New drone carriers are the most dangerous things in the world.

"Illustration of the Jiu Tian drone carrier, the world's largest, poised to revolutionize military operations with drone swarms." (Rude Baguette, “This Isn’t a Ship, It’s a Swarm Factory”: China’s Giant Drone Carrier Alarms Military Analysts Worldwide) The super- and probably hypersonic applications of that system can be more effective than this drone mothership. 

The Chinese drone carrier can be only the beginning of a new type of independent drone swarm carriers. Basically, every type of system can carry drones. Satellites or ballistic missiles can also carry drone capsules. Or things like cluster bomb units can also carry drones. And that makes those systems versatile for many purposes. Regular cargo planes can drop drone swarms from high altitude. 

And things like airships and balloons can also carry capsules that can release drone swarms. A Ukrainian company introduced a small drone boat that carries another drone on its deck. Larger drones can carry more drones than those miniature systems. It’s possible to put quadcopters on the nose of underwater drones and launch those systems underwater. Artificial intelligence gives even small-sized drones the ability to make evasion movements when they detect counterfire. 

Drones can also slip into buildings and observe things like computer screens. Basically, the drone can also insert a USB stick into the targeted system and download computer viruses into that system. A logical bomb is a virus that responds to a certain signal. And that can leave the entire area without defense. A drone can also carry things like a Mesh station. That can link all data that travels on the net to the outsider eavesdropper. 

"Ukrainian unmanned riverine surface drone Ursula, developed by NoviTechNet, carrying a UAV onboard. 2025. Source: YouTube/Association of Ukrainian Engineers." (https://euromaidanpress.com/2025/07/20/drone-boat-ursula/)

NASA plans to drop six helicopters to Mars. But the same technology can be used in drone swarm operations. Images: Rude Baguette

Droneswarms can cause lots of damage in the target areas. The optical fiber makes drones immune to the standard ECM systems. But the high-power EMP can destroy those drones’ electronics. The only weakness of the fiber-optical control system is the wire. If some other drone finds that fiber, it can cut it. Or the laser system can also cut the optical fiber that is behind those drones. But the next step is the AI-controlled drone. The AI allows drones to operate independently without outside control. The laser systems, like optical wireless data transportation, also make it possible to create guidance systems that are hard to jam. 

But those systems require direct contact with the transmitter. This is why things like pseudosatellites or high-altitude platform stations (HAPS) can be the right tools for delivering drone swarms. The HAPS can itself be a robot airplane, balloon, or airship that drops those drone swarms to areas. The drone itself is a multipurpose tool that can search for missing people and give warnings about things like volcanic eruptions. But those systems can also deliver destruction and fear. The high-speed stealth interceptors that can be manned or unmanned systems can deliver drone swarms into the area. Those kamikaze-drones can search and destroy the anti-aircraft systems and keep their crews busy, when the other systems attack harder targets. 

Laser- and microwave-based systems can destroy drone swarms. But those systems must detect drones before they can act. There is always the possibility that drones can travel on the ground or underwater, and then another drone that hits a laser or microwave weapon from behind can destroy those weapons. The power that those systems use should be so high that they destroy the physical components of drone swarms. 

https://euromaidanpress.com/2025/07/20/drone-boat-ursula/

https://www.rudebaguette.com/en/2025/07/america-built-it-but-spain-took-it-as-us-space-balloon-pioneer-gets-snapped-up-and-sparks-furious-clash-over-tech-ownership-and-national-pride/

https://www.rudebaguette.com/en/2025/07/nasa-calls-it-the-skyfall-maneuver-as-plan-to-drop-6-mars-helicopters-mid-air-divides-experts-and-fuels-outrage-over-billion-dollar-space-risks/

https://www.rudebaguette.com/en/2025/07/this-isnt-a-ship-its-a-swarm-factory-chinas-giant-drone-carrier-alarms-military-analysts-worldwide/

https://en.wikipedia.org/wiki/High-altitude_platform_station

The new drone can operate on land, in the air, and underwater.

"Illustration of a 3D-printed drone transitioning between air and water environments, generated by artificial intelligence." (Rude Baguette)

The new drone can operate on land, in the air, and underwater.

In the 1930s, the Soviet engineers tried to create the aircraft-submarine combination. That system could slip near the target underwater and launch attack systems. Then that system can fly away from that area. The problem was that technology was not advanced enough. But AI-controlled quadcopters can make it possible to create that kind of system. Theoretically, the nuclear-powered systems can make even full-size “flying submarines” possible. The system can use quadcopter technology. The new drone can dive and fly. But there is a possibility to make those drones more versatile than systems that can fly and dive. The new drone can have multiple sensors, such as sonars and radar altimeters, at the propeller frames. 

The quadcopters are less sensitive than helicopters to cases where they hit some walls if their propellers are protected by using frames. The rotating frame allows the system to travel through very narrow points. And if the system can adjust the propeller's position by pulling them together when the robot or quadcopter system swims through a narrow hole, it makes those systems more flexible than a regular helicopter can be. 

 But the smaller systems can make it possible to create systems that can fly, dive, and drive on roads. 

The new drone can operate in the air and underwater. An interesting thing in hydro- and aerodynamics is that using the same dimensions, it is possible to make many sizes of crafts from pocket-size applications to truck-size systems. The next step can be a drone that can drive on roads, fly, and travel underwater, which can slip in places where regular drones cannot operate. Those drones can travel in aircraft safety hangars. And the AI-controlled drones can stay on the ground and wait for the right moment. 

That kind of technology is the new tool for many things, from research to leisure, and military applications. The drone that can turn its propellers to push along the frame can make it possible for those systems to operate underwater. Then the propellers or propeller pairs can turn into positions that make the system a “regular” quadcopter. And finally, when the drone operator wants to drive on the road, the propeller frames act as wheels. Those drones can act as research systems, or they can even transport groups of people. 

The high-tech system operates almost independently. And that makes the system easy to handle. Those systems can be manned or unmanned. And they can be dropped from airships, aircraft, or from submarines. The ability to travel on ground, airborne, or underwater makes it possible for drones to operate in complicated situations. They can observe drain systems. They can travel in caves that can be very narrow. The ability to travel in three elements gives those drones abilities that can be used in some accident, or as a military target. 

Theoretically, that kind of drone can carry even small nuclear explosives.  Those drones can be delivered from some airships or bigger drones. And the thing is that those modern drones can be carried using manned aircraft, or some larger-sized drones, or even satellites. There are many roles that drones can play. They can travel over an area and send wake-up signals to the eavesdropping and surveillance tools that somebody has hidden in offices and other rooms.  

https://www.rudebaguette.com/en/2025/07/this-thing-shouldnt-even-work-viral-student-drone-stuns-engineers-as-it-flies-dives-and-swims-like-a-high-tech-beast/                                                                                                                                                                                                                                                                                                                                                                                                                                    

Copyrights are not only things that cause criticisms against the AI-made films.

"Illustration of Netflix's use of generative AI in producing scenes for its original series." (RudeBaguette, “This Isn’t Art, It’s Algorithmic Propaganda”: Netflix’s GenAI VFX in New Series Sparks Industry Backlash and Fan Revolt)

Netflix faced criticism when it changed the' featured scenes using AI. That thing fights against copyrights. Another aspect is that the AI can include an actor's character in movies that are against the actor’s values. But this is not the worst thing on this path. AI-generated movies are tools for propaganda. 

The AI can create characters that look like real people, and those characters can even yell nazi propaganda. The AI can create an artificial model of any person that it sees. So the AI can use images from surveillance cameras to make those images and then put them into a film. That kind of ability allows for the misuse of the AI. 

That kind of tool is dangerous if those films are introduced as real life or documents. Normally, we know that at least most of Western film actors and filmmakers have such high morale that they don’t make those kinds of contracts. But in countries like North Korea, the government plays by different rules. That means those people can make films and use them as propaganda. But in the AI-created films, there is one difference between those films and traditional films. The AI will not say “no”. And that means those tools make everything. That's what their operators want. So, that tool can create anything that its users wish. 

The AI doesn't require any crew, and the operator can do everything alone. The AI has no will. Humans determine the limits of those systems. And there is a possibility that somebody includes their neighbors or other competitors in the surveillance tapes where they steal things. Or the AI can include any person in things like child pornography. You might also think about what things like fake police surveillance tapes can do to humans. That kind of thing can destroy any person’s reputation. 

And there are many different motives for that thing. The political motive could be that the competitor's reputation, or the motive for those things, can be that the competitor in working life can be erased by destroying those people’s reputation. 

https://www.rudebaguette.com/en/2025/07/this-isnt-art-its-algorithmic-propaganda-netflixs-genai-vfx-in-new-series-sparks-industry-backlash-and-fan-revolt/

The new components can boost the AI.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Is AI a black box?

In the black box model, the only thing that means is the thing that the outside observer sees. That thing was the primary element in early 20th-century psychology. And the most modern observation tools are changing that thing. But in the early 20th century the brains were totally unknown. There was no change to research living brains. When EEG systems developed researchers could investigate the brain shell electricity. 

But things like PET and MEG scanners open new ways to see how brains work. But if we think of brain research as the box model, the early 20th-century models were black box models. The modern scanners brought the glass box or white box model to brain research. And the AI brought the grey box to neurology. That means the brain-computer interfaces, BCI, where researchers use brain electricity to control computers and soon read thoughts. 

When developers use the black box method to test programs they simply test that the program works. When we make the black box model for psychological learning methods, we can think about some 9-year-old child. That child can read almost everything and we can put that person to read even complicated scientific articles. The child can read those words but that person doesn’t understand what those things mean. The black box means that the actor can make many things, but the action is the only thing that the outside observer sees. That means that black box applications are not as safe as they could be. 

And most of the computer applications are black boxes for users. A regular user sees the interface and that’s enough.  In the white box or glass box application test, the tester tests the code. In the grey box, the test unit tests the functionality and code in the case of programming. The fact is that the AIs that we see are black-box applications. We see only the command line and the answer or thing that the AI makes. We don’t actually know even if the images and texts that we order the AI to make are made by some humans. 

In the case of the black box, the only thing that matters is that the system gives the right answer. The way the system makes that answer doesn’t matter. The only thing that the user sees means something. 

Is AI a black box? The idea of AI intelligence is something that is handled very little. We know that AI can solve many problems independently, but AI doesn’t know what it really makes. The AI can know many things, but it cannot have deep knowledge about those things. The model is taken from the black box psychology. In black box psychology, the key element is that the behavior that an outsider observer sees is something that we can accept. That means the AI just mimics human intelligence. The black box model means that the AI can give the right answers for some mathematical problems. 

But the same AI cannot make anything else. That is the idea of the black box. In the black box model, the thing that the AI gives the right answer is enough. The AI must do only things that the operator orders. So when the operator asks about the uranium enrichments and something like that the AI must give the answer. It must not make its own connections to things like weapon development. There can be things that deny the AI to give orders that can cause damage to operators or their environment. But those orders are in the AI’s code. The AI doesn't make those orders itself. 

The AI is sliding to the grey box application. For making autonomous learning the AI must have access to its source code. And the second thing is that the AI must have the ability to test the code. The AI can involve three parts. The system that creates the code. Another system that tests and accepts the code. And the last system that keeps the backup copy of the AI source code. A backup is needed for the errors. The system should have the ability to reject the code that is not functional. 

Quantum entanglements and human consciousness.

Researchers noticed that human brains emit light. That very weak light that very sensitive sensors see is the thing that causes interesting ideas and thoughts. The fact is that we know that there is nothing meaningless in human brains. And that strange light must have some connection to brain activity. The question is can part of our thoughts be based on quantum entanglement between some electric or photonic field in human brains? 

The human brains have the capacity to feel magnetic fields because axons transport electric signals. The question is what parts in our brain make that entanglement? Do neurons trap ions like protons into the ion pumps and then make quantum entanglement with them? There is suspicion that the myelin cylinders are the key element in the brain's quantum entanglement. 

If that structure is the thing, that is behind the human brain's superiority it would be the ultimate boost for quantum computing. Researchers can copy that structure into the quantum processors. And make room-temperature quantum computers possible. 

The quantum entanglement can be made between axons or electric fields around axons. We know that human brains will not make anything that it doesn’t need. And the thing is that the very weak light in brains can have its purpose in the thinking process. There is also another interesting thing that researchers noticed. The human brain cells are growing in old age. The memory cells make new neurons all the time. The reason why our cognitive abilities decrease when we turn older is that our brains lose more neurons than they can replace. 

"Liu et al., Physical Review E, 2024

"A closer look at myelin cylinders and its location along the neuron’s axon." (Popular mechanics, Quantum Entanglement in Your Brain Is What Generates Consciousness, Radical Study Suggests)

The finding of the thing. That makes superposition in human brains. Can uncover and supercharge the quantum computer's advance. 

Or neurons start to remove connections faster than before. The destructive thing is that the number of axon connections will decrease so fast that brains cannot adapt to that situation. Our brains simply don't have time to transport memories to the next neuron generation. So do we use our brains less in middle age than in young ages? Do our brains cut so many useless axon connections that they cannot save memories? 

But the problem with alcoholism and some other brain damage caused is that those things destroy brain cells faster than the new brain cells can form. When the memory cell creates a new brain cell, that cell is meaningless without its memories. Brain damage sometimes means that the brain memory neurons have no time to send the memories to those cells. That makes them "empty". 

If those neurons exist they cannot perform the same duties as their precursors can. The cell loses its instructions on how it must make those things. Without those memory units, the neuron cannot do anything. The ability to create new neurons in the old ages makes it theoretically possible to input data, or “train” those new cells and then inject them into human brains. 

The big question is does AI make us less intelligent than our precursors were? The thing is that if a person uses lots of AI the person uses less brain capacity than a person who uses less AI if we think about the neurological aspect, if brains do not use some neural tracks that means that neurons remove those tracks. So if a person writes all texts and draws all things using the AI that can decrease the use of axons and that can decrease the IQ if that happens over a long period. When a person doesn’t use neural tracks that means brains will remove those tracks. 

When people use artificial intelligence for essays they must not think. They must not collect information and the main thing is that they must not process that data. The AI will give them a correct set. And that doesn't give them a chance to process and taste information. In the worst case, the student simply copy-paste the test task to AI. And that makes the essay for them. That doesn't require very much thinking. And in that version, the student cannot advance very much. 

So that means that it’s necessary that people use their brains for thinking. Without thinking, brains disconnect their connections. People say that we should read books and advance our way of thinking. But the problem is this: we have no time to read. 

https://www.euronews.com/next/2025/06/21/using-ai-bots-like-chatgptcould-be-causing-cognitive-decline-new-study-shows

https://www.laptopmag.com/ai/chatgpt-study-by-mit

https://www.popularmechanics.com/science/a65368553/quantum-entanglement-in-brain-consciousness/

 https://www.sciencealert.com/your-brain-emits-a-secret-light-that-scientists-are-trying-to-read

B https://scitechdaily.com/brain-cells-keep-growing-even-in-old-age-study-finds/

Green energy and hydrogen economy.

Things like windmills or wind generators can bring energy to systems that separate hydrogen from seawater. The same electrolytic system that breaks water molecules can also form chlorine and sodium. The other thing that the windmills or wind generators can involve is the radar system. The radar system can also be installed in the wing of the wind generators. That system can have some civil and military applications. 

And in the most futuristic visions, sea-based wind generators can also operate as laser stations. The laser system can be at the foot of the wind generator. And that kind of system can be a very powerful tool. The large carbon dioxide laser that is hidden in the wind generator can be used to destroy even ships by cutting their hulls. 

The hydrogen economy should be the goal for energy. Hydrogen is a fuel that can use existing energy infrastructure.  We all know that hydrogen is easy to get. The green energy and nuclear power can be used to create electrolysis that splits water molecules. But the fact is this. The main problem is the energy that splits water molecules. And another thing is that hydrogen that is created or separated from water doesn’t help with things like greenhouse gasses. 

There are two ways to make pure hydrogen. 

1) The most well-known thing is to separate it from water. The electrolytic system just splits water molecules. 

2) The other way is to split hydrocarbon molecules into carbon and hydrogen. 

If the system filters or otherwise breaks the methane molecules into hydrogen and carbon that removes the greenhouse gas from air. And that decreases methane emissions. The first way to remove carbon is simply to use an active carbon filter. And the other one is to use IR light that gives resonance to the methane molecule. 

The system can simply use centrifugal separation to separate hydrogen and carbon from each other after the system splits the hydrocarbon molecule. In the same way, IR light can separate and break the carbon dioxide molecules. The active carbon filter should also remove oxygen from carbon dioxide molecules. 

The main problem with hydrogen production is that these kinds of systems require money. Another thing is that those windmills and other things change the landscape. And the third thing is that some eagles fly into the wind generators' wings. An interesting thing is that no eagle ever flew in the aircraft's turbine. But because people see that one eagle flies against the wind generator's wings. 

That makes them resist the wind energy. People don't see that thousands of eagle chicks die because of thirst and heat in forests.  They see that the one eagle smashed into the wings of the wind generator. And that makes that system dangerous. The fact is that if we think about how the electricity should be pumped to the electric network we should never put electricity straight into those electric networks. 

The system requires a battery system. That helps to keep the voltage stable on cloudy days if the system uses solar panels. Or calm, in the case of wind energy. And another thing is that. The system must not be based on one monolith solution. The system should have multiple systems. That produces electricity even if there are calm days. The battery platforms between the power unit and network help to avoid situations that cause electric cuts in southern Europe. 

The worst possible situation could be that the solar panels will not produce enough energy. That means that other systems must increase their power to maintain the voltage. Then if energy production suddenly starts again. That causes an overload in the network. That is more dangerous than the low voltage situations.