The world's first superconducting quantum heat engine is real.

“Artistic impression of a superconducting quantum heat engine. Credit: Heikka Valja / Aalto University”  (ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

Finnish researchers have created the first quantum heat engine. “Researchers at Aalto University have built the first cyclic quantum heat engine inside a superconducting circuit. The device uses a qubit, the basic unit of quantum information, as its working substance and repeatedly drives it through heating, cooling, and energy conversion.” (ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

“Quantum heat engines have previously been demonstrated with systems including trapped ions, atomic gases, nuclear spins, and defects in diamonds. Superconducting circuits are especially important because they are already among the leading platforms for quantum computing, communication, and sensing. Until now, however, no experiment had completed a cyclic quantum heat engine using this technology.” (ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

“The immediate significance is not the amount of work generated, which is extraordinarily small. Instead, the experiment shows that heat can be deliberately controlled and converted inside the same type of circuitry used to build quantum processors.”(ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

Quantum engines are the miniaturized versions of nanotechnology. If those systems. They can put particle spin very fast. When particles spin in the cage. It pulls energy through that structure. That causes a quantum glow in that cage. Basically, a quantum engine; it’s similar to other engines. e It can use the magnetic field and IR radiation combination. To make transform radiation into motion. Those systems. They just transform wave movement. Or electromagnetism. Into kinetic energy. So, when the core in a quantum engine spins. That core binds energy into it. When its speed accelerates. When it slows. It delivers energy. 

“That capability may become valuable as quantum computers grow. Today’s superconducting machines depend on large numbers of microwave cables running between room-temperature electronics and processors kept at temperatures only a fraction of a degree above absolute zero. Each cable adds cost, occupies space, and can carry unwanted heat or noise into the system.” (ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

“The researchers are now working toward a fully autonomous version of the engine. One possible application would be reading the state of a qubit without sending a microwave signal from the cold processor to room temperature. Placing more control functions directly inside the cryogenic circuit could reduce the amount of external wiring required.” (ScitechDaily, World’s First Superconducting Quantum Heat Engine Could Transform Quantum Computing) 

The quantum engine that transforms infrared radiation into motion is a fascinating tool. 

This. Kind of system. It can transform all radiation types. Into another by using motion. The radiation. Like radio waves. Hits the quantum engine. It starts to move. And then. It transforms that movement into electricity. Then that electricity. It can be used. As an example, an X-ray system.

Quantum system. That transforms kinetic energy into motion. That thing can be the new tool for micrometeor and armour technology. If the system can transfer impact energy into rotating movement. That can turn a surface extremely hard. In stealth technology. That ability to transfer electromagnetic radiation into movement. Makes it possible to pull standing waves out from space between atoms. Those systems. 

This kind of system. They can feed energy to quantum computers. The system. That can transform radiation into motion. This can bring interesting ideas for energy sources. To the journeys to the edge of the solar system. The quantum engine that can turn minimal energy into motion is the thing. That could replace at least some of the RTG (Radio Thermal Generators). Used in long-distance space journeys. Or those systems. They can at least make the RTG power sources more effective. By benefiting from the temperature that those isotope generators deliver. 

Nano- and quantum technology that transforms heat into motion. That is the system. That can help to create more sustainable materials. That stand the heat. The idea is that those quantum systems. They can transfer heat energy from the shell of the spacecraft or airplane into a moving part. This turns infrared radiation into movement. And then that nano-. Or quantum generator. It can transform the heat into UV light. 

This kind of transformation is quite easy to make. The nanotechnical generator. It simply transforms heat energy into electricity. Then that electricity. It can be transferred to UV light. This kind of system. It can transform almost any wavelength into another. When things like radio waves hit this kind of system. That system can transform radio waves into X-rays through motion. This kind of system. They can be the next-generation tools. For new stealth  technology. 

https://scitechdaily.com/worlds-first-superconducting-quantum-heat-engine-could-transform-quantum-computing/

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

AI might think differently than humans.

“York University researchers have uncovered a surprising mismatch between how artificial neural networks and primate brains process visual information. Credit: Shutterstock.” (ScitechDaily, Scientists Discover AI Models May Not Think Like the Brain After All)

AI might not think like a human at all. When researchers try to make computers think like brains. Those people sometimes forget why human brains are so different. Thinking in human brains is more closely connected to physical structures such as neurons and neurotransmitters. Than we even think about. 

This is the big difference between computers and human brains. The structure of the human brain plays a bigger role in the thinking process. Than we thought. The computer that runs billions of databases. It can have a very impressive capacity to connect information. But the problem is that. One binary processor. It can run one operation at a time. The system requires new processors. 

That processor. It can run. Multiple tasks at the same time. This is not possible for the regular processor. But the processor. That mimics the brain. It can use all its layers as independent processors. 

 The brain has four main areas. 

1) Cerebral cortex 

2) Cerebellum

3) Brainstem 

4 Cerebral hemispheres. The last one has two parts. 

The fact is that if we create a microprocessor that mimics the human brain. We need a five-layer microprocessor. Each of those layers can use a different programming language. That denies the data mix in the system. If every layer of the processor uses different languages, that makes data meant for other layers seem white noise.

Each layer mimics each part of the brain. And those layers. They can have different programming languages. Or different frequencies. That helps them to separate and sort information. The four-layer microchip. It can have one divided layer. That mimics the cerebral hemispheres. 

From different sources. The database connections. They can mimic neural networks. That transfer information in human brains. The difference between database structures and human brains is this. Databases run on the same monolithic computer. In human brains. Every single neuron is like an independent computer. This means that if we want to make a computer. 

Or. We can rather say: an AI solution. We must create a system. That involves 86 billon computers. The system. It can use morphing neural networks to make its operations more effective. 

“Schematic of a simple feedforward artificial neural network.” (Wikipedia, Neural network)

The thing that can make the process quite easy is that. Every neuron has. The ability to change its connections and their relations. This means we cannot measure the neuron’s ability to process information in the same way. As we measure a computer’s ability to process information. Human brains store information in the form. 

That is similar to a mosaic. The information. It is stored. In a form that is like pixels. Brains can connect and reshape those pixels freely. And that ultimate flexibility makes human brains so different from machines. In brains, every neuron has a pair. A mirror neuron. The neuron and its mirror. They act like loops or algorithms. Another purpose for mirror neurons. That is. They tell the primary neuron that the information traveled through. 

In human brains.  Multiple points of start. Data processing. At the same time. Brains can spread the operation. They could reserve more neurons for that action. This means that brains concentrate. In another way. Than computers. In brains, in brains. Every neuron acts as an independent computer. And the large number of neurons gives fine-tuning for processes in the brain. 

Computers can also connect data. But that system is far different from humans. In computers. The binary system. It can handle only one task per operation. The AI. That mimics human brains. Must have 86 million physical processors to mimic human processes. The ability to search data and then combine that data with memory. Is the thing that we call thinking. 

We could make a machine. That mimics human reactions. That machine requires a physical platform. That involves the same structure. As human brains. The fact is that. If we want to make a machine. That thinks like humans. We must remember that the system. It is a combination of hardware and software. 

https://scitechdaily.com/scientists-discover-ai-models-may-not-think-like-the-brain-after-all/

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

What do a locomotive and a data center have in common? They both face resistance.

Political resistance against data centers. Forces them to find new locations for those systems. 

Data centers face resistance. That is one of the things. That we can see. The main problem with data centers is this. Those systems don’t require permissions. Except for the use of land area. The data company. It can buy a large group of houses. And then turn the database into cloud-based systems. The cloud-based architecture means this. There can be extremely large data centers in the neighborhood, and nobody even knows that they are there. 

When we resist data centers. And the use of AI. We can see similar cases in history. In history, people resisted things like cars. The origin of the car is in the train. The steam engine made it possible to make trains. 

The speed of the first train. It was 21 km/h. The crew of the train was two. Two men could handle very much cargo. The first trains were used in mining areas. They could maintain their speed. All the time. And that removed the crew from logistics. And then people started to think about the possibility. To create the train on wheels. The combustion engine made the car real. And that caused problems with workers. Unlike horses. Cars and trains required mechanics. Those people who worked with those mechanical systems required training. Unlike people who feed horses. 

They said cars would cause unemployment. Cars caused pollution. But the first arguments against cars were that cars take work from cattle workers. The problem with that criticism was simple. It was that the critics were cattle owners. Horses were the most important working “tools” before the car. The big problem with cars was that. They took the place that belonged to horses. first car was slower than a horse. The maximum speed of the car. It was about 15-30km/h. But the car was a machine. It could maintain that speed. All the time. So, the car was more effective. The car didn’t need water or food. And that made tractors and cars suitable. To operate in places. Like Antarctica. If people operated there with horses. That required a lot of food. 

But as we know, people resist data centers for many reasons. The big problem is that. The only thing that measures effectiveness. It is the income money. If people have free time. In their workplace. That is ineffective time. That causes a need to decrease the number of workers in the workplace. That causes unemployment. 

Another thing is that. People resist everything that is new. The ICT area is been like in the position of the stepson in the media. When we think about traditional business. That thing required a lot of workforce. A steel factory sends pollution. So that requires lots of permissions. Of course. Data centers require permission to use land area. The data company can just buy a lot of houses. And then make data centers in them. This kind of solution doesn’t need new buildings. This means that. The data centers don’t need as much political support as traditional factories. 

And the second thing is this. Data centers are primary targets for the enemy in the case of war. This means that things like underground facilities can help data center survivability. 

But the answer. It could be an underground data center. The tunnels are full of supercomputers and are not visible from the ground. The technology. That those tunnels require. They can be the same. That is used for making subway trains. 

The ICT company doesn’t require a workforce in the traditional way. They don’t need raw materials. They need people who make code. There are no psychological or health limits in this work. The ICT company just needs working spaces. And remote work makes it possible to operate data centers from another side of the world. The head coder can do the job. That person can operate and train AI agents to make code. The underground facilities are the answer to the natural problems. Data centers that are deep underground. They can use geothermal heat or miniature nuclear reactors to provide electricity. 

The deep caves. Like exhausted gold mines. They can provide stable and radiation-protected locations. Some of those points are used for neutrino telescopes. But those locations can be suitable places for quantum computers. The quantum computer. It can be in a thermos box.  The isolation layer: A faraday cage and radiation protection. They are between the walls. Of the box. The purpose of those layers is to isolate the qubits. From the outside environment. 

The other place where those data centers. They can be made. Is the ocean floor. Large and complex structures. They can be modules. Dropped to the deep sea. Deep-sea data centers can be operated using robots. Underground and deep-sea positions. They can protect data centers against terror and bomb strikes. 

Rising resistance against data centers. Forces data companies to find new positions for data centers. The deep sea and underground positions. They are effective. But things like orbital data satellites are new tools. They can operate using cloud-based architecture. Data satellite. It’s a similar server. To other servers. The orbital server’s program maintenance. It is similar to other servers. So, the person who does the maintenance work. That person doesn’t need to know. The position of the server. The orbital data center. It can be the belt or chain of data satellites. If one of those satellites is visible from a ground station all the time. That means the maintenance will not see any difference between ground-based data centers. And data satellites.  

The satellite. It can have a heat shield. And the ability to land safely. This means that those satellite swarms can recover their critical components. And that helps to find. If somebody tries to “steal” them. The orbital data center. It is a group of satellites. Those satellites can communicate with each other using lasers and radio communication. The system is similar to Starlink. The backups. And other things can be made into other satellites.

Or ground-based hard disks. When one satellite is jammed. That satellite will be replaced with another satellite. The operations with orbital computer platforms are the same as they are on ground-based systems. The people who operate the computers. They drive system updates into the orbital data servers. As they do for the normal ground-based data centers. The people who update and maintain computers. They must not have access to satellite trajectory controls. 

People who adjust satellite trajectories must not sit in the same room. There the compute operators sit. The same way as in every other data center. The maintenance crew can operate those systems remotely. Just like in every case on Earth. The remote operators don’t need to know where their server is located. They need to know how to make those updates. 

Solar sails and their technical problems.

In some ideas: solar sails. They can travel inside the solar system. The idea is that those sails can be very large radio telescopes. Or they could carry large interferometer antennas out from the asteroid belt. 

There are visions of solar sails using laser acceleration. It can travel to other solar systems. When a solar sail travels very fast. Photons that impact the solar sail start to transfer less energy into it. When the sail reaches a speed. About 75% of the speed of light. The laser beam that accelerates it starts to lose its energy. 

The Doppler effect changes the wavelength of the impacting laser beams. The effect is similar. As we were throwing balls to an escaping car. When an object escapes, the particle pushes energy to that object more slowly. And that decreases acceleration. Photons act like all other particles, like balls. When the solar sail moves faster. The laser beam that hits it starts to lose its power. 

The calculations show that low-energy photons can slow the solar sail. This means that when solar sails travel outside the solar system. The same light that accelerated it turns to slow the solar sail. So does light accelerate or slow it down? That depends on the energy level of the photons. 

If the photon's energy level behind the solar sail is higher than its front side. The photon accelerates the solar sail. If that energy level behind the solar sail is lower. Those photons transfer energy into themselves. And that slows the solar sail. But another thing that can slow the solar sail is the gravitation of the entire solar system. 

When the solar sail starts its journey, there is less mass behind it. Than when the solar sail travels out from the solar system, the entire mass of that system turns behind it. This means that the mass of the Kuiper Belt. Oort clouds. And planets, the Sun, and all asteroids start to pull the solar sail behind it. Another thing that can slow the solar sail is the starwind. The starwind is the particle flow from other stars. 

That particle flow impacts. The heliopause from outside it. That can also push the solar sail back. So if that particle flow is stronger than the particle flow from the solar system. That thing pushes the solar sail back. This means that solar sails may need something. That pushes them forward. Those things can be hydrogen bombs that are left in the solar sail’s trajectory. But the problem is always the same. The acceleration means that those systems can push less energy to the solar sail. For the same reason as why the laser beam cannot transfer energy into it. 

When we think about the systems that carry laser systems. The only problem is that. Those systems would form a closed system. The laser system. That shoots a laser beam into the mirror at the front of the craft. It must be released when it is shot. When that laser is released. That system is not closed anymore. And those single-use lasers. They can push the craft forward. The idea is that. The laser is in the frame of the solar sail. Then that system. It will be separated. When the system. It needs the power. 

Those single-use lasers. They can be like in a magazine in the solar sail. Then those systems. They can be released. The laser. It can get its energy from a rocket engine. That pumps energy into it. When the laser is separated, the rocket starts. And it also gives energy to the laser. The rocket pushes that laser system backward. 

The fact is that. Solar sails can be interesting tools. To travel inside the solar system. But stars are always a little bit too far. Inside the solar system. Those solar sails can use solar energy and particle flows. This means that interstellar flight will not be possible until the entire solar system is explored. 

https://scitechdaily.com/the-strange-force-that-could-slow-interstellar-solar-sails/

Short-term thinking is a problem worldwide.

Short-term thinking is a problem worldwide. Not just in the USA.  Short periods in parliaments encourage members of parliament. MPs. To make. Short-period decisions. Parliamentary. And presidential sessions are short. Because if decisions are wrong. That allows electors to change MPs. And then the main problem is this: who tells the elector? The right decision? Electors see their wallets. They see their financial income. And that is the thing. That makes it hard to make long-term decisions. Social media causes pressure to please people. People want jobs. They want cheap merchandise. And that is the problem. Climate change causes worries. But the bigger worry is. How can we get work? 

By promising money and a circus. Politicians can get votes. They don’t want to promise things like sacrifices. They promise work. If work is done in Africa. That is not mentioned. Those workplaces are for African people. So if the African worker makes sneakers in Africa or in China. That doesn’t bring workplaces either to the USA or to Europe. Those taxes are also paid to those countries. 

We see things that happen right now. We see our income. And nobody wants to pay taxes. People know what they see in their windows. 

They know what they want to buy. The fact is that. What people in the future think. That is their problem. Nobody who is not born yet. Tell their opinions. In the same way in business life. If the leader sits for 3 years in office. This gives the possibility. To push investments into the future. The investment decreases income. And this is the reason why the leader makes short-term decisions. In politics, people are not interested in the journey to Alpha Centauri. They are interesting. 

About their jobs. The benefit of the head of state. It could be different than the other nation. And this is the big problem. The head of the state must advance the state’s interest. But that interests me. It’s not clearly determined. So, we must ask one question. Whose benefit is the benefit of the state? Short-term benefits can cause long-term trouble. When U.S. people think of their history. In the Cold War period. They remember how much the Cold War cost. They think that things like the Apollo program were only a waste of money. They don’t remember the technical advances and customers that this program brought. And that is the problem with those things. 

Politicians can say how much that program costs. They can bring numbers. The companies can bring things. Like Velcro tapes. Computers and heavy launch vehicles. The problem is that. Those things are not very nice-looking. If we look. At the price of the program. So, if we want to be negative. We stare at just the costs. We don’t care how much those products bring to companies. We see only investments that can be made somewhere else. The international relationships are another thing. That causes grey hair. Those relationships. They are seen only as a waste of money. Investments in international cooperation.  

Like. Membership in the EU costs money. Negative thinking means that we don’t even want to calculate income. We see only the money that we pay. And that is the big problem. If we want to decrease pollution and stop climate change. We must promote international cooperation. If we just transport polluting factories. Into somewhere there we cannot see it. That is not the answer to the problem itself. This is the same. As we would clean our wastewater. By conducting it. Though the neighbour’s plot. This doesn’t make that water cleaner. That it travels through another plot. This is the thing. That we should realize. The same things that bother the USA. They are global problems. The USA is the most visible actor in the global theater. And that pulls other smaller actors behind it. 

If we think only.  A short-term income. We are in a big problem. Things like AI are good targets for critical thinking. They cause pollution. They need electricity. And they need this and that. They destroy our ability to think. But then we can see another question. How much does traffic pollute? How much electricity do electric cars use? Those things are always similar problems.  As data centers. If heads of state sit,. For a long period. And they make mistakes. That is also a problem. Every leader in the world has an ideology. They have thoughts. How things should be done. 

Strong leadership. It is a good thing. But only if the leadership is in good hands. If the leadership is in the wrong hands. That can turn it against society. And. The center of that problem is: how to determine ? The benefit of the state? The state needs leadership. But what if that leader destroys the state? The big problem is always. What if we just cover problems? It’s easy to cover garbage. And play as if they don’t exist. If we are old enough. We can simply wait until we are buried. And then our descendants. They can find that garbage. And desire to know what to do with them. But they are not our problem anymore. 

https://bigthink.com/history-society/the-pressures-pushing-america-toward-short-term-thinking/

Can the AI learn from its mistakes?

That is a good question. The answer is simple. That depends on how the error or mistake is determined. Determining what the mistake or error is is one of the bottlenecks to creating artificial general intelligence (AGI): how to determine right or wrong? How to describe favorable cases. That the AI should use. And. How to determine the non-favorable cases? The latter are cases that the AI should avoid. In the teaching process. The operator determines and describes the case. And then gives it. Positive (favorable) or negative (non-favorable) values. 

In this text. The main topic is reinforcement learning. There, the system makes something, and the environment. It gives feedback. The feedback. Or. The actor who gives feedback. Determines. If the AI acts right or wrong. And how to determine the values “yes” (Positive)(+)  and “no” (Negative)(-)? 

The system could partially follow Boolean algebra. The chain of positive (+) solutions. It can be conjucted by using “AND”. The “OR” changes the model. And if the model gives a negative (-) value. The system turns to using “NOT,” and then the system. It must change the model. The disjunction happens when there are too many negative values in the series of cases. The negation operation makes the system retake the algorithm. And then try another way, or algorithm, to solve the problem. The problem. It must always be solved by following the rules. 

When we think about the trial-and-error model. That model is effective. But not in all cases. This model is also known as the reinforcement model. Trial-and-error model. It is a good tool for virtual cases. But in cases where the AI must drive a car. That kind of learning solution. That can turn very expensive. There are not many ways. How to react to things the right way. Wrong reaction. It can turn fatal. If the AI driver reacts the wrong way. That can be a very big risk.  

When the car stops at a red light. That is the rule. This instruction is for public safety. But what if somebody tries to rob the car? What if a street gang member  shows a red light or “stop sign” to the car? Trying to rob it? That case is not very common. But those special cases show. How difficult. It is to program the AI. The AI is like a student. That system requires intensive training. The AI trainer must give instructions on what to do. And what not to do. 

In simple cases, the AI uses a limited data type. The AI is very easy to teach. The system requires a description of the favorable case. That case is determined as plus. But then the AI requires determination. About the non-favorable cases. The thing that the AI should not do. That is as important as what the AI should do. The AI should also have value. 

What to do if it doesn’t recognize the case? In a virtual world. The AI. It can make as many mistakes as the user allows. But in real life. When AI controls physical things. There is no room for errors. If the AI controls robot forklifts. Those systems can break lots of merchandise. If they work wrong. If the AI controls vehicles. like cars. And it reacts the wrong way. Results can be devastating. In real traffic, the vehicle has no time to wait and analyze opportunities. 

If we want to use virtual environments. The AI can wait. More information for the entire day. The virtual system. It can have endless time to try again. Or wait for more information. 

The world in the virtual environment. There, the system handles things like numbers. There are only two possible cases. Right (+) or wrong (-). But in cases like traffic, there are also plus-minus (±) cases. When AI controls a car. It can face a situation. That there is an emergency vehicle behind it. The AI can be ordered to drive to the sidewalk. The AI must also have orders that it must not impact people. And those cases. That don’t happen very often. They are the most challenging things for the AI. The AI must be prepared. That somebody tries to rob the car. Or there is an emergency vehicle behind it. In a tight avenue. 

Boolean algebra. 

The AI can learn in three main ways. 

1) Reinforcement learning

“In machine learning and optimal control, reinforcement learning (RL) is concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning.” (Wikipedia, Reinforcement learning)

2) Supervised learning

“In machine learning, supervised learning (SL) is a paradigm in which an algorithm learns to map input data to a specific output based on example input-output pairs. This process involves training a statistical model on labeled data. Each input is paired with the correct output. The term "supervised" refers to the role of a teacher, or supervisor. Who provides. This training data guides the algorithm. Towards correct predictions. For instance, if you want a model to identify cats in images, supervised learning would involve feeding it many images of cats (inputs) that are explicitly labeled "cat" (outputs).” (Wikipedia, Supervised learning)

3) Unsupervised learning

“Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks. In the spectrum of supervision. Including weak- or semi-supervision, where a small portion of the data is tagged, and self-supervision. Some researchers consider self-supervised learning a form of unsupervised learning” (Wikipedia, Unsupervised learning)

“In supervised learning, the training data is labeled with the expected answers, while in unsupervised learning, the model identifies patterns or structures in unlabeled data.” (Wikipedia, Supervised learning)

“The typical framing of a reinforcement learning (RL) scenario: an agent takes actions in an environment, which is interpreted into a reward and a state representation, which are fed back to the agent.” (Wikipedia, Reinforcement learning) The thing that gives feedback. Like determining whether the case is favorable. Or non-favorable. It can be the human. 

The main problem with the AI and learning system is. How to determine whether the solution is good or bad. The simplest way is to use a human as a controller. When the algorithm ends its operation. Human operators. They select whether the solution is right or wrong. Determination of the desired solutions. It can also be programmed into the algorithm. In the case of stock marketing, desired. Or. A favorable solution could be maximized income. In the series of actions, the algorithm repeats the action. Time after time. The solution that it pursues. That is, maximizing income. 

Stock market analysis is a simple solution for modeling. The rising line, or rising income. It is the positive solution. The decreasing line is the negative thing. 

This type of machine learning is not hard to make. The user must only determine the highest number. That is, in a certain column. That is what the AI should pursue. In a series of cases, the user marks the wanted solutions, or actions. As positive (+) and negative (-). The thing. The algorithm must pursue. It is the highest possible number of positive solutions. 

The user determines the plus and the minus. And the AI tries to take as many points in the plus column. As possible. The AI, or its teacher, just selects the answer. That is marked as plus. The process requires more than one point. And then the AI follows the line. When the line is rising. The AI makes the right (+) solution. When the line decreases, the solution is wrong (-). 

https://vertexestechnology.com/levels-of-ai/

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

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

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

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

Plasma engines. The route to space planes and interplanetary flight.

“Plasma Jet Engines Could Revolutionize Aviation and End Fossil Fuel Dependency. (CREDIT: Freepik)” (BrighterSide, Next-generation jet engine converts electricity directly into thrust)

In a traditional jet engine, combustion causes the fuel to expand. And then that expansion pushes the aircraft forward. In plasma engines, electromagnetic radiation ionizes air, creating plasma. And then magnets can drive it backwards. This gives. An enormous speed to those ions. The plasma jet and plasma rocket. They are quite the same thing. The difference. Is in the way those engines take gas. That they need. The plasma jet engine takes air from the atmosphere. And then it expands that gas. The plasma rocket uses an internal propellant source. 

But it's possible that a plasma jet can transform into a plasma rocket. The transformation. It happens this way: the system just closes the hatch from the air inlet. And then starts to use its internal propellant storage. These kinds of systems. Their compressor blows air from the side of the engine chamber, which could make it possible to start regular ramjets on the ground. If there is an exhaust hatch and the ability to push air from the side. Makes it possible to launch the nuclear-powered aircraft. Similar to Project Pluto from the regular runways. The hatch at the front of the ramjet allows this system. To drive the exhaust gases to the back. The nuclear engine makes it possible. To create the space plane with unlimited operational time. 

The system. It can make plasma by using electromagnetic radiation. The ionization. At the front of the wing. And a magnetic system. That drives those ions over the wing. It makes the gas move faster above the wing. This causes lift force. Same way as the run on runways causes in the wings of regular aircraft. Same way there is suspicion that the tower. That is in the middle. Of certain saucer-shaped aerial phenomenon. It is meant for some kind of ion propulsion. The system can ionize air. And then drive it very fast over the upper side. Of that kind of saucer-shaped aerial vehicle. That system. It can generate lift-off force by using the ion flow above the craft. 

“Researchers have developed a prototype jet engine powered by microwave air plasmas, offering thrust without fossil fuels. (CREDIT: CC BY-SA 4.0)” (BrighterSide, Next-generation jet engine converts electricity directly into thrust). 

Could this UAP have a plasma engine? That puts gas to flow very fast above this device. Another possibility is that the system. It can have an internal double-propeller system. Like in Kamov-type helicopters. 

In some models, the system creates a ball-shaped plasma structure. Then magnets will drive the plasma forward. That plasma makes the system act like a sail. In this system, the plasma pushes the craft forward. This kind of system can give the craft an ability. To levitate silently.  And if the craft pushes plasma forward. That makes it possible to create aircraft that have no exhaust gases. A plasma engine that takes the gas that it needs from air can fly almost forever. This means those plasma aircraft with plasma jet engines can act as atmospheric satellites. 

They can fly for years. Plasma jet engines. They can also make it possible. To create small-sized drones that have no operational time limits. Because a plasma jet engine is very small. This makes it possible to create pocket-sized drones. That can fly with supersonic speed. The problem is with the power sources. The plasma jet engine requires nuclear power. Or it needs wireless high-voltage energy transfer. The use of traditional turbogenerators onboard the aircraft. 

They are impractical. The aircraft that uses plasma jet engines. They can fly. Also in space.  The plasma jet. It uses internal gas storage. It can transfer to use internal propellant that those systems drive into an expansion chamber. These kinds of space planes. They can make even interplanetary journeys. And operate in other planets' atmospheres. The system can fill its propellant tanks. By using the air that it pulls from the atmosphere. The compressor system can deliver that gas into the expansion chamber. Or it can transfer it into fuel storage. These kinds of space planes could travel to other planets. But they would not be as effective as pulsed plasma fusion systems. The manned interplanetary mission requires something more powerful. Like a so-called VASIMIR (Variable Specific Impulse Magnetoplasma Rocket) engine. 

The interplanetary system. It could generate plasma, or pulsed plasma. By using microwave or laser beams. NASA's innovative electromagnetic microwave propulsion system was the “regular” rocket engine. In that system. Microwaves cause expansion in the propellant. And that makes the system an electromagnetic rocket engine. But when we think about the hybrid systems. That connects the air-breathing plasma engines and plasma rockets. Unmanned interplanetary missions could use that kind of system. To take samples from gas giants like Jupiter and Saturn's atmosphere. If this kind of engine is mounted to SpaceX's Starship. That kind of nuclear-powered shuttle. It could take samples back from Mars to Earth. 

https://www.innovationnewsnetwork.com/the-power-of-plasma-propulsion-a-new-era-in-space-travel/60991/

https://timesofindia.indiatimes.com/science/nasas-new-plasma-engine-could-reduce-travel-time-to-mars/articleshow/130908505.cms

https://www.thebrighterside.news/post/next-generation-jet-engine-converts-electricity-directly-into-thrust/

https://en.wikipedia.org/wiki/Kamov_Ka-25

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

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