Curvity is the new way to control the drone swarms.

 Curvity is the new way to control the drone swarms. 

"Illustration of robots advancing artificial swarm intelligence inspired by the collective behaviors of birds, fish, and bees."(Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Drone swarms could be the tool that can make almost everything. The idea is that drones can cooperate and connect their computing capacity when they must make complex decisions. Then the swarm can share missions to individual drones. When we think about robot swarms that can mimic things like bird swarms, those robots must know their position in the swarm. The answer to that question can be curvature or curvity. Rude Baguette tells the next things about curvity. 

“A key innovation of the study is the introduction of a new quantity termed “curvity.” This intrinsic charge-like quality allows a robot to curve in response to external forces, guiding its interactions with fellow robots. Each robot is assigned a positive or negative curvity value, which determines its behavior within the swarm. This innovative approach allows for the collective behavior of the swarm to be controlled, whether it involves flocking, flowing, or clustering.”  (Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Assistant Professor Stefano Martiniani from New York University emphasized the potential of this approach: “This curvature drives the collective behavior of the swarm, potentially controlling whether the swarm flocks, flows, or clusters.” Such a model transforms the challenge of controlling swarms from complex programming into a material science issue, opening new avenues for research and application.” (Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Sharing the system into substructures that mimic galactic groups makes it easier to create programs for robots. Each layer or level acts as one robot. 

The system can involve the next type of information. 

“You are a robot of robot group 9. Robots 1 and 2 must be ahead of you. And robot 4 must be on the left side of you. Together, you are Robot Swarm 2, and Swarms 1 must be on your side, and Swarms 3 and 4 must be behind you. Together, your place is in layer 3. That layer must be between layer 2 and 4.” Then the system has other algorithms that tell what to do if one drone is lost. 

The key question is how the robot can determine its position within the swarm. In this case, the modular structure is the solution. There can be multiple data levels, which makes the data structure operate as a mosaic. Or, rather, we can say that the structure mimics the universe. There are individual drones that are galaxies in galactic clusters. Then those drone clusters form a local cluster. Then, local clusters form a super cluster. And then the superclusters form a global cluster. Those clusters are the drone swarms. The ability to share the groups into subgroups makes it easier to program those drones. 

The idea is that the drones can form three or four drone groups. The individual drone knows. What drones are behind it, and what drones are ahead of it? The drone group acts like one drone. And then it must know what drone group is ahead and behind it. Then the drone group must know. Whether it should be above or below some of the other drones. The system can make that quite easily. It can share the drone swarm into layers. And those drones know their own layer. And then they know what drones should be below and what should be above it. Those drones can operate in squares. That can look like randomly changing forms. 

https://www.rudebaguette.com/en/2025/09/curvity-controls-robot-interactions-researchers-develop-new-framework-allowing-robotic-swarms-to-mimic-bird-and-fish-group-behaviors/

How to simulate the entire universe using a laptop?

    How to simulate the entire universe using a laptop? 

How to simulate the entire universe using a laptop? And can psychohistory be possible? 

The idea is this. If we want to simulate a large entirety, we must not have high accuracy. If we want to make a simulation about. How a river flows, we can use the entire river as a model. We must not care. About how a single water molecule or subatomic particle behaves. We must only know where the river flows. To make a prediction about how the river will flow, we must only know where the softest rock is to predict the channel that the river will choose. In meteorology, supercomputers can make very good predictions. If they know the forces that affect the air. In those cases, the system. Look at the entirety. It doesn’t try to make a precise and highly accurate model of how a single water droplet interacts. The system observes the large entireties. Like cloud groups to make a model, how the air mass will behave. 

Weather satellites and computers are good tools. To predict how large hurricanes behave. But those systems are helpless. When they must try to predict how tornadoes will form. Tornadoes are smaller but more destructive than large tropical storms. Tornadoes are too small for weather satellites.

Maybe. The same programs can make predictions of tornadoes. If the system uses so-called atmospheric satellites that observe smaller areas but with higher accuracy. Those systems will get information from smaller areas. But they can use similar computer systems. Researchers used to make a large-scale weather forecast. In this case, it's easy to make a planet-scale weather forecast. But those forecasts are inaccurate. 

In the same way, it's easy to make predictions about how large gas mass behaves. The system removes unnecessary accuracy and handles things like galaxies as solid forms. Those are like pins in the large system. Or maybe we should say that galaxies are like wheels. Those wheels move wave movement, fields, and large material masses over the universe. 

That means if we make inaccurate, “about” predictions. About how large gas masses are. Like galactic superclusters behave, we can make that prediction using laptop computers. In an inaccurate model, we can think that galactic superclusters are the wheels, and the universe is like a ball around those wheels. When the system starts to simulate how the galaxies behave in a local cluster. The system uses the local cluster as a scale, and galaxies are wheels. When the system makes a model of how a galactic supercluster behaves, the local clusters are the wheels. And the last version is the universal scale. The galactic superclusters are the wheels. In the large-scale simulations. The system doesn’t notice or filter out too small actors that have no visible effect on the system. 

This system is called. A variable scale model. The idea is similar to the U.S map. If we want to look at the overview of the weather over the USA. We can use the USA as a whole. But if we want to see what the weather is over in Montana. We can take a Zoom image of the state of Montana. We can use the same computer algorithms in that area. As in larger-scale images. But the higher accuracy means that we lose the entirety. 

Ludwig Boltzmann (1844-1906), Austrian physicist

Can the psychohistory turn true? 

There is a possibility that the same models. Those used for simulating the universe can be used to predict how humans behave. That is called psychohistory. In the SciFi series: “The Foundation”. The idea is that the system predicts the behavior of large human groups. The system uses large human groups. And things like their states’ influence as variables that can predict how people behave. The system makes models. Using billions of people. But if that thing is possible. The system can use the same algorithms for smaller groups. 

In psychohistory, the system looks at things. That happened in the past. Then the system searches for what those things caused. And then. The system searches for details of similar events from its environment. Because people with similar personalities should behave in similar ways in similar situations. So, the system must know. How many certain types of personalities live in an area that faces certain changes? We can think. Human groups have a certain social or psychological mass, and if a certain number of people start behaving in certain ways. That psychological mass can start to pull other people with it, only if it's large enough.

The thing that causes panic is that a certain number of people in a group start to panic. When we think that four people start to panic, that might not seem like a very big thing. But if there are 10 people in one room. And there is one square meter of space. For each person. Then four people will get the larger effect. And one of those reasons is that. There is no outside effect that can suppress the panic effect. And that makes it stronger. If the head of state goes into panic, that can escalate into a very large group. If one single person goes into panic, that has no such effect. 

And then to psychohistory: can we predict how people or nations behave? Every person. With a certain personality. Behaves in certain ways. The thing that makes predictions hard. Is that. We should know. What a person’s personality is. And that’s impossible if the researchers don’t know the entire personal history of the person. 

We can take the scale of millions or billions of people. When we think about psychology and economics. There are inaccuracies. The reason for those inaccuracies is that we don’t know every person’s background. People’s experiences model our behavior. Psychological models are almost right. And they work with most people. But those models are not working with people. Whose nature is not known. We don’t know what type of humans they are if we don’t know that person’s complete history. The personality is unknown, if there is something hidden in history. 

But there should be a certain number of  non-predicted cases. Or a certain type of standard deviation  of cases that behave in a non-predictable way. This means that large, scalable surprises are not very common cases. in large-scale models. Cases like the Kennedy assassination are very rare. They are like black swans, possible but extremely rare things. There must be an acceptable  error level in all models. Some of those black swans can be predicted. We can calculate the possibilities of asteroid hits, but there is a possibility. That some asteroids can come through the defense. Sometimes asteroids are seen. Only when they pass Earth and those things cause problems. 

https://scitechdaily.com/scientists-just-found-a-way-to-simulate-the-universe-on-a-laptop/

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

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

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

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

Researchers sent quantum information through the commercial network.

 Researchers sent quantum information through the commercial network.

“A Penn team has shown that quantum signals can ride alongside everyday internet traffic on commercial fiber. Their “Q-chip” experiment marks a step toward a scalable quantum internet with world-changing potential. Credit: Shutterstock” (ScitechDaily,Engineers Bring Quantum Internet to Commercial Fiber for the First Time)

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“A new integrated chip demonstrates how quantum networks could communicate using today’s internet protocols over existing commercial fiber-optic cables.”

“In a groundbreaking experiment, engineers at the University of Pennsylvania successfully extended quantum networking beyond the laboratory by transmitting signals over commercial fiber-optic cables using the same Internet Protocol (IP) that drives today’s web. Published in Science, the study demonstrates that delicate quantum signals can travel on the same infrastructure that carries routine online traffic. The tests were carried out on Verizon’s campus fiber-optic network. “

(ScitechDaily,Engineers Bring Quantum Internet to Commercial Fiber for the First Time)

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Researchers have introduced a method that allows sending quantum information alongside binary information. That is a significant step toward creating new and more secure quantum networks that can enhance communication safety. And that can make it possible to create new and powerful quantum computers, where those computers can send data in the form of a qubit. There is a possibility. To send a qubit along with binary data using a very thin light wave or laser beam. Then the photon, where the system stored information. Travels around that light string. The quantum information is stored in the photon. And that makes it possible to transport data in the quantum model over long distances. 

But the reality is this. The system must protect data that is stored in a qubit. It’s possible that the system can transport data in a regular optical cable in quantum form. The system can share information between optical fibers. And that forms the virtual qubit. In this case, we can think about the optical cable. There is one fiber in the center and five fibers around that central fiber. The system can share information with the fibers around the central fiber. That means those optical fibers around the central fiber act as a virtual photon. The ability to transport secured information over long distances is a key element in modern communication. 

Photonic data transmission and computing are the new tools for computing. Photonic communication makes networks immune to regular ECM systems. If we use quantum communication. The quantum system increases security to a level that we have never seen before. When information moves from a qubit to a sensor, the qubit loses its energy level. If a qubit travels in a fully controlled environment, the system can calculate how its energy level changes. 

When something looks at the qubit, it changes the energy level or destroys the entire dataset. When a qubit travels in its quantum channel, the system must touch it so that it can release information stored in its internal superposition. That can happen using radiological stress that can force the qubit to release its information. Or the system must make a qubit to send its information to another particle. But that destroys information from the qubits. And in fully secured data transmission, the system can transport information, sharing it with multiple qubits. 

Coherent radio waves can make it possible. Researchers can create room-temperature quantum computers. The system can use different radio frequencies to make the qubit. Each radio frequency in coherent radio waves is one of the qubit states. 

But we know that the photonic data transmission is only one of the ways. To make quantum data transportation. It’s possible to send the data through the hollow nanotubes or hollow metal cables. The system can use coherent radio waves and skyrmions. That travels around that electromagnetic fiber. The structure around the channel protects the signal from outside influence. 

The data that travels in the channel is safe; if somebody tries to affect that data, that actor must break the tube or quantum channel. That causes disturbance in the electromagnetic fields. And the resistance in the channel structure. This tells the system that there is damage in the quantum channel. 

https://scitechdaily.com/engineers-bring-quantum-internet-to-commercial-fiber-for-the-first-time/

AI and the end of the world.

 AI and the end of the world. 

The end of the world can start. When the AI-controlled defense systems start to use weapons in a crisis.  In simulations. AI used weapons more sensitive than humans. This means that the AI is not suitable for making decisions in cases where the crisis has not yet escalated. Into weapon use. The AI can choose nuclear weapons more often than humans in those simulations. Here we can see one of the most frightening. And at the same time, interesting ways in which AI “thinks” about those simulations. 

The AI takes those simulations as a chess game or some other game. And the AI’s goal is to win the game. That means the AI takes the most effective and powerful weapons. Another thing is that the AI always selects the easiest models that are possible. There is one big difference between humans and AI. That difference is that the AI doesn’t think like we do. The AI doesn’t care about human victims. 

The only goal that the system has. It is to win the game. The AI plays these kinds of strategic simulations like it plays regular games. In the same way as some Atari chess simulations, the AI has certain points in losses when it takes a nuclear arsenal to use. When the AI reached a certain level of losses. It saw that it needed more firepower. The problem with the simulations is that they are never. Like real people. 

Simulating real crises is a little bit more difficult to create. Than some shooting games. Those systems require psychological aspects. The thing that causes uncertainty in those simulations is that AI or any human participants in those simulations don’t think like Putin or Trump. They don’t know how big a price real leaders are willing to pay. The lack of a psychological aspect is the thing. That causes problems with the AI. The AI plays to win the game, and the clearest way. To win the game is to destroy the opponent. This is the thing that causes very big problems. If somebody wants to negotiate, the AI will not recognize that action. 

There is a possibility that AI attacks anyway, because it analyzes actions that somebody plays over time and position to make an attack. The AI analyzes games like this: the side that has fewer points or units is losing. And that means the AI doesn’t think of casualties, like humans. It only thinks that the opponent must have fewer points. This makes AI dangerous. If it translates to negotiations and withdrawal causes a loss of points. That makes the AI attack enemies. The AI makes those things because it is programmed to keep its own points higher than its opponent's points. And that can cause a catastrophe in real life. 

https://www.politico.com/news/magazine/2025/09/02/pentagon-ai-nuclear-war-00496884

The mosaic model can be a novel approach to creating AI.

 The mosaic model can be a novel approach to creating AI. 

The regular model for creating AI is the large language model, or LLM. That means that. Developers must have control over large data masses. And large code structures. All large code structures are complicated. Because they involve a lot of code. And there are always some kind of errors in the code. That means, when the number of code lines increases, there are more possibilities to make errors. Making the AI is like making a statue. When the system turns more sophisticated. And more advanced, the development process turns slower. When we want to make statues, the first steps are always fast.

 But when we are closing the goal, finishing details takes more and more time. The finishing process just before the statue or product is ready for delivery to customers. Takes most of the time in the development process. The same way. Finishing and detecting errors from the data structure takes most of the time in the programming process. The problem is this: the LLM requires many event handlers. And each event handler is an independent algorithm. That means LLM is a large number of algorithms that operate as a whole. 

The problem is that the LLM rises like dough. That means there are more and more algorithms that must operate as one system. And when the code mass. And the data mass that the system operates on is both large. There can be lots of errors. The AI is a tool that can detect errors in other programs. But the system is not very effective if it must search for errors in its own code. The outsider algorithm can make error detection. AI needs a model. That it can compare its code to. With the code model. Actually, the outsider AI makes the comparison process with two other language models. 

And the problem is: when a new AI model comes. There are no models that the developers can compare their code to. Without models, it is impossible to compare even billions of code lines, which can involve minimal errors. But when there are billions of code lines, and let’s say. There is an error in 1000 lines; searching those codes is a long-term process. That requires carefulness. 

The modular, mosaic model helps expand the AI. 

The mosaic structure or the morphing neural network. That can involve multiple independently operating small language models. It can make it possible to make a flexible and elastic system. Every brick in the mosaic structure is an independently operating server that runs an independent small language model, SLM. Each SLM is a module that involves a certain skill. If the system doesn’t need a module. It can put the server that runs the module into sleeping mode. That makes it more energy efficient.  When developers want to give a new skill to the AI. They can make a new SLM and then connect. That thing to the entirety. 

Researchers say that the future belongs to small language models, SLMs. SLMs are lighter; they involve less code, which makes the development process easier to handle. The SLMs can also operate as a whole. This means: each SLM can operate independently. But those things can also form the virtual entirety. That entirety is like a mosaic. Each SLM has certain skills. When the user sends signals to the system, the SLM knows. If it has that skill or capacity. If the SLM doesn’t have a match. That system forwards the message to another language model, which has the database. That involves data about the SLMs and their skills. And the system sends that information to SLM, which can make the job. 

The idea is that each bite of the mosaic can be written independently. Which means developers can make new modules for AI. And then collect them into  a mosaic. The mosaic-type developing means that. Programmers can control the code better. That also decreases electric use, because if those modules or parts of the mosaic are not required, the system can put its servers to sleep. A mosaic model or morphing neural network structure allows developers to make an elastic and flexible system. 

The long-term data storage problem.

 The long-term data storage problem. 

When we think about long-term data storage. That resists electromagnetic radiation, magnetic fields, and physical damage, we can think about things like films, where data is stored in the form of barcodes. Those barcodes can be stored. In the microfilm, each frame can be protected using armored glass. The computer can read that data using the microfilm reader. If there is a CCD camera mounted in the system. The system can use a projector and the film. That barcode travels through that system. The computer can have a simple operating system that allows it to read those barcodes and then decode that data into the computer. The barcodes can have like two thin lines, which represent zero, and one wide line can represent one. The system can have certain code that tells the end of the program. 

Or code sequence ends. But if the system uses a geometrical form. like squares, triangles, crosses, and circles. That thing makes creating the new type of quantum communication possible. The square can be one, the triangle can be zero, and the circle can be the operator that tells that the code line or program’s code is ended. Basically, those geometrical shapes that the computer reads and transforms into programs can be letters. B can be 1, A can be 0. The system can take any letter group from the alphabet. The system requires marks to separate two zeros and show when the program ends. That makes the data system faster. 

The ability to store data in chemical form can be a game-changing way to store information. But can there be a practical way to make that thing? Sometimes futurologists say that they will store data in the DNA. molecule. And that is one of the most exciting ways to store data. Artificial cells can transmit that data into computers using bioluminescence, which flashes are ones and zeros. Or those artificial cells can send electric impulses to a computer. And that is one way to store information. But there is another way. To make chemical data storage. That doesn’t require the ability to code DNA molecules. 

One way is to use carbon-chloride molecules. Those chroride-carbon chains are flat. And there are  ways to make that thing. 

1) The choride-carbon chain is the one. And the intermediate is zero. Those molecules can be put under the glass. And then the system can read those molecules. The length of the intermediate determines. If there is a zero or a break. 

2) The system can involve two types of molecules. The first molecule is one, and the other one is zero. Those molecules can be stored under the glass plates, and the microscope reads data, which is stored in those molecules. 

3) The system could be faster if there were different molecules that show the zeros and ones. And if there is a molecule that shows the break. Or the endpoint of the code. There should be a separator that determines. When there are two zeros after each other. The system must also be separated. If the power is shut down or if there is only a break when the system waits for a new program. That makes those systems faster, and they don’t require a clock as much as electronic binary systems. 

A simple way to store data is to use images or a series of geometrical images to store and transmit data. The geometrical forms can be 1, 0, beak, and the end of the code line. Chemical and optical ways to transmit data. This is the thing. That makes data transportation safe. The data that is stored in the form of molecules can be transported using protein tapes. 

Activism as an influence tool.

 Activism as an influence tool.

Terror is a dirty tool in foreign politics. And terrorism is the most dramatic and aggressive form of activism. 

Many people think that activists are always operating domestically. The fact is that the KGB has always tried to use activists as a tool whose purpose is to break NATO. The peace activists got courses. And guidance from the Eastern European intelligence. Some activists got equipment. Like propaganda material. Guidance on legal methods, so that they could resist the police. And in some cases, the large activist groups got leaders, commissars. That was trained by the KGB. The KGB gave those people things like drugs that gave them their position as leaders of the gang. That propaganda material included images of dead children's bodies. The thing that the KGB forgot is that the Soviets also used napalm, cluster bombs, and extortion in Afghanistan and their other operations. Another thing that the Soviet Security police used was raping. 

Sexual violence’s mission was to make a canyon between the Germans and other occupied nations and Soviet troops. When the Soviet army occupied Eastern Europe and Eastern Germany, those people were classified as ideological enemies. That means Stalin’s headquarters wanted to prevent those ideological enemies from spreading their propaganda to Russian troops. And another thing was that. The soldiers who operated in the occupied territories must remain silent. So Stalin created one of the most disgusting tactics in the history of war. That thing was sexual violence. Rapings were things that created a distance between the Soviets and other people. The problem with the Red Army was that there was not enough political training to “resist that influence”. And that made this system, or apparat, a threat to Stalin. Or the purpose was to play good and bad cop. The good cop was the NKVD, the secret police. And the bad cpop was the Red Army. 

There are tales that commissars ordered their men to make those disgusting things. And sexual violence offered an excuse to put those men on court-martial and order the secret police to shoot them. In that case, Stalin must not say that the arrest was political. He must just show the crime. Stalin’s idea in that brutal game was simple. The Red Army committed crimes. And the political police were the thing. That supports and protects people. So the purpose of that brutal action is to make the secret police and state leaders look like good guys. And I think that Putin and the FSB follow the same route in Ukraine. 

But then to the modern days. 

Cyber is the new battlefield. And the cyber is the key to the next-generation propaganda and other psychological operations. The ability to break into information channels opens a route to hostile cyber influence against society. This makes it possible to share disinformation through trusted channels. That disinformation can be used to break relationships, support friendly politicians, and undermine trust in authorities. 

By recruiting NATO countries' citizens, it is easier for the FSB than to make strikes using their own people. If those foreigners. Friendly operators will be arrested . The FSB can claim. Those people operated on their own initiative. Making sabotage against things like electrical substations is not very difficult. People can throw stones at insulation or shoot those ceramic insulators using an AK-47. In the same way, if somebody jams aircraft navigation, it's easy to claim that those actions are only lies or a product of imagination. The key element in those operations is this: Everything is always denied. Foreign actors operate with minimal training. They can be criminals like narcomen who get drugs or guns from their services. 

Those activists are always poorly trained. Which makes them receptive to disinformation. Sometimes their leaders play professors or some kind of doctors, “who disagree with their university's values”. So they sold their houses and other things that they owned and went to search for “ a real world”. There in the far east, those people realize that communism is the only thing that is accepted. The real reason could be that those people used drugs or were fired because of pedophilia. 

Things like jamming aircraft navigation signals are meant to deliver fear. This kind of thing is used to give a signal that the decisions people made are not accepted. And if people give in, those attacks will end. This cheating is targeted against high-ranking deciders. The idea is that the terror will make them give in, and then they will escalate that throughout the entire society. This is why things like aircraft are excellent targets for that kind of influence. When terror is targeted at high-ranking leaders. That requires fewer resources. When we think that a leader has an automobile, it’s easy to put the paper on the windshield, there is text, “this could be the bomb”. 

Or the activists, as some media call them, can pop a tire from those cars. The fact is that the car is a good indicator. When some people use cars. Observers can follow those vehicles and then connect them to the person who is targeted by activists for that action. This is one way to influence leaders. 

The method in far wing radiacals is always the same. They use hybrid methods for recruiting. The idea is that most of the objects that those radicals support are acceptable. But some of them are not. Or their methods are not acceptable. The tool that those people use is fear. Their message is always that “they could be armed, and they remember your face”. In many cases, adult people lead underage actors. Adults tell youngsters what to do. Sometimes, there are pedophiles who are using those groups as sex objects. The idea is that sometimes the actors find people who have nothing to do. 

Then they offer things that give their lives a purpose. And then those outside, adult actors will raise the leaders of the gangs. They can offer drugs that help them to keep their position. The image is always the same. The adult leaders raise the sub-leaders in the group. This hierarchy makes things easier. First, they came to tell that it’s easier if only a couple of people come to take orders. And then those “chosen ones” will share the works with the activist groups. 

Those sub-leaders share orders, whose mission is to paint banderolles, and whose mission is to get transportation. Like bus tickets. Those leaders are marked with a different color. Those groups also have a kitchen team, which involves the cooks. And the people who collect garbage. And the people who work with garbage are the newbies or lowest-ranking members.  They should earn their promotions. But, as we know, some of those people are more liked than others. 

The idea in information operations, also called psychological operations, PSY-OPS, is that the hostile actors support actors who are useful to them. Those actors can be far-side nationalists. Or, selfish businessmen who want to do business with dictators. The useful actor is the actor that breaks the line at the front of the hostile actors. In cases like Russia, far-right nationalists serve the regime on both sides. 

The far-right nationalist government breaks NATO, and they also act as a tool that serves Moscow's propaganda machine. That propaganda introduces Russia as a nation, which is surrounded by hostile actors, whose purpose is to destroy Slavic culture. And the only thing that can protect this culture is Russia with its nuclear weapons. In Russia, nationalism serves the military and the high-ranking nomenklatura. 

Hacking as the new and old threats.

 Hacking as the new and old threats. 

There are always suspicions that organized crime uses hackers to steal psychiatric papers to get policemen, prosecutors, and judges fired. Same way. Fake papers can also be a tool that allows people in foreign intelligence to make military forces. To kick off their best commanders. Sensitive information can be used to blackmail even top-level politicians. 

Hackers are people who steal data. Some of that data is harmful, or it contains personal, sensitive information. That kind of data can be a very effective tool if someone wants to destroy someone’s reputation. Hackers can steal data from psychiatric services and try to blackmail politicians. One of those cases was the Vastaamo case, where a hacker stole client information from a psychotherapy company. That hacker also sent a SWAT team to a person’s home and marked one aircraft passenger as a bomb carrier. Hackers can also make things like deactivate the payment cards of their victims. 

Or, in some cases, hackers simply steal money from accounts. If a hacker steals 1 euro. From 10,000 bank accounts. Those victims might not even notice that thing. Or do you follow every euro that is lost from accounts? If there is a loss, let’s say 1 euro, do you call your bank? You should tell that thing. Because in those cases, hackers steal a small sum from many accounts. But are hackers evil people? Some of them are. Some of them enjoy their crimes, and they want to hurt people. 

Being an effective hacker. You don't have to be a computer genius. You must only have access to passwords. One unprotected telephone on the desk gives a hacker access to the entire system. If a telephone is left open on a table, the hacker can call the IT support. And ask for access to the system. If that is some very high-level boss's telephone, that makes it possible to create a super user’s access to the system. That allows an intruder to make new users.  And that allows hackers to expand that operation. 

We can say that all criminals are marginal people. But what makes them marginal people? When some ex-neonazi or MC-gang member wants to get back into society, those people carry the criminal stamp. The rest of their lives. Some people ask, can ex-Nazis or other ex-criminals really regret their actions? If we think like that. Criminals are individuals. That means some of them regret, and some of them don’t. 

We will put those people. Into a marginal position in society.  The rest of their lives. And that raises the risk that those people will commit other crimes. If a person is surrounded by other criminals, they cannot re-integrate into normal life. 

Only jobs. What the ex-inmates can get is some kind of cleaning work. They carry a criminal stamp. The rest of their lives. 

So, are hackers criminals that society created? We can say that some of them have criminal behavior. Because of other people. didn’t accept them for who they are. The media introduces computer hobbyists as some stereotype who is not social. Their place in a mental hospital is the message. Those people face demeaning treatment; they have no girlfriends, because some elder guy wants to show that they are alpha members of some school party. What would you feel if somebody yelled at you, “Get out”? Would that be non-respectful behavior?

What if your workplace treats you as necessary furniture, whose mission is to do jobs? But whose mission is to be otherwise invisible. There are people who just wait to fire those ICT support persons. They show their authority to those people all the time. So, what if your workmates treat you without respect? What if you are always an outsider? Would you want to take revenge? Those kinds of outsiders are excellent targets for a criminal gang recruiter. The hyride threat is that those criminals can cooperate with foreign intelligence services. And they can give a tip for those hostile agents. Maybe they get guns or drugs as payment for cooperation. 

And then we must ask why hackers are what they are. In this case, we must ask why computer hobbyists are what they are. Those people are boring nerds who are not in any way interesting.  Do you know those people? Some of them are people who don’t find any social hobbies. They are people who are lonely because nobody wants to play with them. And the computer is their only friend. Then some criminals come and offer money or women to those people. Some hackers are young, and they don’t understand why some criminals want policemen's home addresses. But then. We must realize. People grow into criminal behavior. 

Maybe the first case that. Those people did it for revenge. It’s easy to steal somebody's passwords. To some system, and then send a message to customs or airport security. When we think of things like professional hackers. Those people work for some criminal organizations or governments. 

Some hackers are made by governments. They can be forced to make those things for the military intelligence. Or some criminal organizations can blackmail them. The fact is, this hacker must not be a qualified programmer. That person must not be an extreme computer genius. If the person gets access to the system is enough. One of the oldest tricks is to play some cleaner and then step into the office. And search for those passwords in the places. Like under keyboards or from computer briefcases. 

The question is always who made the initiative.  Who gave the idea for the hacking operation? Or was it the hacker self, or somebody else? That means some sensitive information can be used as a booster in political games. Psychiatric papers are tools that can offer a possibility to clear the competitor out of the way. That means some people can steal those papers. And some other people are willing to pay for that kind of information. 

AI-controlled drone swarms are entering battlefields.

 AI-controlled drone swarms are entering battlefields. 

The next step in drone technology is the development of AI-controlled drone swarms that utilize a LEGO-based system architecture. That cloud-based modular technology offers them flexibility and a multi-mission ability. Those drones can search enemy targets, support fire control, and make kamikaze attacks.  They can carry various sensors. Like Geiger meters, gas detectors, microphones, and other systems. 

That means when those systems require more calculating capacity, they unite their processors' capacity to work as a cloud-based morphing neural network. When the solution is made. Those drones, or their computers, can be separated, and then those systems, or each drone, can operate independently or as part of the entirety. 

Researchers took this idea. From a hypothetical alien model, where aliens can be like insects. When those insect-aliens require intelligence. Those things turn together. And then they share missions with each other. 

That idea is transformed into the drone swarms. Those drone swarms can call other swarms to solve complex problems, and then they share their missions or roles with the drones that participate in that swarm. Those drones can operate as one entity. Some drones can attack air defense. In that case, even small drones can be a more dangerous tool than anyone expected. They can hunt enemy commanders from the streets. The drone can slip into buildings through windows or ventilation. And even through sewer systems. If they are able to operate underwater. 

A large drone swarm can create a layer over the battlefield. Those drones can interconnect their sensors, which can transmit enemy moves to the commanders. Drones can also attack targets. That they recognize. The system uses images stored in the drone’s memory. 

One drone can drill a hole into the wall using explosives, and other drones can drive themselves into that hole. The drone can wait until its AI recognizes the target, and then attack it. The drone swarm can land on the roofs of trains. And then make their attacks. Large-sized cruise missiles or unmanned boats can carry drone swarms to target areas. Those drones can perform those missions without communicating with the command center. That makes them immune to normal jammers. 

The EMP system uses  high enough power EM impulses that it can destroy physical electronics. It can also destroy AI-controlled drones. The drone swarm can be released to the operational area just before manned aircraft comes. Drones can search for anti-aircraft artillery,  missiles, radar systems, and radio transmitters. They can attack ammunition storage. 

They can also make a radar and IR shield between aircrafts and ground-based systems. In those cases, small drones can search ground-based systems. And attack them. They can also disturb defense. Using jammer systems, aluminium bags, or IR lights that cover stealth planes behind them. Drone swarms can also close airfields, and they can fly into the aircraft’s jet engines. If drone swarms hover above runways, they can deny aircraft takeoff and landing. The small damage to the aircraft’s window or structure destroys the stealth-fighter’s stealth capacity. The drone swarm can communicate with aircraft. And stratospheric and orbital  satellites using laser systems. And those systems can also deliver those drones against the targets. 

https://www.msn.com/en-us/lifestyle/shopping/ai-powered-drone-swarms-have-now-entered-the-battlefield/ar-AA1LHwJg

The new computers are morphing neural network systems that mimic quantum computers.

 The new computers are morphing neural network systems that mimic quantum computers. 

"By linking smaller superconducting modules like building blocks, researchers at the University of Illinois Urbana-Champaign achieved near-perfect qubit performance. Their modular approach could open the door to scalable, flexible quantum computers of the future. Credit: Shutterstock" (ScitechDaily, Scientists Build Quantum Computer That Snaps Together Like LEGOs)

The fact is this. The regular binary computers can also operate like LEGOs. When a problem becomes too complicated for one computer. That computer can call more calculation units or computers. To operate on the problem. The system can call for assistance over the internet. That means when the computer doesn’t get an acceptable answer, it calls more computers to work with that thing. 

The new innovations in quantum computing represent a significant step toward a more efficient and effective way to calculate things. The reason why quantum computers cannot be stuck is this. They are like a tower of binary computers. Every layer or state in a qubit operates as an individual quantum computer, and if one of those states is stuck. 

Another state or layer comes and releases that state. When we think about the power of quantum computers.  We must remember that they can drive multiple programs. At the same time. Or they can cut and share complicated problems over those layers, and the AI-controlled quantum computer operational systems can act like LEGOs. 

Those systems can operate and run multiple different programs at the same time, but if that system sees something very complicated. That system will collect more and more quantum states and quantum units together to solve those problems. If the quantum system does not find an acceptable answer. That system connects more and more quantum units and quantum states to operate with complicated questions. 

So, in the case when the system doesn’t need very much power. That can allow all its units to work separately. With different problems. But when the system requires more power. The central system orders those systems to save their duties. And then start to work as a whole on that complicated problem. Things like drone swarms can use similar technology. That system can call all units to work on things. Like routes that those drones can choose. And then the system breaks entirely and shares those solutions to individual drones. 

The second big advance will be a room-temperature quantum computer. 

"Figure: (upper panels) Scanning-electron-microscope image showing a charge-density-wave device channel in the coupled oscillator circuit. Pseudo-coloring is used for clarity. Circuit schematic of the coupled oscillator circuit. (lower panels) Illustration of solving the max-cut optimization problem, showing the 6 × 6 connected graph, circuit representation of the six coupled oscillators using the weights described in the connectivity matrix, and values of the phase-sensitivity function. Credit: Alexander Balandin" (ScitechDaily, UCLA Engineers Build Room-Temperature Quantum-Inspired Computer)

The UCLA engineers built a quantum-inspired computer. The system will use a morphing neural network technology that mimics the quantum computer. That can change the world. The room-temperature quantum computers are tools that will revolutionize computing. When we think about things like quantum dots in virtual quantum systems, those quantum dots are the binary computers that operate like states operate in quantum computers. That makes those computers very powerful tools. Because those systems are immune to errors and stucks. 

"Scientists have built a physics-inspired computing system that uses oscillators, rather than digital processing, to solve complex optimization problems. Their prototype runs at room temperature and promises faster, low-power performance. Credit: Shutterstock" (ScitechDaily, UCLA Engineers Build Room-Temperature Quantum-Inspired Computer)

If some of those computers are stuck, some other computer releases that system. Because that system is morphing. That means all its participants can operate independently with different problems. But when a problem reaches a certain state of complexity. The system sends a message that all computers must unite their force to work on that problem.  

If a researcher makes a quantum computer that operates at room temperature, that system can be superior to the regular binary systems. There are so-called virtual quantum computers that operate in data centers. In those special neural computing systems. Each physical binary computer works as an individual quantum state in a quantum computer. The system operates entirely. It tries to mimic a real quantum computer. 

The system can operate like a quantum computer, but the qubit states are replaced. By using a physical binary computer. Those systems act like a quantum computer. That system’s Achilles heel is that it needs. A lot of power. If we want to make a virtual quantum computer. That qubit has 129 states, which requires a system with 129 binary computers. And that causes very big electric bills. Those systems release heat. This means those systems require powerful coolers and other things that protect those machines. 

https://scitechdaily.com/scientists-build-quantum-computer-that-snaps-together-like-legos/

https://scitechdaily.com/ucla-engineers-build-room-temperature-quantum-inspired-computer/

A company is always as good as its workers.

 A company is always as good as its workers. 

We can react to change only if we recognize what changes. We don’t have to make a comprehensive response. That goes through the entire company. in every case. We must find the way. How to respond to that new situation effectively and economically. In the changes of data directives, the change will touch information management. That means people who work on assembly lines don’t have to react to those kinds of things. If the reaction is wrong, the damage can be huge. 

The reaction to change must be. 

1) Effective

2) Economical

3) Sustainability. 

4) Legal. 

5) Respect nature. 

6) Respect values. 

7) Follow the environmental needs. 

The company cannot make better products than its employees can. 

Workers are the company. Their skills make the company’s products. Without products. The company faces bankruptcy. The worker must develop their skills so that they and the company can respond to challenges that a changing environment and business ecosystem form. The business ecosystem can face changes. That form when things like building materials change. When bricks turn into concrete elements. That means the brick factory must change its products. It must start to create other ceramic products. 

Another way is to search for and expand a new marketing environment. The third way is to close the factory or reduce production and kick out workers. Or, the company faces bankruptcy. The problem is that products are as good as the worker’s skills. If the company leaders kick workers out. The factory’s ability to respond to new orders decreases. The answer is that robotics is a thing that can give answers. The company must find out. Does it have the skills to make these types of projects? 

The company can get those skills in three ways. 

1) The company can hire people who have those skills. 

2) The company can order a course to get those skills. 

3) The company can give orders that every worker must go to the library, and then find the information about the new thing. 

There is a famous so-called 10-20-70 model of company learning method. 

10% is official courses

20% is learning in teams

70% is self-directed learning. 

In all those cases, some kind of test can be a useful tool to make sure. That people really have the skills. That they need, or they claim. That they have. 

There are some problems with the last two cases. The problem is how to make sure. People who use self-directed learning really know those things. That they should know. Another problem is. How to make people share their knowledge in the team. People think that their skills are capital, which guarantees their workplace. That means people can hide their knowledge. They might think. If they hide something. That is important. That raises their value. This is one of the reasons why things like AI projects can fail. 

The failure can be caused. Because people don’t share their information. They don’t want to help their competitors. And that is one of the biggest problems with the working environment. Workers must have certain skills to make products that the company sells. Without those skills, the work is undone. 

When we face the need for change, we face the effect. That comes from the outside environment. Those changes can be legislative. Or they can be technical, or some other things. Like war causes situations. That companies must change. So that they can adapt to the changing environment and its challenges. The change can reshape a customer’s relationship. Or it can reshape the manufacturing lines. Or it can be reshaped into information management. The control team must find a way. To solve or respond to the problem. The fact is that outsourcing some solutions is a good choice. The company must not keep or recruit all the needed personnel itself. But outsourcing requires money. And it can cause a situation where all people who worked with that thing go to other companies. 

When a company makes a list of needed changes. The list must not be too long. That the people who work with those things have time for deep analysis. Of things. That requires changes. If the list is too long, that means the analysis turns too superficial. The central business is the focus of that operation. But then. We must understand that if we outsource something. We must have money. For that thing. Outsourcing the need doesn’t mean that the need is gone. 

Why does AI fall into the infinitely continuing loop?

 Why does AI fall into the infinitely continuing loop? 

Infinite loops, or infinitely continuing loops, mean that the system is stuck operating with the same problem without a reasonable solution. 

All our neurons operate as pairs. When the first neuron sends a message to the receiver. The receiver acknowledges the message. Those receiver neurons send the message. That the message is received. Sometimes something causes a situation. The transmitting neuron sends an acknowledgment back to the receiver. And then. Those neurons start to play a ping-pong, using those neurotransmitters. That means those neurons can fall into a situation where they just surround the same dataset in the form. Called infinity loop. 

But no problem, the outside neurons come and remove the loop. That releases those neurons to operate on a new problem. The outside system must only recognize the infinite loop, and that is quite an easy thing to do. The control system, “judge,” must just see. The system  under the “judge’s” supervision gives the same answer repeatedly. If the answer is the same multiple times, the supervisor sees that those data processor units, like neurons, can be released to operate on another problem. 

The reason why our brains would not fall into a thinking loop is this. We have so many neurons. Our neurons watch each other. And if there is a situation in which some neuron group starts to operate on the same problem repeatedly, and data starts to surround that neuron group, the outside neuron comes and releases those neurons. That means. Outside neuron destroys neurotransmitters that carry the surrounding information. And releases those neurons. 

The upper image introduces the algorithm. As you see, data travels in a circle. But sometimes the algorithm makes mistakes. The mistake can happen when the algorithm uses the wrong dataset. Or sometimes the algorithm simply returns the last mission solution to its beginning point. The system should only send a mark that it's not busy. But sometimes the router will send something else to the return point of the algorithm. When data travels in a computer. 

One wrong value causes a scandal. And in binary computers. It is not accepted. If the value is more than 1. Binary processors can operate only in states one and zero.  The stuck gate causes value 2. The system is stuck. The problem is that the system cannot null itself. And in infinite loops form when data surrounds the system. And it cannot null itself. Without stopping, those algorithms cannot take on the new mission. 

Have you ever tried to make an infinite loop in your mind? The infinite loop, or infinitely continuing loop, is the case where thoughts surround in a circle. The infinite continuum is the case where we think, “I had a dream, that I had a dream...”. This means the list of those internal spaces can continue forever. But the fact is this. Our brains cannot make an infinite loop. Or an infinite circle. Things like pi (3,14...the ratio of a circle's circumference to its diameter) are not infinite loops. They are infinite continuums. 

Outside systems can deny the infinite loops. When the system operates to solve a problem. The outsider judge system. Checks the answers. If the main system always gives the same answers, the system has fallen into an infinite loop. And the outside system orders stuck systems to dismantle the loop. And reboot the system for the next mission.

Brains can create situations that we might think of as a “virtual infinite circle”, but we are never stuck in that thing. And the reason why the AI can be stuck in those processes is this. The algorithms are like circles. But the second thing is that. The AI operates over the binary computer platforms. The AI is an algorithm group that requires the giant computer centers. There are billions of microchips in that system. But there is one weakness. When the AI or large language model, LLM, starts to solve the problem, it has a certain data handling capacity in use. 

Or, the system reserved a certain number of microprocessors for use in that problem. But if the system cannot solve the problem, the AI calls more data handling units to operate on the process. If there are no limits for that process, the system can use its entire capacity. For one problem. That is the thing. That causes the infinite loop. The computer makes its calculations. And then. It makes an error detection. Calculating the same calculations backwards. Another way is to make the error detection. Using two different lines or computers. 

If both computers have the same solutions, that means (probably) there are no errors. There is a possibility. There is a common error that causes a false answer in both computers. But the last one is faster. Than the case. Where the system detects errors. By calculating all calculations backward.  After that, the system can introduce a solution. But sometimes, Something causes situations that the system cannot detect the errors as it should. 

The infinite loop forms in the case that there is no outside actor. Or the system uses its entire processor capacity to solve some problem. In that case, the system has no resources to end the task if the processors are starting to play pin-pong with the solution. That keeps those processors busy, and they have no time to null that process.  

There is a need for an outside microprocessor. That gives an order to stop the action. If the entire system is not reserved. There is a system. That denies the main system from falling into infinite loops. 

The problem with AI is this: It’s not intelligent.

 The problem with AI is this: It’s not intelligent. 

"Opaque AI systems risk undermining human rights and dignity. Global cooperation is needed to ensure protection." (ScitechDaily, “AI Is Not Intelligent at All” – Expert Warns of Worldwide Threat to Human Dignity)

The AI is not as intelligent as we know intelligence. The AI utilizes specific parameters to gather information. If AI collects information about a person, it might use things like photographs. And it recognizes that object. Then it searches texts that are written or films that are connected to that image. Then it creates a data matrix about that person. The problem with that is this. The AI doesn’t actually know. Do those texts and other data have any connections with a real person? 

The AI is a tool that can connect data from multiple sources. And it can make many impressive things. But AI doesn’t know. Does the person really have a connection with the data that AI uses? This is the problem with the AI. The AI connects data and makes medians, and then it creates a summary about that text. An interesting thing about AI is that. Every single data unit can be introduced as a numeric value. We can give as an example a ca value of 6. Or something like that. 

This makes the system easier for programmers because numeric data is easier to handle. But the problem is that. AI doesn't have a natural ability to be suspicious of data. That it uses. This means the AI is easy to cheat. The AI can have prohibitions that prevent users from using the AI for certain types of purposes. But the problem is that the AI programmers and engineers are not always experts in law. Another problem is this: what if  the AI software order comes outside the EU region? 

The programmer can operate using remote connections. That means the person who orders software might be different from the person whose name is in the paper. This means the real customers can sit far away from the person who is marked as a customer. The problem with algorithms is this. Things like malware are easy to make using the AI. And there are lots of actors like China and North Korea who want to create AI to control their society. 

Those actors have no limits for recruiting programmers to create AI that can generate spy programs. People forget this aspect too often. They think that the entire world is like the EU, where people follow the same rules. We forget that the Internet allows spies to operate from thousands of kilometers away from their target. The spy who operates for Chinese intelligence can sit in an office and use the internet and virtual spying tools to steal secrets. 

https://scitechdaily.com/ai-is-not-intelligent-at-all-expert-warns-of-worldwide-threat-to-human-dignity/

Ukrainian new Flamingo missile can change, something.

 Ukrainian new Flamingo missile can change, something. 

Ukrainian new FP-5 Flamingo missile has a range of approximately 3000 kilometers. That means it's capable of long-range strikes against Russian targets. The Flamingo missile made its tribute and destroyed the FSB station in the Crimean area. The missile itself uses a GPS/GNSS navigation. With inertial, INS backup. That means the system is immune to the jammers. The ability to make long-range strikes means that Ukraine can cause damage and pose a threat to large areas in Russia. And that means the Flamingo is the thing that can cause very bad damage to the Russian military industry. 

The missile range is long enough to reach Moscow and many other important targets. The thing that makes Flamingo important is that the system decreases Ukraine's addiction to Western weapons. This missile can fly without the GPS if the system knows the position. Where the missile is launched. The operation can be made using the missile’s INS navigation. The system can also use AI-based target recognition. And that means the system is highly independent. The fact is that the large-sized target drones are easy to transform. Into missiles. 

Geran 3 drone. 

"The center of the circle is not on the frontline and its not either very far west in Ukraine either. Even some larger cities and or factories east of the Urals Mountains are in range." (Reddit)

The new tools, AI-controlled, like visual image or Lidar-scanner-based terrain contour matching TERCOM systems, connected to inertia, make drones independent of GPS. Those systems can also make it possible. To create new types of precisely attacking drones. That can even ambush jet fighters and helicopters from the air.  When a jet fighter turns against a drone swarm, some of those drones turn to attack that fighter. 

Russian jet-engined Geran 3 Kamikaze drones are causing trouble for Ukrainian air defense. Those drones are too fast for helicopters but “too slow” to manned jet fighters. The main problem with drone defense is that. Those drones can fly in large swarms. That means those jet fighters might face a situation where they have enough ammunition to destroy all those drones. 

Another problem is that those drones could change their targets. The advanced AI makes those drones more lethal, and the next-generation drones can have an AI-based imaging infrared systems that allow them to attack jet fighters and helicopters. Drone swarms can attack as one entity. The problem is that AI-controlled drones can already be a reality. The AI-controlled drones can make ambushes against defending fighters and helicopters. The AI itself is cheap when the algorithm is ready. 

https://www.aerotime.aero/articles/flamingo-missiles-strike-fsb-base-crimea

https://www.defensemirror.com/news/39493/Russia_s_Geran_3_Jet_Powered_Kamikaze_Drone_Ready_for_Operations

https://www.ir-ia.com/Ukraine-Flamingo-FP5-Cruise-Missile.html

https://sfg.media/en/a/ukraine-flamingo-missile-claims-doubts/

https://en.wikipedia.org/wiki/Flamingo_(missile)

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

https://en.wikipedia.org/wiki/HESA_Shahed_136

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

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

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