The new method, known as distillation, enhances the effectiveness and reduces the cost of running AI.

In chemistry, distillation means a technique that purifies a material. The same way chemists distillate liquids, AI researchers can distillate AI. Distillation in the human body means that when we move our hands, we don’t need to move our feet at the same time. Or when we order pizza, we don’t want the entire list. We want that certain pizza. In AI, that means that the AI can create a student model that it trains for customers' needs. 

The large language model (LLM) can create a small language model (SML) and customize it. That means the LLM removes all unnecessary things from the SML to make it compact and more secure. The SML is easier to test and it requires less powerful servers than the LLM. There are always mistakes and errors in the LLM algorithms. The problem is that the corrupted AI is not a good tool for detecting errors in its internal code. The human coder must recognize the suspected errors and then fix them. But the problem is that the code can be right, but its target is the wrong object. 

The idea is that the system cleans information in the system. That means that the AI has only responses and actions that it needs for complete missions. The system takes all unnecessary parts away. And that sometimes causes questions about the information that the AI will not need. Humans make decisions about information that the AI needs. And that is seen in things like Chinese AI. Those things don’t discuss things like Tiananmen Square. 

That is one version of distilled information. The system will not give answers that are against the state policy. AI is a tool that can make many things better than humans. But those things will happen in well-limited sectors. The AI can observe things like nuclear reactor functionality. The fact is that the nuclear reactor is not like a chess game. The AI must only keep values at a certain level. The thing in the AI is that it can generate code, but it can use only existing datasets. The difference between a nuclear reactor and a chess game is that the nuclear reactor will always follow certain rules. 

The nuclear reactor will not make anything unpredictable. If the AI knows all its values, the nuclear reactor is safe. But unpredictable values like leaks in the cooling system can destroy a reactor. The programmer who creates the nuclear reactor control systems. That creator must be very professional and collect all data so that the system can respond to all situations. The system must collect information from many sources, such as surveillance cameras and other tools. The system must recognize if some light doesn’t shine as it should. 

That kind of system requires very high-level skills and the ability to train the system for new things. There is always a possibility that the programmer, or the engineer who advises programmers, doesn't always remember everything, such as details of some kinds of damage. That means the AI requires training for that mission. And like always, this kind of thing means that all mistakes that AI makes are actually made by humans. Humans should test and accept that kind of system. And that causes dangerous situations. The training is the final touch in the AI R&D process. 

When we think about things like the North Korean government, they want to use AI in the same missions as Western actors. But do those actors have the skills and abilities to make the final training for their language models? If those language models are made by using some kind of pirated copies that are transported using USB sticks, it can make it possible that the AI and its complicated algorithms don’t work as they should. And that makes those systems dangerous. 

https://www.quantamagazine.org/how-distillation-makes-ai-models-smaller-and-cheaper-20250718/

Ion traps and photons are the tools for next-generation quantum systems.

"By twisting light just right, scientists can now unlock dual hidden images from a single metasurface, ushering in new possibilities for encryption and molecular detection. Credit: Shutterstock" (ScitechDaily, New Tech Uses Twisted Light to Reveal Hidden Images)

The ion traps and twisted light make it possible to create new types of quantum systems. What if researchers can create a particle and trap the twisted light ring around that thing? That could revolutionize quantum technology. If somebody can connect and stabilize twisted light around an ion or electron, that can turn the system into the most accurate scanner that has ever been seen before. The photonic system that can create a “photon smoke ring” and stabilize it around some particle, like an ion or electron, can revolutionize information technology. But that system faces many technical issues. 

But theoretically, artificial brains require ions that play the same role as neurotransmitters. And a photonic system that mimics the brain's electrical actions. Miniature particle accelerators act as axons, and they shoot ions through the axon hole. Information is stored in those ions. 

The ability to create ions, or electrons that twist light orbits, makes it possible to create a system that operates like a human brain. That ion-photon combination can act in the same role as a neurotransmitter in that system. And if the system can trap that combination at a certain moment, that makes it possible to use the photonic data transmission for the messages that require an extra-fast speed. These kinds of systems mimic human brains. The ability to connect photonics and ions makes it possible to use two quantum lines side-by-side in the system. 

One of the most exciting things could be creating the photon ball. Their data transportation photon travels inside this photonic ball. It could be possible to trap the ion-photonic ring inside the fullerene molecule. And that allows the system to transport qubits over a long distance. The long-range qubit will travel in the laser or maser beam. And that thing could make new ways to transport information. The problem is how to make a photonic ring stay around ions? 

The problem is that. Stabilizing twisted light is not a very easy thing. The hollow lasers can make photon rings where the waves or curves are one or zero. The other way is to adjust the hollow laser light’s brightness. The hollow lasers can also protect the data that travels inside them. In those cases, the data transportation laser beams travel inside a hollow laser beam that protects them against outsiders. 

https://scitechdaily.com/harvard-scientists-unveil-tiny-ring-laser-with-giant-potential/

https://scitechdaily.com/lighting-up-the-ion-trap-fiber-optics-built-into-a-chip-for-quantum-computing/

https://scitechdaily.com/new-tech-uses-twisted-light-to-reveal-hidden-images/

Bitchat allows internet-free end-to-end encrypted P2P communication applications.

"Illustration of Jack Dorsey's Bitchat app enabling offline messaging through a peer-to-peer mesh network, generated by artificial intelligence." (RudeBaquette, “Jack Dorsey’s Offline Messaging Bombshell”: Bitchat Launches Peer-to-Peer App With End-to-End Encryption and Zero Tracking for Total Privacy)

Bitchat is a new tool for chatting and communicating. That application offers end-to-end encryption. P2P communication.The new application for P2P messaging and maybe, quite soon, for other data sharing uses BlueTooth for communication. The BlueTooth has its limits for communication. The range for that communication tool is the main problem, and the system requires mesh technology. That means support stations for long-range communication. The other version is to use an extra power BlueTooth device or some kind of amplifier that can increase the range of the BlueTooth. The system can use a standard radio amplifier that raises the BlueTooth power. 

***************************************************

Standard BlueTooth devices have the following classes and ranges. 

Device Power Class Bluetooth Range

Class-1 100 meters

Class-2 10 meters

Class-3 1 meter

(https://www.rfwireless-world.com/terminology/bluetooth-range-and-coverage)

***************************************************

Or a series of mobile telephones with BlueTooth capacity. BlueTooth is a common system in wireless headphones, mice, and other kinds of wireless tools. BlueTooth allows to share an internet connection and share files between devices outside the Internet. That thing makes it possible that the data can be shared outside the network. That can cause some data security problems. The BlueTooth connection requires that the other participant of the session send the access key to the other participant. And there is a possibility to cheat a person into connecting the device to the wrong system. That means the system’s ID is easy to fake. Or there can be a router in a mesh station that sends all data to the network. 

And if the hacker sends the fake ID to another participant using the stolen ID, that means those people can connect their devices to the hacker's computer. The problem is that the ID that the device uses can be stolen or even created by hackers. But the end-to-end encryption protects privacy against internet-based eavesdropping. This kind of system can be interesting. They can replace internet-based data transportation. But there are also weaknesses. And one of them is this. 

Because there are no phone numbers, no internet, and no servers. That means those systems are hard to hack over the net. But there is a possibility of cheating the users into sending data to hackers’ devices. Or there can be a router in a mesh station that can double the data flow. And that can endanger data security. Because BlueTooth range is so short, the need to use mesh stations can endanger data security. 

https://www.rfwireless-world.com/terminology/bluetooth-range-and-coverage

https://www.rudebaguette.com/en/2025/07/jack-dorseys-offline-messaging-bombshell-bitchat-launches-peer-to-peer-app-with-end-to-end-encryption-and-zero-tracking-for-total-privacy/

Bitchat homepage: 

https://bitchat.free/

Black holes and gravitational radiation.

"Two colossal black holes slammed together, forming a 225-solar-mass behemoth so extreme it shouldn’t exist under current theories. Credit: SciTechDaily.com" (Cosmic Heavyweights Collide – LIGO Detects Largest, Fastest-Spinning Black Holes Yet)

Spinning black holes send gravitational waves. This means the black hole’s spin makes it bind energy into it. Or in other words, a black hole collects energy from around it and then turns it into kinetic energy. Theoretically, gravitational waves can form in particles that are just at the edge of the event horizon. 

The model is taken from the centripetal force. When some object starts to spin very fast, that movement pulls energy out from its core to the object’s shell. When spin turns fast enough, energy that travels from the object’s core into its shell breaks that object. In normal cases, atoms in those objects act like antennas. 

And they conduct energy out of the object. In the case of black holes, the gravitational field and interaction around it are so massive and powerful. That ultimate energy field around black holes is so powerful that the energy that comes from black holes will not pass through the material disk easily. The black hole’s interaction is very strong. It pulls material and wave movement from such a large area that the black hole cannot break the whirl around it. Gravitation forms when the gravitational center binds quantum fields into it. 

Sometimes a black hole is separated from its material disk. And that makes it possible that gravitational waves can escape from its event horizon. That happens when a black hole pulls an extraordinarily massive object inside it. When that material and energy boost ends, the black hole sends its extra energy into the space around it. That is one model of the black hole and its ultimate interaction. 

But then we can return to the hollow ball model. Or, rather, saying a spinning hollow ball model where the fast spinning ball pulls energy into it. That means the hollow ball’s shell turns energy around it into its structure. The ball also pulls fields from inside it into the ball’s shell. Or, actually, energy flow always travels to the lower energy side. That means that if the space outside the ball is at zero energy level. That spinning ball can create the energy of a false vacuum. And when that false vacuum falls, it can collect a lot of energy and material into the same point. 

When we think about models. Some so-called dark dwarfs collect dark matter around them, and then collisions between those dark matter particles or weakly interacting massive particles, WIMPs. The annihilation or collisions of those packed particles can cause a situation where dark energy rises so high that the dark dwarf can shine because of those dark matter interactions. When those impacts happen often enough, that thing causes a situation where dark energy interaction with material turns strong enough that it causes visible material to shine.

We must realize that there can be a similar interaction between dark matter and visible material that is much stronger around black holes. There is a possibility that the dark energy that can form in that interaction can push all other interactions, or at least electromagnetic interactions, away from the black hole. That can cause the footstep at the front of the particle.

Normally, when a particle faces electromagnetic radiation, that radiation or wave movement makes a shadow behind that particle. The electromagnetic radiation pushes particles into that shadow. 

That means the electromagnetic shadow that pulls particles out from the radiation center turns into a higher energy level than the area at the front of the particle. That thing makes the pulling effect so strong that the particle cannot escape from it. 

The particle sends a photon at the front of it. Or the photon that forms at the back of the particle turns so high energy that it forms the shadow or channel at the front of the particle. And that thing causes the particle to start to fall into the black hole. It’s possible that around normal gravity centers, only the field transports the particle. But when the particle comes closer to the black hole, there is something that causes the shadow to move in front of the particle. That shadow or quantum low pressure will raise the force of gravity. 

https://scitechdaily.com/cosmic-heavyweights-collide-ligo-detects-largest-fastest-spinning-black-holes-yet/

The new components can boost the AI.

"A new discovery in atomic-scale magnetism may hold the key to the future of high-speed, compact, and energy-efficient technology. (Artist’s concept). Credit: SciTechDaily.com (ScitechDaily, Researchers Solve Long-Standing Magnetic Problem With Atom-Thin Semiconductor)

When researchers make new applications like autonomous robots, those systems require new types of advanced microprocessors. Things like advanced algorithms require effective microchips. And effective microchips allow developers to develop new and more complicated programs and algorithms. When developers create new systems, they often encounter a new need that they need to solve. Even if developers use effective and compact programming languages, the code grows and becomes complicated. 

And complicated code requires new processors that can drive it without problems. The problem is that in small-sized systems, smaller processors. And smaller processors require new types of architecture. In larger systems, it is possible to put more small processors in the same space. And that gives new abilities for multitask systems. The number of processors determines how many operations the computer or data center can perform in the same time. And that is the key element in the large language models and self-developing AIs. 

"A schematic representation of magnets composed of CrPS4 included in a motherboard circuit for future electronic devices. Credit: Elton Santos" (ScitechDaily, Researchers Solve Long-Standing Magnetic Problem With Atom-Thin Semiconductor)

The main problem with AI is the need for power. Powerful microchips require lots of electricity. And that electricity brings temperature problems. The temperature problem means that the resistance in the system rises when the temperature rises. Sooner or later, that starts the accelerating process that destroys the system by cutting wires. The result is a cooling system that requires lots of energy. The AI can use nuclear reactors, solar panels, or geothermal energy. The system should produce its energy. Miniature nuclear reactors or geothermal energy are the most stable versions. 

There are attempts to remove the oscillation by putting those wires in the water tubes and raising the pressure in the system. Rising pressure decreases oscillation, which causes resistance. And theoretically, it is possible to create room-temperature superconductors using high-pressure systems. The main problem is what if the pressure system faces damage? Leaks in the high-pressure system are dangerous for people and systems in the same space. 

"Artist’s illustration of the new tunable ring laser. Credit: Joshua Mornhinweg" . "The ring design has potential applications in telecommunications, medicine, and other fields." (ScitechDaily, Harvard Scientists Unveil Tiny Ring Laser With Giant Potential) A ring laser can be used as a photonic box wrench. That can adjust photons' and atoms' energy levels. 

The other way to solve the temperature problems is simply. Create photonic processors where photons replace electricity as data transporters. Laser rays can transmit data between microchips, and in that model, the microchip itself is traditional. And the wires that connect microprocessors in one entirety are replaced by laser rays. The laser rays transmit data to the processor through the photovoltaic cells. Or certain wavelengths or colors in laser rays, like green and red, can mean zero and one. 

"Schematic of tailoring the resonant reflection via radiation directionality in misaligned metagratings. The novel bilayer metagratings selects only a single angle and a single wavelength under incidence with broadband spectrum and wide angles. This is achieved through a “directional eraser”, that precisely suppresses light’s spectral signature along a dispersion curve. Credit: Ze-Peng Zhuang, Xin Zhou et al." (ScitechDaily, One Tiny Structure Just Broke a Fundamental Rule of Optics)

Fully photonic processors require new ways to control light and optics. The new materials allow the closure of the route of light. And then open that route. When light travels through a material, it gives value one for a microchip. And when material blocks light, the value is zero. 

In quantum systems, each color can mean each quantum state. There is also the possibility of sending laser rays through the nanotube that is used for electric transmission. That laser ray acts like a thermal pump. The fully photonic system, where all data travels in photonic form, can also have the ability to use the ion flow as a cooler. The ion system can transport ions through components. But the problem is that those systems disturb the electricity in the microchip. 

The 2D materials allow the system to transport heat out of the system. That makes it possible to create smaller and more effective processors. Those systems, like tiny ring lasers, can transport data to those 2D structures. The 2D network can have the silicone base photovoltaic points where the laser systems transport information. 

The idea is that those photovoltaic cells transform photonic information into electrical impulses. And that can make the system more effective. There is a possibility to use laser light as a thermal pump. An extremely thin laser ray travels between those layers and transports thermal energy out from the processor. 

https://scitechdaily.com/harvard-scientists-unveil-tiny-ring-laser-with-giant-potential/

https://scitechdaily.com/one-tiny-structure-just-broke-a-fundamental-rule-of-optics/

https://scitechdaily.com/researchers-solve-long-standing-magnetic-problem-with-atom-thin-semiconductor/

The Gemini AI refuses to play chess against antique ATARI chess computers.

The Gemini AI refuses to play chess against the ATARI chess computer. And why does that system make that decision? There is a model in its algorithms that it uses to compare models and probabilities. And because two other AIs lost the match, that means it's more probable that Gemini loses the chess match than wins it. The other thing is that the AI is programmed to be polite and also serve commercial use, which means the AI translates that loss as bad for its own and its background company’s reputation. 

The reason why Gemini is considered polite is that the company wants users to like their product. This is the main problem with commercial AI development. The purpose of that thing is purely to make money for the companies. Not to serve the national interests or scientific work. This is why AI is sometimes misunderstood. They use things like mathematical statistics and other things to advance trust between it and users. And the other thing is that the AI must also support its users' willingness to select the AI service that benefits the company, behind the AI and LLM. 

The ATARI game consoles from the 1970s are not so easy to win, as we expect. If somebody played chess against those chess machines that used an interactive chessboard where the chess buttons had a digital ID. The player must also move the computer’s chess pieces. And the computer shows movements by using light pairs that point at the button. And then the system showed the point where the system wants to move the button when it notices something in those chessboards. The player must move the button as the chess computer wants. If the player didn’t follow the order, the system just repeated “that was not my move”. And refuses to continue the game. 

Or when we look at the discussion that the AI had about that match, the beginning was that the AI told how powerful it is, and how many moves it can calculate before, but then in real time, the AI refused. The AI could “think” that if it loses a chess game to some antique game console, that’s bad for business. 

The fact is that the ATARI is the RISC machine. Its only purpose is to play chess. There is a limited number of movements in chess. And that’s why chess is one thing that is used for AI development. The AI can make multiple models to make moves. But the AI must have knowledge of how to play chess. In the world of AI, that means the AI creates a new dataset for the action. And when AI expands its skills, that means it just makes or loads a new dataset for it. 

The AI will not think like we do. It creates datasets and combines data from different sources. Most of the hardware systems that run AI or language models are so-called neurocomputers. In a neural network, each computer can operate as part of the entirety or independently. The problem with every single neural network is that they need chess programs to play chess. In chess programs, every game or tactic that the system uses is a database or dataset. 

The next step is that the system must analyze each of the games stored in the chess program. And then that system must find the right game and find its counter game. Those games are tactics that the system must use. The problem is that the AI can find more games or datasets on the net if it has instructions for that thing. The AI doesn’t praise itself as we do. It simply tells things about the systems that run it, if it has the permission to give that answer. If that is not permitted, the AI can tell that it cannot answer. Or it can tell lies if there is a dataset that involves lies. The computer doesn’t even know if it is lying. The dataset involves all answers that the computer can give. 

https://www.freethink.com/artificial-intelligence/ai-datasets

https://futurism.com/google-ai-refuses-chess-atari

https://www.tomshardware.com/tech-industry/artificial-intelligence/google-gemini-crumbles-in-the-face-of-atari-chess-challenge-admits-it-would-struggle-immensely-against-1-19-mhz-machine-says-canceling-the-match-most-sensible-course-of-action

Can Sci-fi weapons: nanomachines and sophons be a reality someday?

 

The grey fog is one of the superweapons that are so horrifying that we cannot even imagine them. That grey fog can erase entire planets. Nanomachines are the new tools. They can be the ultimate Swiss blade for everything. Theoretically, nanomachines can erase any molecule that they face. Those small molecular machines must only create the wave movement and resonance that cut the chemical bonds between atoms. The miniature machine can simply send an electromagnetic impulse to the chemical bond in a targeted molecule. And that energy can push atoms away from each other. This kind of system can have multiple civil and military applications. 

The nanomachine that can terminate forever molecules can be the most wanted thing in the world. But that same technology is also capable of creating the terrifying “grey fog” that terminates everything that we know. The main problem with nanomachines is their movement. The surface active agents, or surfactants are the things that can solve the nanomachine movement problem. If the nanomachine has two surfactant molecules that the system can turn on when it gets a command. That makes it possible to move the nanomachine. Surfactants have two heads, one is hydrophobic and one is hydrophilic.

If the hydrophobic head is in the direction where nanomachines should move and the hydrophilic head is at the tail of the nanomachine. That makes the nanomachine move in the desired direction underwater. The hydrophobic head that can be connected with water droplets can also make the nanomachine hover and travel to wanted direction in the air. When the water droplet surrounds the nanomachine and then the hydrophobic- or water-repelling heads are turned to that water. That thing can cause an explosion. And the pressure wave can help to raise the machine up. The small nanomachine that can control that thing can make it possible to use that thing for controlled flight. 

The other version is that they use some. more exotic propulsion systems, like theoretical systems that can change the shape of the quantum fields near the nanomachines. Those systems can make the machine hover and travel at very high speeds. 

Those nanomachines can be connected with the von Neumann probes. The term Von Neumann probe means self-replicating machines.  Those systems can include miniature factories that create copies of those machines. The nanofactory can be very small. And they can create copies of themselves and create those molecular machines. Those machines and factories can be DNA-controlled. 

The sophon is introduced in the sci-fi novel 3-Body Problem. The sophon is a proton-sized quantum computer that can control humans and steal their imaginations and thoughts. The model of sophon is in the real quantum models where the proton, or quarks that form this hadron will be put into the superposition and entanglement. This kind of quantum computer is very unstable. There are models made of what those sophons can be. And one of them is that the sophon could be the group of photons that are trapped around the quantum-size black hole. The other version could be the quantum-size grey hole. 

The system creates those things by pressing some particles like protons with antimatter implosion. The ball-shaped antimatter-matter ball will be exploded around the proton. That thing can be the fullerene that acts like an implosion bomb. And then photons will be put around that extremely dense object. And the system will transport data into them. 

But there is another way to make the theoretical sophons. That is the DNA-based quantum computer. The system can be an artificial bacteria or an artificial amoeba that is injected into the target’s blood. There, genetically engineered amoebae can travel to the human brain. Then that thing will steal the electric impulses or make copies of the neurotransmitters in that thing. 

When the artificial amoeba or biorobot is ready it calls the genetically engineered mosquito to pull it out from the blood vessels. 

The artificial mosquito can use certain chemical marks, antibodies to call the artificial amoeba to it. And that amoeba can also send neurotransmitters to neurons around it. The system mimics the natural parasites. But their purpose is different. Their mission is to paralyze and steal information from the targeted person's nervous system and even control that person. 

Then that mosquito travels to the laboratory. And there are many ways that that thing can transmit data to the computer. The mosquito can split that amoeba on the research table. Then the amoeba starts to blink the bioluminescence light and using that light the biorobot can transmit information that it got to a photovoltaic cell. The amoeba can also reprogram the mosquito and make it communicate with computers. The artificial amoeba-mosquito couple can be the ultimate tool for intelligence and other systems. 

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.