that those robots require. 

But then we can think about AI as a mathematician. The system must also recognize the mission that it has. When the AI recognizes the mathematical formula, it can connect the data that it collected to that formula. The problem is this. If the mission is not well-explained AI will not simply understand that work. The AI must dare to say that thing. If the mission is not clear the AI must not try to make anything. The main problem with learning systems is this. They simply connect a new subprogram or macro in them. And that makes them look very intelligent. But the main question is: can that system think? 

For computers, every skill is a database or dataset. A learning system is described as a system that can get new skills and then link those skills with other skills. Or, otherwise, we can say that the self-learning system can create new datasets and link those datasets with other datasets. 

It can connect data and data frames into one entirety. But the fact is this. The AI simply mimics subjects. It seems that the subject makes something, and then the AI makes the same thing if it faces a situation that matches that case. But we humans also learn from mimicry. When we see that the teacher makes something at the front of the classroom we can mimic that thing. 

When we learn something new with teachers we simply mimic things that the teacher makes. And then we store that data model in our memory for the next time use it. That is the rigid model. The rigid model includes basics for some computer skills. And then we must simply connect that model with other things. This ability to interconnect that new model with other things makes it flexible. The model turns into a thing that is like an amoeba. 

The system can connect that new model to many other skills. When we talk about things like image processing programs, we can also connect skills that this program requires with things like writing skills. The fact is this: the AI must not do everything that the user wants. It must have the possibility to refuse to follow orders if the user wants to use it for criminal activities. The other thing is that the AI must have certain orders for what it must do. The AI must have the ability to use virtual models on the screens that it really makes when somebody gives certain orders. 

When we think about cases in which the robot acts as a mover there are some human-shaped mannequin statues that can cause a bad situation. If the mannequin statues are not well described to robots, that system can also transport humans to the lorry. In those cases, the AI must know all the details about their subjects. They must know that the mannequin statues are plastic and other details. 

The new form of living is the “new village”.

In medieval times the city walls separated people who lived in the city from people, who lived outside the wall. There lived people who ever stepped out of the city. In that time people told stories that in the forests lived monsters who ate people. Sometimes mentally ill people are banished to the forests. But those walls created a feeling that the world outside the walls was hostile. That increased the city leader’s authority. When people believed that there were evil spirits in the forests around them, that thing made them easier to control. And the question is: are we returning to those kinds of cities? 

What if our future is that we would live our entire life in the same building? Things like artificial intelligence and virtual reality make it possible to make virtual trips to lands that are far away from the place where we live. We can simply open a solarium, take a VR system to our eyes, and then the AI-controlled system connects winds, sounds, and other things that we need to the space. The AI observes that we will not take too much radiation. 

The Saudi-Arabian mega project called “Neom”. That thing will be the most incredible megastructure in the world. That kind of thing brings the new types of village societies into the front of our eyes. The idea is that the system brings homes, all services, and workplaces under one dome. And in some visions, cities like New York will be covered with giant domes that should make the air comfortable every month. That thing brings the route to the ultimate segregation into the front of our eyes. That thing can look like a village society with idyllic things, like the ability to keep the T-shirt on every day. 

What happens if we ever leave that dome? Can that dome feel good? The fact is this: the dome turns into an entirety where we can live. We will never feel fresh air. All physical works are made with robots. And maybe we see the future as a thing where there are giant forests and there are giant domes there and here. That future is the thing that takes us to heaven and hellfire. The AI-controlled structure allows us to control each other. The place where we would live is safe. 

But there is also another side in that idyllic structure. That structure can turn into a prison. What if our leaders will use that thing against us? The dome allows people to control people simply by using the chemicals that are in the air. Or the leaders can use the air pumps to control air pressure. And as always: there is a chance to use that kind of system to steal people's lives and entirety. This dome can turn into the thing that brings the highest walls between people that have ever been made in history. But that kind of thing offers solutions that can also save nature. The city can use green energy as an example of energy production. 

There is the possibility that the AI turns non-predicted.

 

The AI can turn dangerous because it cannot think. And then another thing is that the AI becomes dangerous if it can think. Thinking AI can process data automatically. That means it can create unpredicted actions. The problem is that the AI that thinks must have something that determines its actions. That thing is the law book. But even if the AI thinks like a human, it must have orders to search and compare the queries with the lawbook. 

The AI is like a child. It cannot know the sources automatically if it learns and thinks like a human. If we ask a child to do something, can we expect that the child will take the lawbook from the shelf and then search if that action is legal? The AI will not make any checks without orders. And that is the blessing and curse of the AI. The AI makes only what its operators order it to make. This makes the AI “trusted”, but there is also a possibility that the AI is in the wrong hands. 

North Korean intelligence can make the cover-up company in some EU cities. And then get the user rights for the AI systems. In that case, the company will not control things that the AI makes. If the AI uses the lawbook to check the query's relationship with law there is a possibility that the company links those lawbook links to faked lawbook homepages there that operation is allowed. The wrong user can cheat the AI to turn dangerous. 

AI can turn dangerous in the wrong hands. The North Korean hackers taught the Chat GPT to cheat the BitCoin companies. And that tool stole money from BitCoin investors. There is a possibility that those hackers can use the AI tools against other systems.  The North-Korean case is not the only one, where the security of the AI is broken.  That is the new thing in hacking. There is a possibility that hackers train the AI assistants to break into the systems that look secure. The fact is that the AI doesn’t think. It imitates humans. But the AI cannot think like humans. 

Because the AI cannot think it is possible to cheat to make things that it should not. The AI just follows its protocols. And that makes it dangerous. The AI will not automatically search law books and that makes it the tool that can operate against the law. There is a possibility that the faked law books allow the use of AI to create things that are illegal. 

Because every skill that the AI has is macro, that means the operator must only cheat the AI to activate a certain macro. And then the AI will not make resistance. AI is a tool that faces lots of criticism. But the thing that takes the bottom out of that criticism is that the people who introduce criticism start their own AI project next week. Every single company in the world is fascinated by AI. AI is the tool that makes people more effective. 

They say that AI is the next-generation tool that transforms everything. And then we face calculations that the AI can increase productivity and other things faster than anything before. And if the company doesn’t follow that trend they will lose their effectiveness. AI has turned into the dominating tool for the business environment. And that thing makes the AI dangerous. 

Business actors will force almost everybody to choose and use AI. And then we face an interesting thing. At the same time when somebody wants to push brakes for the AI development some other actor will turn to use AI as a control tool. When we talk about thinking and imitating, we can say that imitating offers a better solution than thinking, if we take the point of view from the company leaders. 

The AI has no will. That means the AI should not deny anything that operators order it to make. But there are cases in which AI refuses to make something. Sometimes the action that the user asks is reserved for users who have privileged accounts. They are reserved for the paid accounts. Or those actions are given by unauthorized users. So the AI can refuse to shut it down because the user has no right to shut down the server. 

Some people said that this person created an AI assistant that was a better coach than anybody before. This can be right. But why is AI a better coach than humans? There is a risk that the AI pleases the user more than the human coach. There are tales about AI as therapists. The big question is what the AI should do if the customer says something that can cause a trial or crime report. AI can be the tool that will never turn angry. But the big problem is this: What are the limits of AI? And when should AI destroy the privacy of people who use it? In some visions, all actors on the internet have AI assistants, who advise the user. 

That assistant can observe how long the person spends with other things than the work duties. But the big problem is this: what if the company pays for that kind of AI assistant for the worker’s home computer? The operator can simply add the worker’s home computer’s access account for the allow to use the company’s AI assistant. There is a possibility that the AI assistant can simply use stealth mode to observe the user. And then it can send that data to the company’s computers. The problem with AI is that it must be open. There are always some people who want to use this kind of system to observe other people. 

https://www.rudebaguette.com/en/2025/07/ai-in-the-wrong-hands-north-korean-hackers-exploit-chatgpt-to-steal-millions-while-malaysian-funds-vanish-in-digital-heist/

New laser applications can offer protection against the EMP and make quantum networks closer than ever before.

"UBC scientists have built a quantum “translator” that bridges microwave and optical signals, potentially unlocking global quantum communication. The tiny silicon chip maintains delicate quantum links, opening a path to future quantum networks. (Artist’s concept.) Credit: SciTechDaily.com" (ScitechDaily, Engineers Build “Universal Translator” for Quantum Computers)

The new systems can transform optical waves into microwaves and the opposite. The nano-size system that can transform radio transmission into optical waves can make it possible to create new, ultra-small robots. 

Researchers developed a quantum translator that can transform microwaves into optical signals, and the opposite.  That kind of translator can protect electric systems against EMP systems. In that model, the radio- or electromagnetic pulse will be transformed into the optical signals. That thing decreases their effect on the microchips. The ability to transform electromagnetic bursts into non-coherent optical waves is the tool that can create new types of protective systems against EMP systems. And if the system can be the tool that can be used to create new, ultra-small lasers and masers. 

Those systems can delete things like DNA- and protein molecules with extremely high accuracy. The ability to transform micro- or radiowaves into optical waves makes it possible to create systems that make very small robots swim forward in the water. Those small robots can use lasers to create small bubbles ahead of them. The liquid in the back of the machine pushes it to that bubble. Then that system can revolutionize nanotechnology. 

If the system can transform radio waves into optical beams and turn them coherent. It will revolutionize nanorobot research. 

"Artist’s illustration of the RAVEN technique, which measures a complex light pulse using micro foci and spectral dispersion, which is then fed into a neural network for retrieval. Credit: Ehsan Faridi" (ScitechDaily, Scientists Just Froze the World’s Most Powerful Laser Pulse – In a Single Shot)  If that system operates backward it can create extremely powerful laser beams. 

"An artist’s concept of NASA’s Orion spacecraft orbiting the Moon while using laser communications technology through the Orion Artemis II Optical Communications System. Credit: NASA" (ScitechDaily, 4K From the Moon: Artemis II to Trial High-Speed Laser Communications)

The ability to trap laser rays opens a path to new types of secured data transmission. And it opens the path to new types of military applications. 

The new laser systems offer the fast 4 K data transmission to the Moon. Laser communication is important because solar storms can disturb data transmission. The fast data transmission allows control systems to remotely from Earth. Another thing is that data transmission allows engineers to update systems without the danger that some outsider can steal the robot vehicle’s codes. Those codes can also make it possible to use them to control military drones and robots. The other thing is that it allows you to watch regular TV on the moon. That is a good thing if there are astronauts that stay on the moon for a long time. 

That also makes some operations cheaper, because that means there is no need to create special systems for Moonbases and vehicles. Highly secured data transmission with very high accuracy makes it also possible to create new types of systems that can protect spacecraft against things like small meteorites and space junk. The same laser system can also make it possible to create systems that can destroy targets from the Moon. We know that some nations are interested in using the Moon as a military base. 

The new thing is that the researchers trapped an extremely high-power laser beam between two mirrors. That thing makes it possible to create systems that can revolutionize USB sticks, and the same technology can make it possible to create new types of laser systems. Does the power of the laser system determine its role as a weapon, or is its role as a communication tool? The trapped laser ray can make it possible to create a laser system that pumps energy into that chamber where the laser beam jumps between two mirrors. 

The outside radiation source pumps energy to that beam. And sooner or later the laser ray breaks the structure. The laser bullet can be that kind of system. The bullet simply involves two mirrors and the laser beam that jumps between two 100% reflecting mirrors. When that bullet hits the structure it releases a laser ray into the object. The same system can also store data in that laser ray. The optical USB stick offers very high capability and secured data transportation between two computers. If somebody opens that USB stick that releases a laser beam immediately, 

 https://scitechdaily.com/4k-from-the-moon-artemis-ii-to-trial-high-speed-laser-communications/

https://scitechdaily.com/engineers-build-universal-translator-for-quantum-computers/

https://scitechdaily.com/scientists-just-froze-the-worlds-most-powerful-laser-pulse-in-a-single-shot/

The quantum network is more secure but harder to make than a binary network.

"The universe now has an open, quantum-powered dice roll—free, provable, and ready for anyone to use. Credit: Shutterstock" (ScitechDaily,Spooky Action, Real Results: Turning Quantum Weirdness Into Secure Random Numbers)

"NIST’s CURBy beacon transforms quantum “spooky action” into certified random numbers, guarded by a blockchain-like Twine protocol and broadcast for public use—from jury selection to cryptography."(ScitechDaily,Spooky Action, Real Results: Turning Quantum Weirdness Into Secure Random Numbers)

Researchers created an 11-mile (17,7 km.) long quantum wire that transports data between two systems. This kind of thing makes quantum systems interesting. That photonic quantum highway is the beginning of the more powerful quantum computers and high-power and secure data transmission. 

Because data that is stored in the photon that travels in the network must be well protected, these kinds of experiments act as pathfinders for many other systems like antimatter tools and antimatter and ion weapons. The key element in successful quantum data transmission is that the photon will not interact with quantum fields. 

And the walls of the quantum channel. The same technology is suitable for transporting antimatter particles like positrons and anti-protons. Those tracks can also make it possible to transport antimatter particles to the rocket engines or across the air to selected targets. 

The main difference between quantum and regular networks is this: In quantum networks data that travels in the quantum network is connected with physical particles. The quantum network requires systems that can turn the data that travels in the network into a universal form. And the second thing is that data that travels in the quantum network must be protected. 

The main problem is how to use one quantum channel for transporting multiple data types with multiple destinations. Without the ability to deny data that doesn’t mean anything, that system will turn very busy. The GSM system can send data packages to multiple receivers and guarantee privacy with simple tricks. Every data package that travels in the GSM network is equipped with a small code. 

That code opens the lock to the precise right receiver. At the beginning of the data transmission, the GSM systems like cell phones make key exchange operations. In those processes, those systems exchange keys that allow only selected receivers to open those data packages. The process itself has three stages. First, the transmitter sends a query to the general broadcast address. There, the transmitter asks if the receiver is in the net. Then those systems start to communicate using fixed keys. And in the final step, those systems start to use single-use keys. When data transmission is over those single-use keys will be crushed. 

That should secure privacy. And the other thing is that it makes the receiving system’s operations easier. The meaningless data stays out of the gate because the receiving system rejects that unnecessary data. If that process is done in the system itself that will require lots of data capacity. The system uses single-used keys in that process. The random number generator will make those prime numbers that those GSM phones use in data transportation. The quantum system also requires random numbers. 

The main problem is that the simplest possible quantum systems where the transmitter sends the wire or frequency where it sends data the hijacker can steal data is that the hostile operator knows the data line. The random number generator allows us to solve the right frequency. The random numbers are required in short-term keys. The main problem with the normal random number generators is that they can create virtual random numbers. Those virtual random numbers are generated with computers that use certain types of calculation series. And if the attacker can have the source code for those generators they can break the entire system.

The system must have the capacity to see the right data transporters or qubits before they reach the receiving sensor. That system must have the capacity to aim the wrong qubits, or qubits that involve the wrong dataset to another track. 

https://scitechdaily.com/researchers-build-11-mile-long-quantum-highway-using-photons/

https://scitechdaily.com/spooky-action-real-results-turning-quantum-weirdness-into-secure-random-numbers/