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

Why does the AI change answers all the time?

“ChatGPT may sound confident, but when tested on complex scientific claims, it often guesses and even contradicts itself. Researchers found it struggles especially with spotting false information. Credit: Shutterstock”(ScitechDaily, ChatGPT Was Asked the Same Question 10 Times. The Answers Kept Changing)

“In the initial 2024 experiment, ChatGPT answered correctly 76.5% of the time. When the study was repeated in 2025, accuracy rose slightly to 80%. However, once the results were adjusted for random guessing, the performance looked far less reliable. The AI was only about 60% better than chance, which the researchers described as closer to a low D than strong performance.”(ScitechDaily, ChatGPT Was Asked the Same Question 10 Times. The Answers Kept Changing)

“The system had particular difficulty identifying false statements, correctly labeling them only 16.4% of the time. It also showed inconsistency. When given the exact same prompt 10 times, ChatGPT produced consistent results for only about 73% of the cases.”(ScitechDaily, ChatGPT Was Asked the Same Question 10 Times. The Answers Kept Changing)

Researchers talk about those cases like this. “We used 10 prompts with the same exact question. Everything was identical. It would answer true. Next, it says it’s false. It’s true, it’s false, false, true. There were several cases where there were five true, five false.” (ScitechDaily, ChatGPT Was Asked the Same Question 10 Times. The Answers Kept Changing)

The reason for that is the accumulation of information. When the researchers ask exactly the same questions hundreds or thousands of times. That causes data accumulation. Another thing is that. There is probably a pointer in the algorithm. That tells whether the answer satisfies the user. If the user does not stop the algorithm. While bombarding it with the same question. 

The algorithm interprets. That situation. That there is something wrong in the answer. If the user drives the same algorithm.  Again and again.  There is a possibility. That some router. Or a switch is stuck. This can cause a situation. That the system gives different answers. When the AI gives an answer that remains. It's RAM memory. If the algorithm runs in a loop, the question repeats. 

Time after time. That can also fill the memory of the central servers. So, before the next run. The user must remove the garbage or the data from the RAM. The system must have time to stop the algorithm and then clean its memory. If that is not done. The memory. It can be filled. And data. It can be polluted. 

The user should finish the job first. That happens by telling the AI that it’s time to begin the new operation. 

We all know that 1+1=2.But sometimes a stuck switch, or gate. Causes. That microchip fails in the simplest possible calculation.  And tells researchers that 1+1=3. The failure in a processor’s internal structure. It can make it break mathematical rules. 

The situation is similar. To cases. There are binary microchips that calculate 1+1=3. This happens sometimes. When the binary processors are tested by calculating 1+1 thousands or billions of times. Suddenly. A microchip. It can give an answer that can surprise us. The reason why the computer gives 1+1=3 is in Boolean algebra and switches. When the system runs 1+1 many times. That simple calculation jams the switch. And that causes the wrong answer. 

The biggest problem with AI is that. The same AI should handle all types of things. There is no human on Earth. Who knows everything. The limit. Of the sector. Of AI use. It can make it more trustworthy. If the same AI is used for fun and for things like scientific work. That causes the data that it involves. Scientific data and other types of data. Like poems. The biggest problem is that. The AI will not make. A difference between the sources. The AI handles all homepages the same way. The thing that makes AI more trustworthy is that. Its data source. It can use. They are limited to trusted scientific homepages. In cases like entertainment purposes. The AI must not use data in a similar way. 

Did you ask something? From the AI? Then you might notice that the answer changes all the time. The reason for that is in the AI, or LLM (Large Language Model). And especially in its structure. The AI is a cloud-based solution. The giant entirety. People who use AI might think that they are using their private software. The LLM or AI is a giant network of databases and servers. When somebody uses those systems. The system scales that interaction all over the network. So, every user in that kind of AI is participating.

 In the AI-training mission. Even if other users cannot see directly what other people ask. That data grows and refines the dataset. That. The system involves. When we ask something.  From the AI. It searches data. From its own registers. The AI searches. Is there the same question? And then the list of data sources that the LLM used. Questions. That people make. They might be from the same topics. But. They are a little. A bit differently written. 

What is the heaviest stable element? It is not the same question. As the question: “What is the heaviest non-radioactive element”?

The AI uses statistical methods to generate answers. This means that the homepages that the AI uses must be involved. A certain number of references that match the question. The AI must know the trusted data sources it can use. If the AI is used for scientific work. Things like thesis banks, universities, and national institutions offer very qualified information.  But then. We must be careful. When we use the AI. When we ask things like the heaviest known stable element. The AI might give an answer. That is wrong. It might tell.

That Oganesson is the heaviest stable element. Oganesson, element 118, is a very unstable element that decays in less than a microsecond. This means AI makes a mistake. And the reason for the mistake is in the way of thinking. The AI can “think” that the person who asks that question. Means the heaviest element that exists is confirmed. And the element is connected to the periodic table of elements. Normally, that question means the heaviest non-radioactive element. But as I just wrote. AI understands. This is the heaviest element. That has its place in the periodic table of elements. So, we should ask: what is the name of the heaviest non-radioactive element? 

This means that the AI translates and treats them as different questions. The system searches data from its internal registers. But if the questions about the topics are a little bit different. The AI also searches data from the network. This means the AI accumulates information about the source lists in its memory. And when data is accumulated. The AI will use different data sources. The other thing is that. When the LLM makes a search and opens homepages. It changes the homepage's page rank. And that also causes a situation. 

There, the AI’s answers are changing. The other thing is that the AI’s answers will be turned into the homepages. And that makes the AI recycle its output. This is the big problem for the net. The dead internet means that AI generates more and more material for it. That generates and accumulates. A data mass. The same data repeats again and again. This way of generating answers fills the servers. Another problem is that. For generating good answers. Those AIs require well-articulated questions. But another fact is that. A good-looking answer is probably not the best or right answer. 

The problem is that. The wrong answers might look funny. People share them on social media. This causes a situation. Those incorrect answers affect the page ranking. They are visible in discussion forums. If those incorrect answers are often shared. They are seen in the statistics. And that can make the AI repeat them. The problem is that. 

The AI searches data using statistical methods. Page ranking and the involvement of certain words in the list of words that are used in those pages. Make the AI select them. As the data source. Statistical methods. Don’t make a difference between right and wrong information. Or wrong information. The ability to limit. The use of data sources from trusted organizations. Makes AI more trusted.

The big problem is that. The AI causes. Those markings that people normally make become unclear. This breaks. The AI use. In medical work. If people do not make queries or make their markings as they should. That can break the AI. The AI’s purpose. It is to save the medical staff time. In the same way. It's made to make work easier. But the problem is that. Employers see the AI as a chance to fire workers. And if we think that way. The AI benefits only the owners of the companies. 

https://scitechdaily.com/chatgpt-was-asked-the-same-question-10-times-the-answers-kept-changing/

New autonomous fighters entering service.

Autonomous jet fighters are actually large-sized drones. Those drones can operate like manned jet fighters. They can make almost all missions as humans. And those drones can be robotic versions of regular fighters. Like F-15,F-16 and F/A-18. Or they can be specially made for drone missions like Kratos QF-58 “Valkyrie”, or FQ-42, and FQ-44. The idea of robotic jet fighters is not new. During WW2, there were plans to create a Western version of the “Kamikaze”. The Western version of the Kamikaze. It was a remote-controlled. An aircraft that could dive to the target and be controlled from other aircraft. The first attempts to use remotely controlled aircraft, like radio-controlled B-24 Liberators and B-17 Flying Fortresses, against German V-1 production. 

Those early drones were unsuccessful. And the reason for that was primitive technology. Another idea was that CAM ships were equipped with radio-controlled V-1 or later Regulus missiles. The idea was that those systems could attack enemy ships. Even if “Operation Aphrodite” was unsuccessful. The idea of those long-range drones remains. 

But then, long after the WW2. Things, encoded radio transmitters, and more effective computer technology made those systems suitable for operational use. There were ideas to use the target drones. Like QF-4 Phantoms.  And QF-16 fighting Falcons. Also. For Kamikaze missions.  Those drones could also fly. With manned aircraft. And pull the enemy's notice to them. The drone can fly into enemy airspace. And then the enemy aircraft and anti-aircraft systems. They can aim at those non-stealth aircraft. And the F-35 type stealth aircraft can follow them. 

The first so-called killer drones were MQ-1 “Predators” and MQ-9 “Reapers”. Those drones were and are made for anti-guerilla operations. So they are vulnerable to air defense and other drones. There is also. A possibility to use the robot jet fighter in attack missions. Those systems require the same technology. As those slower drones. But in those missions, the problem is electronic warfare. But advanced AI makes those systems more effective. The main problem with “Predators” and “Reapers” is that they are slow. They have an old-fashioned stealth technology. And this makes them an easy target. Those systems are used to force the enemy to open fire. And then stealth aircraft will attack those flak systems. 

But the problem is that. The robot aircraft requires more advanced stealth technology. And independent AI to accomplish their missions. The modern jet fighter. It can cooperate with drones. The drone can fly near the fighter. And it can be used for attacks at low altitude and high-risk targets. Those drones can make the attack. When the jet fighter is backward. The drone can have internal warheads. It can also be equipped with missiles and bombs. 

In some ideas, the B-52 type strategic bombers. They could be transformed into robots. The system finds its targets. The aircraft. It can find its targets using radars and other systems. In some cases. The small stealth aircraft can drop a drone. On the roof of the target. The bomber or attack fighter activates the target locator by using radar. A drone can use a radio transmitter. Or it can use lasers to point at the target. And then the bomber. It can drop its weapons on that target. 

In original ideas, the system that uses crossing radio signals will make the aircraft. To fly into its target. The crossing radio signal over the target makes the system open the bomb hatches and drop them. The system is based on the “Loran” technology. The aircraft. It flies to the target by using the radio beam. That is aimed at the target. Then the aircraft crosses the first crossing radio signal. That orders it. To open bomb hatches. Then another crossing radio beam orders the aircraft to drop its bombs. The problem was: how to deny the enemy from spoofing the radio signal. The answer was the encoded radio transmission. 

Another version was the AI that uses the TERCOM system. Or a TERCOM-inertial hybrid system.  To find the target. The system can use optical image recognition for search and lock onto the target. This means that independently operating drones. They are more immune to electronic warfare. Than the remotely controlled systems. 

The system requires training. And the thing is that. The F-35 can collect data that those drones require. Those drones can also operate independently. And the air-to-air capable drones. They can be launched against the enemy bombers and fighters from catapults. The drone-plane. It can also carry anti-radiation missiles. Those systems can be used against the electronic warfare systems. And they can open a path to other drones and aircraft. 

https://interestingengineering.com/military/us-production-of-autonomous-fighter-jets

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

https://en.wikipedia.org/wiki/General_Atomics_MQ-1_Predator

https://en.wikipedia.org/wiki/General_Atomics_MQ-9_Reaper

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

Can private corporations offer a chance to respond? To the new challenges in space?

 

“SpaceX launched the NROL-179 mission for the U.S. government early Friday morning (June 19) from Vandenberg Space Force Base in California. (Image credit: SpaceX) (Space.com, SpaceX launches new batch of US spy satellites from California (video))

SpaceX  launched NRO recon satellites from Vandenberg. Details of those satellites are classified. But because NRO operates reconnaissance satellites. Those satellites’ mission is  connected to intelligence operations. This means that the U.S. strengthens its spaceborne abilities. 

But that launch itself. It causes discussions. About the role of Elon Musk and the SpaceX corporation in governmental operations. Those satellites play a vital role in space-based targeting and other types of missions. And they offer the ability. To see things that are hidden from other actors. The space gives SpaceX the possibility to rule those areas. And people are concerned about the strength. Of the SpaceX corporation. 

NASA attempts to save the SWIFT telescope. It can also have dimensions. That we ever imagined. The Katalyst corporation is the actor behind the satellite. That should do the mission. 

The same rockets that can transport things.Like satellites to space. They can also be used to carry killer satellites. NASA plans to launch. A miniature satellite that takes the Swift telescope by using manipulators. The satellite can push the SWIFT telescope into the right trajectory.  By using the hydraulic piston. The satellite can also use manipulators to throw the telescope. Or a miniature satellite. It can be used as a space tug. That pulls the damaged telescope to the right trajectory. The satellite that should do that mission is made  by the Katalyst corporation. 

And the knowledge of the satellites' trajectories is the thing. That allows them to affect them. And we know that the same system. That can push  space telescopes. Into another trajectory. That system can also throw other satellites into the atmosphere. This makes the attempt to rescue the space telescope by using another satellite. That will be launched by using the Pegasus rocket. The Pegasus is an airborne-launched system. That rocket. It can transport a small satellite to the orbiter. And the satellite. It can use similar systems. These are used in the case of the Swift telescope. For pushing the targeted satellite back into the atmosphere. And those kinds of systems. 

The mission profile for that service flight. For the rescue SWIFT telescope. 

They can be used to find and affect killer satellites. Or. So-called sleeping FOBS (fractional orbital bombardment system) satellites. Those spaceborne nukes. They  can be used for surprise attacks. The FOBS satellite. It can be used as a nuclear-based EMP(electromagnetic pulse) system. In simulations. The EMP impulses can be used to prepare the opponent for a nuclear strike. The idea in those systems is that a high-power nuclear explosion at high altitude paralyzes electronics before the nuclear mass raid. In 1962, the high altitude nuclear test “Starfish Prime” was conducted above Honolulu. The 1,4 megaton exoatmospheric nuclear explosion caused electronics to be destroyed all around Honolulu. 

Modern electronics are more vulnerable to spaceborne nuclear explosions and their EMP pulses than 1960’s primitive technology. The EMP causes a situation. All communications are shut down. The jetfighters. They cannot rise to defense. And it’s possible that missiles cannot be launched because the EMP destroyed their electronics. Or the transmitters that should transmit launching signals are destroyed. The ability to find those FOBS satellites. It makes it possible to deny the surprise attacks using the sleeping nuclear detonation satellites. There is. The ability to push them into the atmosphere is the thing. That makes them unable to complete their missions. 

The problem with the nuclear-powered EMP is that. The 1,4 megaton hydrogen bomb is not the limit of those weapons. The EMP weapon. It can be much more powerful than the 1,4 megaton bomb. Used in Starfish Prime. The EMP satellites can also form a network all around the world. The large-scale EMP strike can have a destructive effect on fleet and ground-based infrastructure. 

Wikipedia says the Russian killer satellite program is like this: “Nivelir (Russian: "dumpy level"; Project 14K167) is a class of Russian military low Earth orbit (LEO) satellites widely believed to be co-orbital anti-satellite weapons (ASAT) with secondary space surveillance missions. The spacecraft are often compared to Matryoshka "nesting dolls". As each contains a smaller inspector subsatellite, which can itself. Deploy one or more kinetic kill vehicles (KKV).” Wikipedia, Nivelir) 

The first of those satellites was launched in 2022. And there is a possibility that the Russians plan to create Earth-orbiting nuclear-armed satellites. Those satellites can drop a nuclear bomb on cities. Or they can detonate their internal warheads in surprise attacks. Detonating those satellites is not very difficult. The system is like a high-tech car bomb. When that satellite is in the right position. The system. It gives a launching code. Then the nuclear warhead detonates. The only problem is that EMP also destroys friendly satellites. 

https://www.nro.gov/Portals/135/Documents/news/Press%20Kits/10463_Press%20Kit%20book_Launch_Pro-Arch179_6.11.26.pdf?ver=0v03xnXSpOK_ni7ywyhemw%3d%3d

https://roboticsandautomationnews.com/2025/10/01/nasa-awards-30-million-to-katalyst-space-technologies-to-rescue-500-million-satellite/95080/

https://www.space.com/space-exploration/launches-spacecraft/spacex-spy-satellite-launch-nrol-179-nro

https://www.the-sun.com/news/14598954/russian-killer-satellite-us-spacecraft/

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

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

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

18 stealth ships can protect the entire U.S carrier fleet.

“San Francisco, Calif. (Mar. 18, 1999) The U.S. Navy Sea Shadow (IX-529) craft gets underway at dusk to participate in events associated with Fleet Battle Experiment-Echo, sponsored by Commander, Third Fleet and the Maritime Battle Center. Sea Shadow was reactivated this year to support the evaluation of future Navy ship designs and technologies, including automation for reduced manning, propulsion concepts, and characteristics of surface ship stealth.” (Wikipedia, Sea Shadow (IX-529))

The new ship designs are based on stealth technology. In the new designs and visions for fast reconnaissance, patrol, and attack craft. The craft itself can look a little bit like a blackbird. That biomimicking outfit makes radar impulses to slide away from the transmitter. The craft itself would be catamarans with two underwater keels. And the boat would look like. Being lying on two torpedoes. Those underwater structures give them incredible speed. The Sea Shadow retired and was scrapped in 2012. But  modern specialists think that 18 stealth crafts can protect the entire U.S. carrier fleet. 

These two crafts. Retired Sea Shadow and the Ghost boats can operate. Along with bigger ships. The Sea Shadow uses technology. Developed for F-117 Night Hawk. The Sea Shadow can drop torpedoes or launch missiles between its keels. That makes it possible to open fire without. Breaking the stealth form of the craft. If the torpedo or missile hatches are at the bottom of the craft. The craft can drop those weapons into the water. And those launches will be harder to detect. Especially if some kind of drone. 

It carries the weapon a certain distance from the Sea Shadow. That craft is one of the stealth ships in service. The Juliet Marine System’s Ghost boat is a smaller and very fast stealth boat. “Juliet Marine Systems Ghost is a super-cavitating stealth ship. The ship's experimental hull design can reduce hull friction to 1/900th that of conventional watercraft. Ghost was designed, developed, and built by the private American company Juliet Marine Systems.” (Wikipedia, Juliet Marine Systems Ghost)

Juliet Marine System Ghost. The craft could carry two Harpoon or SLAM missiles under its hatches. 

The Corsair drone boat. That picked the downed Apache Crew. Out Of The Gulf of Oman

That system can operate with special forces or attack craft. There is also a possibility of using that system as a surface drone. The surface drone can be used for reconnaissance or attack missions. The kamikaze-sea drone can carry an internal. Conventional or nuclear explosives. The drone can also carry other drones or missiles. That makes them more versatile. 

Or they can save things like pilots. Who were shot down. This kind of mission is made. In the Hormuz Strait. When the U.S AH-64 “Apache” helicopter was shot down by Iran. The sea drone picked the crew out of the water. The drone was not the Ghost boat. But the mission introduced a new doctrine in naval operations. 

The small vehicles can be carried to the operational zone on bigger ships. The ships could carry those smaller boats in the dry pools. In their hull. When those bigger ships require their drones. They can fill that pool with water and release them against the enemy. The idea is taken from the model. Of the WWII tactical scenario. There are landing ships that normally carry small landing craft. Could carry torpedo boats.  When the enemy attacks, those torpedo boats will be released from that dock. The large-sized landing ship could also carry those sea drones. 

https://www.businessinsider.com/juliet-marine-systems-ghost-boat-2016-11

https://theaviationgeekclub.com/18-sea-shadow-stealth-ships-could-protect-the-entire-us-navy-carrier-fleet-remembering-the-warship-that-used-the-stealth-technology-of-the-f-117-nighthawk/amp/

https://www.twz.com/news-features/ah-64-apache-crew-rescued-by-drone-boat-after-going-down-near-strait-of-hormuz

https://www.twz.com/sea/this-is-the-corsair-drone-boat-that-plucked-the-downed-apache-crew-out-of-the-gulf-of-oman

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

https://en.wikipedia.org/wiki/Sea_Shadow_(IX-529)

The key element of drones: flexibility.

As we know the drone. It can transport pizza to the right balcony. But the thing that we don’t normally think about is this. The same drone that delivers pizza at a certain point in the city. It can also transport grenades or bombs to the same point. This is the reason. For why this AI-controlled Skyways drone is so interesting. The drone can transport equipment and food. Into the precisely right position. The drone can make the same thing. With grenades and depth charges. Or it’s pizza can be replaced by using the radar antenna. So those drones can operate as miniature AWACS platforms. 

Those drones with radar systems can see at least larger drones. That flies below them. The radar observation drone can map underground tunnels. A swarm of those drones can communicate. With command, control, and communication platforms. This means that the AWACS platform outsourced its radar to other aircraft.  And that helps the crew to survive if the anti-radiation missile locks on those radars. 

So that makes those drones very versatile. Even if they are standard versions. The bigger drone. It can also operate with other drones. The bigger drone can carry a smaller drone. 

This means that the quadcopter strike drone can be dropped near the target. And those drones. They can use those drones. As aerospace relay satellites. The drone that flies over the area can also send a signal to eavesdropping systems.  To deliver the data that they recorded. Those “sleeping systems”. They can be extremely dangerous. The scanner doesn´t see those passive systems that record speech or data. When the system sends a radio signal, it sends recorded data to that drone. 

Or. It can pull another drone or missile behind it. That kind of system can launch the drone from the right position. And that increases their ability to operate. The pizza drone can also drop a quadcopter into the right position. And those copters can operate as reconnaissance or kamikaze missions. In pure reconnaissance missions, drones can be equipped with microphones or seismic sensors. That can deliver information to the command centers. 

This ability makes drones more versatile than traditional systems. The kamikaze drone can also send reconnaissance data for its operators. The thing about the quadcopters is that. Those drones. They can also transport guns like automatic pistols or small submachine guns. So they can be the most dangerous things in the wrong hands.