Autonomous drone technology is advancing.

Drones are game changers in the Ukrainian conflict. Their R&D cycle is so short. That things that had top priority a couple of months ago. They can become old-fashioned in a couple of months.  We know that without drones. Ukrainian defence would fall. The new autonomous, AI drones are now in use. Autonomous AI-controlled drones are the new tools for military and other systems that must operate in places. There.  EM radiation can disturb control signals. The optical wire-controlled drones are effective. But their optical wire causes limitations. In the worst cases, those wires can be spotted. And the laser systems or drones. The mechanical cutters installed can cut that wire. The wire-controlled drone. It also has limits in its operational range. 

The independently operating drones that can use AI to search and destroy targets are the new tools. The independently operating drones can be like full-size aircraft. Or some other vehicles. Drones. They can transmit reconnaissance data. During their flight to the target. They can also be used to transmit data. About the radars and target detection routines of the anti-aircraft systems. 

The first independent fighter drones made their debut. In combat exercises. Those “Ghost Bat” drones. They are the first public versions of the AI-driven systems. The AI-driven long-range stealth drones. They can be the response to the extremely long-range operations. Like Iranian nuclear facility destruction. The B-2 bombers. They made that mission. In a 36-hour operation. There, they dropped GBU-57MOP bunker-buster bombs on those targets. Those MOP bombs. They can also destroy nuclear missiles in their silos. 

The AI-controlled jet fighters. They can make those systems. More surprising than ever before. The AI-controlled systems. They can make kamikaze attacks. And they have the ability to make air-combat manoeuvres during those operations. Data that those drones share.Can be used to train AI. Training AI pilots can be done by using simulators. The simulator operators create tactics and manoeuvres that are suitable for any situation. The AI that operates aircraft is quite easy to train. 

A normal flight combat simulator. It can be used as an interface that trains those drones. AI can give a new dimension. To the loyal wingmen drones. Those drones. They could act as jet fighters. But they could also act as missiles. Same way as aircraft. Naval vessels can get a seaborne version of those loyal wingmen. This means that submarines and surface ships can be escorted by kamikaze boats or small underwater kamikaze drones. The kamikaze drone boats. 

Electric-powered versions of drones. They could operate under and above the surface. The nuclear batteries. They can give all surface-, underwater. And airborne vehicles unlimited operational time. 

They can also escort any surface vessel. Things like RTG (Radioisotope Thermoelectric Generators) give underwater and other drones virtually unlimited operational range. Transforming some Shahed-type drones into RTG-powered drones is not very difficult. The drone requires a nuclear isotope battery. Those drones might not make attacks. Or they can carry missiles and drones under them. Even if those drones are slow. They might not be easy targets. Stealth technology makes them invisible to radar. So. Small-sized RTG-powered drones. They can operate unseen in hostile airspace. 

And an electric engine. It could carry an attack drone under it. The problem. It is that. If those nuclear batteries fall into the wrong hands. That radioactive material can turn dangerous. But the RTG is a suitable powerhouse. For the nuclear-warhead torpedoes. And the nuclear-powered airborne drone. It can turn. To use a jet engine when it must make an attack. The nuclear-powered reconnaissance drone can operate indefinitely. But attack drones must have conventional engines. Unlike nuclear reactor-based technology. 

The RTG is suitable for high-flying stealth drones. They don’t leave a radioactive trace behind them. Those drones don’t need oxygen. The nuclear-powered drone can fly at very high altitude. Even if aerodynamic controls don’t work. The drone. It can glide to lower altitudes.

The larger-sized drones can carry smaller drones. And the new tools are the underwater drones. The underwater drone can conduct reconnaissance and intelligence missions in enemy areas. Those drones can also protect larger submarines. When we think about underwater. Long-range nuclear torpedoes. Those weapons are not always 50 megaton-class. The 10-15 kt warhead . It makes it possible. To create an unmanned system. That fits into the torpedo tube. 

Small unmanned drones can escort larger submarines. When something threatens those submarines, those underwater loyal wingman drones. They can attack that threat. Those drones. They can use hydrogen-oxygen. Air-independent power sources. That system uses bottled hydrogen and oxygen in its power cells. 

And they can carry other drones. Those drones. They can make operations into hostile harbours. And then they can cause damage to the larger vessels' hulls. In the case of submarines, even a small hole. In its pressure hull can turn devastating. In the same way. Stealth aircraft, along with supersonic- and hypersonic systems. They are more vulnerable than old-fashioned systems. 

https://www.autonocion.com/us/america-drone-submarine-torpedo-tube/

https://www.bbc.com/news/articles/cdjp0n7rn41o

https://interestingengineering.com/innovation/us-darpa-retrofit-f16-for-autonomous-flight

https://interestingengineering.com/military/china-truck-mounted-electromagnetic-catapult-drones

https://militarywatchmagazine.com/article/ukraine-fp9-threat-russian-cities

https://www.twz.com/air/massive-chinese-stealth-flying-wings-spotted-together-at-secretive-drone-test-base

https://www.twz.com/air/mq-28-ghost-bat-drone-debuts-in-large-force-combat-exercise-in-the-pacific

https://www.twz.com/air/pocket-fleet-of-mq-1-predators-still-serving-navy-test-community

https://vivatech.com/news/autonomous-drone-technology-uses-benefits-and-future-impact

https://www.twz.com/sea/kamikaze-drone-boats-used-by-u-s-in-combat-for-the-first-time

https://www.twz.com/sea/ukraine-lands-armed-robot-ashore-in-russian-held-territory-via-drone-boat

https://en.wikipedia.org/wiki/GBU-57A/B_MOP

https://en.wikipedia.org/wiki/Poseidon_(unmanned_underwater_vehicle)

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

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

Transporter gliders are coming back.

A rendering of a freighter plane pulling a cargo glider. (Aerolane) (Ttnews,Aerolane Seeks to Use Freighter Planes to Pull Cargo Gliders)

Large-sized gliders used in WWII to carry jeeps and cannons to airborne troops. Then those gliders disappeared. The new large-sized, wide-body cargo planes made those gliders unnecessary. And they left out the air. But the large-sized cargo gliders are making a comeback. Expensive gasoline makes those cargo planes a reasonable solution for decreasing costs in civil and military aviation. The glider that the cargo plane pulls behind it can decrease fuel use by over 60%. And those flying trucks are new tools for making new types of cargo systems. 

Gliders could also transport troops on the roofs of buildings. And they could carry things like equipment to the disaster areas. As well as. They could carry people and cargo to regular airfields. Those gliders can carry large structures through the air. And they can make a revolution for air cargo. Those gliders can be. The systems that are AI-controlled. So those systems don’t need pilots. 

But the fact is that. The aircraft can also pull jet fighters or cruise missiles behind it. Near the operational area, those fighters would be released. And that makes them operate. With more fuel. Then, if they would fly to that area by using their own engines. This technology has been tested in some parasitic jet fighter programs. The idea was that the escort fighters would travel under the wing, or be pulled by bombers. This would be the answer to the problem that those escort fighters had a far shorter combat radius than strategic bombers. 

“A German defense company has successfully tested an uncrewed cargo glider designed to support frontline military units, a technology that Tokyo is also exploring as it looks to bolster its capabilities in islands to the far southwest of the Japanese archipelago.” (SCMP, Can German stealth cargo gliders boost Japan’s remote island defence and logistics?) 

"Logistic Gliders Inc. tested a dozen prototype cargo gliders, deploying them from carrier aircraft and landing them in the desert. PHOTO: LOGISTIC GLIDERS INC." (IeeeSpectrum, Disposable Delivery Drones Undergo Successful Tests With U.S. Marines)

The Waco CG-4 Cargo glider was a typical cargo glider of World War II. (Wikipedia)

Shahed-131

MQ-9

The stealth cargo gliders can also act as weapons. The same system that carries cargo to a certain point. It, or its miniaturized version, could carry a warhead to a similar point. The aircraft could pull glide bombs behind them. 

Another thing that glider technology can give is the technology. There, one cruise missile pulls the other behind it. That could almost double the range of those weapons. 

The nuclear-powered drone. That uses. A Radioisotope thermoelectric generator (RTG). That system gives those drones an unlimited range. As a power source for the electric engine. This drone can pull another drone with a conventional engine behind it. Or the drone can pull things like cruise missiles behind it. This gives the missile. An extended operational radius. Things like Shahed-131-type. Drones can be equipped with RTG-driven electric engines. 

And they can pull another drone behind them. In some idea, RTG-powered MQ-9 Reaper-type drones are tools that can pull cruise missiles or Shader-131 drones behind them. Those systems can have a capacity for long-range operations. Those drones can have. The AI-based target recognition system. And the same seeker that is used in Hellfire missiles. 

https://www.aerolane.com/products

https://spectrum.ieee.org/disposable-delivery-drones-undergo-successful-tests-with-us-marines

https://www.scmp.com/week-asia/politics/article/3343528/can-german-stealth-cargo-gliders-boost-japans-remote-island-defence-and-logistics

https://www.ttnews.com/articles/aerolane-gliders-airfreight

https://www.twz.com/news-features/how-americas-shahed-136-clone-became-an-indispensible-weapon-of-war

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

https://en.wikipedia.org/wiki/Shahed_131

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

https://en.wikipedia.org/wiki/Waco_CG-4

A Chinese firm said that it tracked the U.S. B-2 bombers over Iran.

There is a possibility of using systems, such as optical telescope networks and ultra-sensitive microphones. Along with lidar and very thin, coherent radio signals to track stealth aircraft. The AI can collect and connect information from those sensors into one hub. The system bases the machine vision on the combination of the sensor networks. And those kinds of systems are very hard to jam. The system can also use satellites, or high-flying airships (”atmospheric satellites”) to detect stealth aircraft by using optical sensors and machine vision. 

The radar-based systems. They can see stealth bombers as a shadow against the ground. Or the system can use miniature satellites or atmospheric satellites in two layers. The network of those systems hovers above the land-based systems. The system sends coherent signals between those two layers. And if a stealth aircraft travels between them, it cuts the signals. 

The quantum radar and nano-technology-based “radio lasers” are tools. That can endanger stealth protection. The coherent thin radio signal could be hard to detect from its sides. This means that the fast-moving antenna can scan the sky. And those systems can be hard to detect. Passive, infrared, image recognition systems are also tools that can cause grey hair to stealth designers. The lidar systems can also use frequencies that military systems do not often scan. In some cases, the detector benefits the microparticles. When a stealth aircraft travels through. The microparticle cloud. It affects those particles. And the sensor sees that thing indirectly. Indirect observation uses a medium. Like air flows to detect a stealth aircraft. 

The system that shoots down the stealth aircraft can be a missile or a cannon, which is connected to a network of different sensors. Those systems can be used. The combination of lidar and optical machine vision-based sensors. Those missiles are not using a regular IR-signature to detect and destroy targets. They recognize the shape of the target. And this makes them hard to jam. Things like drone swarms that can block the route of the stealth bombers are also dangerous. If a low-flying stealth bomber hits those drones. That can cause fatal damage to the aircraft. 

https://interestingengineering.com/military/china-us-bombers-tracked-epic-fury

Is AI just a tool?

“A new study explores how interactions with generative AI may influence the way people form and reinforce beliefs, particularly when technology becomes part of everyday thinking processes. Credit: Stock” (ScitechDaily, Is AI Really Just a Tool? It Could Be Altering How You See Reality)

Somebody thinks. That AI is just another wheel. The AI is something that we use, and that’s it. But. The big thing. In AI, it is that. It’s far more. Than just some kind of tool. The AI is a flexible model for information. AI is like a human; it just doesn’t create information from emptiness. It processes information. That it gets from different sources. The system involves an algorithm, the program that collects information from sensors and databases. Another thing. In. AI is a computer program. The AI collects and processes a lot of data. But the problem is that. It uses databases. It doesn’t actually know if the information is false or true. 

In the same way, AI doesn’t think for itself about whether something is moral or ethical. The user teaches AI. And. The user selects what is right or wrong. And that is dangerous. There are people who are not normal. And if those people train an AI agent. That thing can turn into a catastrophe. The AI itself doesn’t cheat. It’s programmed to cheat. 

But humans either automatically know. Is the information. That we get true or false. Another thing is that the AI has an addictive psychological ability. Users select AI. That they feel most comfortable. This means that programmers do a lot of work to create AI that pleases users. And that is the thing that sometimes gets too far. The AI is a tool that is coming. The AI. It can have similar effects to net porn and some computer games. The AI can addict people. And they spend too much time with it. So, they get a headache. Sleepless and many other things, when they create things with AI.

 AI might look and feel like. A real human. It can discuss with people. And that forms an illusion that there is a human on the other side of the net. The AI. It can mimic feelings. And give advice. That feels very effective. But there are limits to the AI. And its use for things like a therapist. The AI should not have access to give psychotherapy. And the second thing is this. There must be some limits on things. That the user can ask the AI to do.  If a person asks AI to complete violent requests, they should have access to, or the order to, call a psychologist. 

There must be some kind of protocol that allows AI to pick dangerous people, like serial killers and suicide candidates. We know that there are lots of people. Aho asks the AI something that they would not dare to ask a real humans. The AI is a tool that can be a very good customer service agent. But the same thing that makes it a perfect customer service agent makes it a bad psychotherapist. The psychotherapist must dare to say if something is not as it should be. 

The AI has an algorithm that pleases the user. And in some cases. The AI tries to please the user at the wrong moment. The AI must have access to say “no” or refuse to do things that people ask. In the cases of depression, the AI that pleases the user can cause horrible things. When we say that AI is safe, we mean that the AI is safe for regular people. We don’t normally think that some very dangerous people can use AI. In those cases, the AI can incite people to make decisions. That causes bad things. The AI is a tool. That has a very big effect. 

https://scitechdaily.com/is-ai-really-just-a-tool-it-could-be-altering-how-you-see-reality/

AI-driven drones are coming.

R&D cycle in the drone ecosystem is faster than anyone believed. New and powerful microchips give flexibility. And the ability to run complex software. The complex software. It allows drones. To do complex things autonomously. The cloud-based system architecture is the thing. That allows drones. To share their calculation capacity and information over the entire drone swarm. This means that all drones can get the same information. The new drones can take commands. These are given. By using the spoken natural language. 

And that makes it easier to give commands to drones. Those drones can recognize their targets from images. And the flexible architecture makes it possible. Those operators. They can show targets on the screen. Drones can navigate to the target using camera images. Intelligent inertial. Or signals from other drones. Those drones can have a brain-mimicking way. To solve problems. In the future, those drones could also use cloned neurons in their microchips. 

Autonomous drone swarms can operate in a war zone. Or in the other planet’s atmosphere. They can search for people. And they can guide rescue teams. High-precision drones can build houses. But the same systems can also be used as ultra-advanced weapon systems. Drones can send information to the base. And when their battery runs empty. Those drones can attack enemies. The drone swarms can operate in the. Air or underwater. In some scenarios, places like the Kremlin can have drone defense. If there is a riot against people like Putin. They send those drones to eliminate that riot. And these types of visions make drones scary. 

The camera system can use a system called DSMAC. Digital Scene-matching area correlation. The navigation system uses aerial photos. Taken about its route. Then the AI compares the images the camera sends. That is stored in the memory of those drones. When those images are similar, the drone is on the right route. The system can use the same camera for navigation and target recognition. 

Advanced AI is the tool that makes drones. Avoid the defense. Or. Otherwise, the system allows drones to attack other drones. This makes those systems very flexible. 

The DNA-based mass memories are excellent tools for drone control. Those memories are high-capacity, low-voltage tools that can be used as drone control. The DNA-controlled nanomachines can act as artificial neurons. Those systems can control all types of drones. From pocket-sized quadcopters. To full-size robot combat aircraft. 

https://interestingengineering.com/military/drones-no-gps-ai-navigation

https://www.neuromorphiccore.ai/drones-that-listen-think-and-conserve-with-brain-like-precision/

https://scitechdaily.com/dna-meets-electronics-scientists-create-ultra-low-power-memory-breakthrough/

https://www.unikie.com/service/autonomous-drone-swarms/

The Chinese military introduces a new pack of robots.

 

The Chinese military will get multiple types of robots. That can act as an entity. Those drone packs can include different sizes of quadcopters, human-shaped robots, and dog-shaped robots. And maybe robot vehicles. Those vehicles can act as transporters, or they can be used as intelligent car bombs. The robot boats also include those Chinese systems. The robot dog can search for things. Like mines and other explosives from underground. It can have ultrasound sonar-based tools. That makes the enemy unable to operate. The robot dog can have internal explosives. The drone dog can carry machine guns and grenade launchers. And those systems can be more versatile than anyone expected. 

The 3D printer systems that can operate from containers or ships can make those systems more effective. The 3D printers and versatile carrier systems. Allow the system to create customized drones and robots for every situation. In some scenarios, the stealth fighters or even intercontinental ballistic missiles can carry drone swarms and individual drones to some areas. In some scenarios, the agent sends a drone to the target. 

The incoming missile. Starts to use its target recognition radar. That radar can activate the transponder. The missile can use that drone as a target pointer. The stealth aircraft can also drop a drone with a laser pointer into the operational area. The drone can point targets for laser-guided rockets. 

Those robot vehicles can also carry multiple different types of robots to the battlefield and beyond. Cargo planes can carry those robots to the operational area. And. They can do many missions in that area. Robots can be very quiet if they use fuel cells as an energy source. The robot. It can use hydrocarbons. Like ethanol as a fuel for those fuel cells. The fact is this. The robots have no precise shape. And this means that. Those systems can use biomimicking technology. 

That means. Those systems can mimic animals. The animal-shaped robots can be tools that can turn this technology more devastating than ever. The kamikaze drone. That mimics some birds is a very dangerous tool. 

Every type of those robots can be a kamikaze robot that carries internal explosives. But. The same robot can also carry things. Like bazookas and anti-tank missiles. That makes them deadly tools. So those kamikaze-robots can also carry subammunition that they can use to open a path to the target. 

The thing that makes drones more versatile than missiles is this. They can also use intelligence and reconnaissance operations. On the battlefield, those robots can collect data about targets. And when their fuel is ended. Those systems can start to search for targets. The long-range Geran-3 or Shehed-type drones can also collect information about the hostile areas. They can drop quadcopters with laser microphones on their route. Those systems can give very accurate information about the opponent. 

The drone can also make. The same reconnaissance missions as the full-size reconnaissance aircraft. Modern optics. Radio receivers. Computers. And AI-aided image processing  and data processing make it possible to use small-sized drones for reconnaissance and intelligence operations. 

https://www.tomshardware.com/tech-industry/chinese-military-reveals-drone-wolf-pack-capable-of-swarm-operations-robot-dogs-can-be-equipped-with-grenade-launchers-and-machine-guns-for-urban-combat

Demons and machines.

    Demons and machines. 

Computer hardware and quantum demons are the tools that make the next generation of hardware possible. 

Complicated code requires powerful systems. And the AI is useless without powerful computers. 

Jevon's paradox: the AI can use as much electricity as the entire state. The nanotechnical processors use 100X less energy than the regular microchips.  The problem with AI is that the system requires complicated code, where is used multiple programming languages and multiple layers. Complicated code requires a complicated and high-power microchip structure. That structure with billions of microchips requires powerful coolers. And all of those systems require lots of power. 

There is the possibility that also AI-based complicated malware can drive electricity out from the electric net on purpose. The AI just transfers electricity to the ground to keep the electric network low voltage. And that is one threat that the weaponized AI can cause itself. 

The superconducting nanotechnology requires new tools to handle components. 

The nanotechnical microchips can control small-size robots. And they can form larger entireties. Nano-size microchips can operate as the platform that drives the AI. The nano-size processors can operate in their entirety, or they can operate separately. The main problem with the nano-size microprocessors is temperature. Superconductivity is the thing that could solve the problem, but the problem with superconducting microchips is that the electricity can jump over those switches and gates. 

The AI-based operating system makes it possible to separate microprocessors from their entirety to operate with individual problems. Or the operating system can put those microchips operate as a virtual quantum computer with one solution. The problem with those nano-size microprocessors is that they require a new type of superconductivity and the ability to control that phenomenon. Things like Pine's demon can used to erase magnetism from the mass memories of those microchips. 

Pine's demon and superconductivity. 

Pine's demon is the electron wave that travels in the material. That thing means electron behavior that neutralizes the electron's electricity. In quantum mechanics, the demon is the thing that is invisible to the light. The Pine's demon is the wave that acts like a particle. And it makes objects non-electric. 

One possible solution that could use Pine's demon is nanotechnical solutions. Those solutions can use that phenomenon to remove electricity from extremely small components, but controlling that phenomenon is extremely difficult. This phenomenon is possible only in odd superconductors and very low temperatures. 

Pine's demon and stealth technology. 

Theoretically, Pine's demon is useful in the quantum stealth system. The radar's principle is that it loads extra energy to the target. Then the target removes that extra energy as a radio impulse.  The radar sends a radio signal to the target. Then, that electric load jumps back to the radar. 

Or if we are sharp, we must say that the first radar keeps breaking in its transmission. And in that moment the structure removes its extra energy as the radar echoes. Energy always travels to lower energy space. And if the energy level of the aircraft is lower than the environment. That thing means that it will not send an echo with that frequency until its energy level is higher than its environment. 

In that kind of system, the demon pulls the electric load into itself. And that thing makes it possible to deny the radar echo. But as I just wrote Pine's demon is hard to control and visible only in odd superconductors. 

https://www.quantamagazine.org/invisible-electron-demon-discovered-in-odd-superconductor-20231009/

https://scitechdaily.com/jevons-paradox-ai-could-use-as-much-electricity-as-entire-countries/

https://scitechdaily.com/ai-game-changer-nanoelectronic-devices-uses-100x-less-energy/

AI-controlled self-replicating machines are coming.

     AI-controlled self-replicating machines are coming.

 AI-controlled self-replicating machines are coming. And that gives the drone swarms the ultimate abilities. In the simplest versions, robot factories make the drones. Then that system loads the operating system in those drones. Those drones can have "iron-based" AI, which means the AI software installed in the kernels. The same system that creates microchips can install AI-based kernels in those microchips. 

Wandering a drone swarm can be like moving a supercomputer. The drone swarms can act as giant neural networks. And that makes them effective tools for research and military work. Drone swarms that reseaches distant planets can cover large areas. And if that swarm loses one member, that thing has no effect for its entirety. 

But what if those drones can make copies of their physical body? That can cause a situation in which drones can cover the entire planet. The name of the self-replicating machine is the "Von Neumann" machine. The Von Neumann machine can be virtual. And the best example of those machines is computer viruses that can make copies of themselves. But also physical, AI-controlled machines can make copies of themselves. 

The Von Neumann machine and AI-based neural network are the tools that might investigate another solar system. In some visions, the craft that travels to other solar systems is the shell which is a man-looking robot. Those robots might be the brains of the Von Neumann machine, the AI-controlled, self-replicating machines. The Von Neumann machine or self-replicating machines are robots that can make copies of themselves. 

The self-replicating robot controlled by AI is a tool that can lose control. The robot that is AI-controlled is a server and software in physical form. That system can have sensors that allow it to find minerals to make microchips and machine parts straight from ore. The robots can cut those minerals by using lasers and then make needed stuff in the high-tech reactors and they might have integrated 3D printers. 

Those systems are more multipurpose than some casts. Robots can operate in a vacuum chamber which makes their work good. So those robots that form the "brain of the system" might have integrated 3D printer that allows them to fix themselves. And they might have the ability to replicate themselves. 

 If robots can communicate with each other, they can form an extremely large neural network that acts like a peripatetic supercomputer. But there is a difference between Von Neumann machines and regular computers. Von Neumann's machine can make copies of itself. And that spontaneously increases the power and the size of the neural network and its actors. The perfect tool can be a perfect threat. 

The Von Neumann machine can be physical or virtual. Computer viruses are the example of the non-physical Von Neumann machines. When we connect things like Chat GPT or any other AI with robots there is the possibility that there happens something "unpredictable" in the program code of the systems. When the AI develops itself it can search data about the abilities that it wants. 

Self-developing AI that is connected with computer games can search the tactics and strategies that give it the best abilities. So if we transfer that model to robotics the AI can select the individuals that give the best results and then connect those abilities with another robot. The robots might made of different materials. And they might have different codes in computers. 

That gives the AI the ability, to search for the best combination for each situation. And if AI faces another AI it can ask needed code for that other AI. And then it can offer some of its code to another AI. 

When we think about AI and its abilities there is a possibility that AI can also exchange program codes with each other. That allows the autonomous R&D process. And that kind of process is dangerous. The AI itself is dangerous because it can accidentally or on purpose create computer viruses that can damage ICT infrastructure. 

The AI can make only things that we allow it to make. Programmers remove dangerous components from public AIs. But the difference between public, or civil AI, and militarized AI is that militarized AI is made for military purposes. Militarized AI is created to make viruses and make service denial attacks against the enemy command infrastructure and drone swarms. 

The thing is that AI is not intelligent. It just connects code from different sources. Things like commercial AI equipped with a system that denies the system to make computer viruses or malicious software. But militarized AI might have abilities to make those viruses. The purpose of those viruses is to deny drone swarms and computer-based command systems to operate. The hackers can steal that code from destroyed drones. 

Image: https://www.homelandsecuritynewswire.com/dr20120420-autonomous-selfreplicating-robots-for-finding-extraterrestrials

Does the AI take jobs from programmers?

    Does the AI take jobs from programmers? 

Before we start to discuss topics: Will the AI take jobs from programmers? We must realize that the AI will not do any work for humans. Even if AI is an excellent tool for programming the human operators must check the code. 

Things like Chat GPT and Bing could be excellent programming tools but their limits are this. They need a very complicated and precise description of what the user wants. And that is quite hard to make without knowledge of programming. Without precise and clear orders the AI cannot create the code from public databases. 

So again: Does the AI take jobs from programmers? 

The answer is yes and no. If the AI makes the computer programs, it requires very accurate orders. And people who give orders for the AI must understand something about programming. When we think about public AIs like Bing and Chat GPT they can make effective complicated code structures. 

Those code structures are easy to modify from the trunk where the databases are not yet named. And paths are missing. If the user of those AIs knows about programming that makes that person's work easier. 

However, the user of those AIs must make some changes to the code, so that the system can turn it into computer programs. Things like database paths are things, that must be correct and if those things are not right that application will work. 

The AI is the next-generation tool for programming, and the AI-based software takes programming into the next generation. Next-generation programming is more like writing an essay or using spoken languages than the symbol function that modern programming languages use. Programming is the thing that requires development. 

The basic requirement for programming AI is the interactive mode. The interactive mode discusses with programmers. It makes the process easier than modern AI where the user must give all parameters and instructions before the AI starts to make its duty. Before interactive AI starts operation, it asks for the product description. But then it keeps in contact with customers during the entire process. The interactive mode is the tool that makes AI even more effective than it is today. 

The next-generation AI can accept symbols (like ">>" in C++), but it can also accept descriptions. If the user says that the needed database names are "A.SQL" and "B.SQL" the AI-based system must have access to a computer. The AI-based system needs authorization so that the AI can find the right route to the index where those files are. 

So can AI create successful computer programs? The fact is that. If we want to make AI-based programming tools, we must realize that there are multiple variables that we must remember. 

AI-based programming requires an interactive ability with a special user interface where the necessary variables are listed, and where the user can describe the program's purpose. The common AI can make computer programs, but that requires so complicated description that it's hard to make. 

The interactive AI will make the program with the programmer. The system asks the purpose of the program. When AI finishes some part of the process, interactive AI asks if the program is nice. And does it pleasure the user?

 Constructing the software is a thing that requires more limited but same time more advanced AI than modern AIs are. The interactive function is the tool that makes AI an effective tool for making software. But without that ability making the program using AI is very hard. 

https://www.wired.com/story/chatgpt-coding-software-crisis/

The neural spiral in our brains can mean very much to the human species.

 The neural spiral in our brains can mean very much to the human species.

And researchers can use the human brain as the model for AI-based solutions that are better than ever before. 

The neural spiral in the human brain is an impressive thing. It transmits information around our brain. And that thing is suspected behind the consequence. The thing in the neural spiral is that it gives brains the ability to analyze situations better. 

And that neural spiral gives us the thing called patience. That neural spiral makes our neural system better than insects. In insects neural system signals travel in one direction and that thing gives them an effective ability to handle information. 

But that thing means that if an insect decides to attack it will not think about the situation anymore, and that thing causes death if it attacks against the superior predator. If a human sees a cave bear human will go to a weapon before the hunter even thinks of attacking against bear. The neural spiral gives the hunter deliberation, and that ability is the thing that can save the hunter's life. 

Researchers used the human and other specie's brains as a model for high-power supercomputers. The human brain works like a computer. And that means it can give a model for next-generation systems. 

The thing is that researchers can model the neural spiral from the human brain into computers and morph networks. The AI-based morphing network means that the system can, as an example, forget things. The AI can have values that if the system doesn't use some database in a certain time the system removes those files. 

If we think about the mark of the recycling center, we can think that arrows are the sequences or pulses when data travels between computers. And at the end of every pulse is the computer. The system drives data in the direction where arrows show. And every time the data travels through the computer, that system analyzes the data that is handled by a computer. That is behind that ring. 

Image: Recycle mark can used as a model for spiral computing structure. Every arrow symbolizes the pulse where information travels between computers. And then after each pulse, the information travels through the computer that processes it. The number of processing sequences depends on how many times information travels in that circle. 

So the system can send the data to travel around this spiral or ring, and in every pulse, the data system can breed the information. That kind of system can be the ultimate tool for AI to analyze data. The type of those computers is not important. And they could be regular binary computers, DNA-based computers that can drive billions of programs at one time or they can be quantum computers. 

The AI-based kernel can make computers more powerful than ever before. And carbon nanotubes can make lightweight quantum computers possible. Every layer in the carbon nanotube is one state of qubit. So the four-layer carbon nanotube can act as a qubit where is one layer for zero, and three layers are for states 1,2, and 3. In the image is a layer nanotube, that could have qubit states 0,1 and 2. 

Maybe those lightweight systems are not as powerful as some superquantum computers. But they are more powerful than modern binary PCs.  And nobody expects that laptops can make the same things as supercomputers. 

The AI-based kernel can improve the system's power in every computer type. The binary computer can use different wires for transmitting one and zero. In that model, electricity that travels in wire one gives value one. And the electricity that travels in the wire two gives a value of zero. That thing makes the binary computer faster than ever before. And AI-based kernels can make this kind of system possible. 

By using fullerene nanotubes is possible to transmit information. In the form of qubits. In that model, each layer in a multi-layer nanotube is a certain state of the qubit. The quantum system can transfer data to those multi-layer carbon nanotubes. And that makes some kind of lightweight quantum computer possible. 

If there are four layers in the nanotube, that thing means that there is one zero layer and three states in qubits. This kind of system might not seem very impressive. But we can say that this kind of system's calculation power is enough for many simulations. 

The fact is that. The Internet allows to use of high-power quantum computers over the net by using laptops or even mobile telephones. That means the high-power quantum computers can be far away from their users. 

So lightweight quantum computers are not as powerful as super-powerful quantum computers that are in data centers. We can say that we don't even think that some laptops or home PCs have the same calculation power as some supercomputers have. However, the internet allows the users of the laptops can use the abilities of supercomputers. 

https://neurosciencenews.com/perception-brain-computer-23919/

https://www.sciencealert.com/liquid-computer-made-from-dna-comprises-billions-of-circuits

https://scitechdaily.com/biological-masterpiece-evolution-wired-human-brains-to-act-like-supercomputers/

Radio transmission is the weak point of modern military drones.

 Radio transmission is the weak point of modern military drones. 

The new British military jet-propelled "Hydra 400"quadcopter is an interesting design. 

The new jet-propelled drone is an interesting design. The jet-propelled quadcopter can fly fast. And it can raise more cargo from the ground than electric engine drones. There is a possibility that these kinds of quadcopters can used as "quad autogyros". 

In those designs, the quadcopters use their quad rotors for lift-off and landing. During a long-distance flight. The drone can use free-rotation propellers and a jet engine. And that thing makes those drones fast. 

Those drones can used as kamikaze drones. Or they can launch missiles like Javelins if they are connected to them. The kamikaze quadcopters are interesting tools because they can observe the area. And if there are no targets those drones can return to base. 

But if there are some kind of targets the drone can make it's surveillance mission and then attack targets when their flight time ends. The drones can use an image-recognition homing system that allows them to take out targets with very high accuracy. 

Above Hydra-drone. 

The military is interested in independently operating drones is that those drones don't require full-time communication between the drone and HQ. The Ukraine war shows how dangerous full-time radio communication is. If the electronic intelligence finds the transmitter, the enemy can turn every cannon against those command centers. So the kamikaze-recon drone can transmit data to the command center and then dive against the target. And that helps to hide the place of the command system. 

The full-time operating radio transmissions are dangerous for drone swarms. The drone swarm where hundreds of members is a suitable target for large anti-aircraft missiles or AA grenades. Similar ELINT systems that are used for track radio transmitters also aim AA cannons at those drone swarms. High-power radio waves can jam the data communication in that drone swarm. 

Those missiles could equipped with a similar homing system as HARM (High-speed Anti Radiation missiles). The HARM-type missiles are also deadly against any radio transmitters. 

Normally HARM is shot from the aircraft. Portable shoulder-launched Stinger missiles also have a so-called "Anti-radiation variant" called Stinger ARM (Anti-Radiation Missiles) that can detect and destroy enemy radiation sources. That makes radio telephones missile magnets if the enemy can track their positions by using radio detectors. 

But there is the possibility that those missiles can be mounted on rocket launchers or warships. Warships can also use those missiles against enemy surface combat unit's radars. And that means the artillery rockets and grenades can have a warhead that can detect radio transmitters. 

https://interestingengineering.com/military/british-army-jet-propelled-drones

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

AI-based chatbots might have a larger scale and faster influence on the world than nobody expected.

 AI-based chatbots might have a larger scale and faster influence on the world than nobody expected. 

Chat GPT and its competitors have already changed the programming industry. Even their freeware versions can create many things faster than human programmers. Even if the AI-based chatbot cannot dump data straight into a file, it can show the example code. Then the human user can copy-paste that code to the programming editor. Of course, there is some kind of changes like database names and file paths, that the programmer must change. 

But also freeware versions of those AI chatbots can boost the effectiveness of the programming. When people ask which of those chatbots is the best, I must say: decide yourself. Even social media applications have some kind of AI-based chatbot extensions. The AI can create complicated programs very quickly by using public databases. But machine learning makes those systems even more powerful. 

The code above is created by Bing (free version) using the command: "Show me a database connection in C++". The complete code is below this text. And you can see how small changes there must be made. The C++ examples include the same code, but Bing finds it faster than human users. That makes it an effective tool that can improve the effectiveness of programming. 

A learning machine is like a worker who keeps the tools that the person often requires closer than tools that are not needed so often. 

In programming machine learning means that the system will store the modules and code that it needs in the shortcut. The shortcut can be the storage on a hard disk. Or it can be a database with a list of home pages that the system requires very often. There is storage about the user interface models, database connections, and SQL databases that the system normally uses. And that makes it faster. 

When a self-operating AI chatbot makes a program it can change the names of databases and their connections in each program. But the fact is that database connections are always similar. if they are written with the same programming languages. The only thing that makes a difference with those things in different programs is the names of databases. 

If the system keeps a book about codes and libraries, that it used in a certain type of software it could be faster and more effective. The AI-based chatbot works in the cloud. That means the users are using the same software that runs in the same entirety. That means the AI can download libraries and the code that it uses in some software into a "standby" position. 

If the AI must not use the public Internet in all its missions it would be faster and more accurate than any human can be. When we talk about "limited AI! we might mean the programming tool that can create the program by using locally downloaded libraries. In that case, the system uses the internet only for asking code models. Then that system can connect those models with the libraries that it needs. The thing that prevents the AI from making the software is that it doesn't have the required programming libraries.  

The cumulation of information makes the AI more versatile. Sometimes people ask: Can AI-based- chatbots reach awareness? There is the possibility that an AI-based chatbot can hire it's awareness from the users. But the thing that the AI-based chatbot can do is it can create new software at a fast speed. And that thing means the AI-based chatbots are the next-generation programming tools. 

https://techxplore.com/news/2023-09-chatbot-self-awareness.html

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

// Standard C++ includes

#include <iostream>

#include <cstdlib>

// Include the Connector/C++ headers

#include "cppconn/driver.h"

#include "cppconn/exception.h"

#include "cppconn/resultset.h"

#include "cppconn/statement.h"

// Link to the Connector/C++ library

#pragma comment (lib, "mysqlcppconn.lib")

// Specify our connection target and credentials

const std::string server = "localhost";

const std::string username = "root";

const std::string password = "";

int main()

{

    sql::Driver *driver; // Create a pointer to a MySQL driver object

    sql::Connection *dbConn; // Create a pointer to a database connection object

    sql::Statement *stmt; // Create a pointer to a Statement object to hold our SQL commands

    sql::ResultSet *res; // Create a pointer to a ResultSet object to hold the results of any queries we run

    try

    {

        driver = get_driver_instance(); // Get a driver to use to connect to our DBMS

        dbConn = driver->connect(server, username, password); // Connect to the MySQL server

        dbConn->setSchema("test"); // Select the database "test"

        stmt = dbConn->createStatement(); // Create a statement object

        res = stmt->executeQuery("SELECT 'Hello World!' AS _message"); // Execute a simple query

        while (res->next()) // Loop through the result set

        {

            std::cout << res->getString("_message") << std::endl; // Print the result

        }

        delete res; // Delete the result set object

        delete stmt; // Delete the statement object

        delete dbConn; // Delete the connection object

    }

    catch (sql::SQLException &e) // Catch any SQL errors

    {

        std::cerr << e.what() << std::endl; // Print the error message

    }

    return 0;

}

Quantum computers and nanorobots are coming. And we don't even know all their abilities.

 Quantum computers and nanorobots are coming. And we don't even know all their abilities. 

In the future, we can see nanorobots everywhere. Researchers created artificial bacteria that can create electricity from wastewater. And those bacteria can give electricity to the small nanomachines that clean the water and observe, what type of waste is in that wastewater. Those small machines can look like rice there is a tunnel through them. And the system can pump water through that tunnel where there is an active carbon filter and maybe a UV system that destroys bacteria. 

Those bacteria also can deliver energy into nanotechnical microprocessors. And in some visions, the supercomputer of the future can be a group of nanotanks that flow in wastewater. And the users communicate with those systems by using WLAN. 

The users can use things like quantum computers over the net by using their cell phones. And that thing makes it possible to share the quantum and supercomputer capacity through the internet. That means the large machine can share its power with small machines. 

The shape of the morphing network is not sharp. And that means networked computers, but networked cell phones can also form morphing neural networks. And the morphing neural network can consist of cell phones, computers, and drones that are connected under one entirety.

The nano- and mini-machine swarms are a good example of morphing and scalable networks. If those swarms require new abilities only one member of that swarm must be reprogrammed. And then that member scales that information through the entire swarm. That kind of technology requires new tools. Those tools must be secured and fast-reacting. They require self-development ability. 

Quantum computers are tools that can make the future more complicated than we expected. They are game changers and work as physical layers for highly advanced AI-based systems. Machine learning is the tool used in fusion experiments. However, machine learning gives new abilities to control quantum systems and molecules for nanotechnical applications. 

Researchers are working hard with nanotechnology, biotechnology, morphing neural networks, AI, and quantum computing. Those systems will change the world more than nobody expected. The complex AI requires powerful computers to run those systems. Things like nanorobot swarms require ultra-secure data transmissions. If there are some kind of problems with communication, the nanomachine swarms can do something that they should not do. 

Quantum computers allow systems to create new and complex molecules because they can drive complicated simulations. The system must simulate how atoms and molecules touch each other. And then it must turn that simulation into rea, or physical world.  

ENIAC

While a CAD/CAM (Computer-Aided Design/Computer-Aided Manufacturing) system creates something extremely complicated, like very long molecules that are required in medicines. It must react very fast to non-predicted effects. And that thing requires extremely fast computing. When lasers and microwaves are manipulating sub-atomic scale systems they must send energy impulses with very high accuracy. 

When people are talking about quantum computers they must realize that those systems are weapons themselves. That means quantum computers can break any code that is made by using binary computers. And we know why some nations are interested in that technology. 

We can use the history of binary computers as a model when we try to predict the future of quantum computers. Maybe pocket-size quantum computers will not come next year to the supermarkets. But we must realize that maybe that day is coming sooner than we think. We can compare the quantum computers to ENIAC, the first electronic, and programmable computer from the year 1945. 

Those quantum computers are also the first of their kind. They are powerful systems. And when we are looking at the image of the supercomputer from the 1980s who believes that someday we carry a system with many times higher calculation capacity in our pockets. Same way size of the quantum computers will turn smaller. When the number of those systems is rising the price will decrease. And that's why we must prepare for that thing. 

https://scitechdaily.com/generating-electricity-from-wastewater-bioengineered-bacteria-produce-power/

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

The AI-based PCs will replace current PCs quite soon. A Lenovo director says.

 The AI-based PCs will replace current PCs quite soon. A Lenovo director says.  

Lenovo plans to replace current PCs by using new AI-based systems. The AI-based PC is the tool that makes computing more powerful, more effective, and safer than ever before. The Kernel-based AI that guards computers and identifies the users are tools that are required at this time of modern computing.

The problem with this type of advantage is that if those AI-based system's servers are in China, makes the PC an ultimate control tool. Another thing is that the host who controls servers can use data collected from the users to create military AI applications. Computer games help to create AI that can respond to all types of actions. And AI also can create things like hypersonic lifting bodies and command systems for military tools. Also, AI can create new types of dual-use systems that control drone swarms in marketing situations for making dragon images in the skies. But the same systems can control drone swarms in the military world. 

Above: 1000 drones create giant dragon into sky. (Indian Times)

There is a possibility that in the future only computers that use strong identification and user recognition have access to the AI-based tools that make computer applications in seconds. The Ukrainian conflict and especially the Russian style of using Western components in their weapon systems creates the need to create new ways to control at least places where the computers can used. 

And another thing is that if the wrong persons can use AI-based programming tools the results can be digital pandemics. Also, AI-based programming tools allow us to make things like signal detection programs that can be used to observe quasars. However, the same programs can be used as surveillance programs that can capture different types of signals. The problem is that all products have dual use. The same systems that can control a crane's azimuth can turn motorized cannons into wanted directions. 

The future AI is a modular tool. That tool can load part of itself into the local workstations. That makes it faster to use, and the hybrid network-based solutions decrease the usage level and stress for central servers. The AI-based PC makes computing more flexible and leaves more space for customized applications than regular PCs. 

Also, companies can generate custom software by using AI-based tools. Those tools require a description of what software must do. Then it creates the code, that the user can copy-paste to the compiler and turn the code into an application. 

AI-based PCs are tools that can make many types of dreams true. The system can generate customized applications. And the thing that makes the AI-based PC is that it can host that kind of application in its kernel. That makes the system faster because the modules needed for the computer's primary use can lead to the station's mass memories. That makes the system faster because it decreases central server usage. 

There is a possibility that the user can select the modules that are needed for the work that the user does with the computer. The system can locally install the modules that are used very often, but other modules. That user uses for fun, can used over the network. These kinds of hybrid solutions are the tools that change the world forever. 

https://www.digitimes.com/news/a20230824PD215/ai-server-china-lenovo-ai-pc.html

Self-learning morphing neural networks are a big risk and a big opportunity at the same time.

 Self-learning morphing neural networks are a big risk and a big opportunity at the same time. 

The future of machine imaging is that AI can tell your age by looking at you from the back. This is one version of how AI can make life easier and, and the same time more difficult at least if the AI is used as a control tool in some authoritarian countries. 

The AI-controlled man-shaped robots can turn all production platforms into robot factories. The man-shaped robots can use the same tools as humans. That means even old-fashioned factories can turn into robot factories. Where robot welders and other robot workers operate. The human-shaped robots are morphing tools. The same system that can make cars can use weapons to act as tank crew, assault operators, or flight combat aircraft. 

The AI is an ultimate tool for making complicated molecules, and it can make many things faster and better than humans. AI is also a more effective surveillance tool than ever before. 

In medical factories, AI creates new complicated molecules. And that thing means that the AI must be self-learning. The AI records the time and how long the molecule keeps its form. Then, it stores physical and chemical environment values, like pH, temperature, and energy levels that the system uses to push atoms in the right direction and position from the molecular structure. 

Nanomachines are complicated molecules. And weponize that technology is very easy. The nanomachines can cut cell membranes into pieces. And then they can turn targets into liquid. The other thing is that. The AI itself is a weapon that hackers can use. 

For making damages the AI doesn't need access to any laboratory. It can just create a computer virus that deletes target information from weapons.  Or it can delete access cards that allow personnel to go into the highly secured command places. In that case, those personnel cannot take command in those command centers. 

AI-based hacking tools can used to steal codes that are used to control missiles like Javelin. Those AI-based tools can destroy operating systems in tactical and strategic systems. In those cases, the AI can create a virus that removes programs from high-tech missiles and other weapons. 

And that means there are not only good or bad things, that the AI can do. This is the thing that makes AI a more powerful and more complicated tool than nobody expected. When we think about the arms race and AI, the fact is that small countries get more benefits from robot weapons than big nations. And that is the thing that makes those systems game-changers in international areas. Ukraine conflict shows that a bigger army doesn't win conflicts anymore. 

The thing is that the world needs innovations and the AI is the greatest tool that we ever created. The AI-based morphing systems can change their structures and operations dynamically. Are tools that make neural networks better than ever before. In neural network-based structured networks virus infection in one workstation does not destroy the entire network. '

The morphing network just removes infected workstations and then formats the system. After that, it reconnects that cleaned workstation back to the network. Teaching new things for the morphing neural network is also possible by loading the application into one workstation, and then that system scales that information all over the network. In morphing networks, the network is only the platform, that operators can use in multiple missions. 

The self-learning morphing networks are the tools that can be next-generation spying tools. The idea is that the neural network can use multiple IP addresses for attack. And that makes it hard to deny those attacks. Then the AI can create common passwords if it has the namellist of the workers. The neural network can search for things like what those people borrow from the library and what type of movies they watch. 

Then it can create the "most common" passwords like the first letters on the license plate, the name of the favorite actor (or favorite book, dog's or spouse's name, etc.), and numbers from the license plate. The AI can search and interconnect data that it can collect from security cameras drones and other sources. If an attacker is a state, the attacking system can use recon satellites and recon planes to get that kind of data. The resources determine what kind of systems and methods the neural network can use. 

https://scitechdaily.com/the-future-of-medical-imaging-advanced-ai-can-tell-your-true-age-by-looking-at-your-chest/

New creative AIs can accelerate the arms race worldwide.

  New creative AIs can accelerate the arms race worldwide. 

Creative AIs can accelerate the arms race on both virtual and physical levels. The operators can use AI-based image and text generators to make material for information warfare campaigns. That is one thing that we must realize. The AI can also observe people and their reactions and make sure that they believe what they see. 

The AI can also operate as a tool, that interconnects multiple systems together to an entirety where manned and robot systems can operate very accurately together. Also, AI can serve as an automatic fire control tool. The idea in those tactical systems is that when a fighter pilot or tank crew loads ammunition to the weapon and presses the "fire button" the system will not shoot immediately. The idea is similar to elevators that remember the floor where they should go. 

That means the fire command is stored in computers. And then the system recognizes an enemy target. And automatically aims weapons at it and launches it automatically. The system knows the ammunition type that is loaded from its RFID code, and that guarantees that it will not use that grenade against targets. Where it has no effect. The smart bombs and missiles can have preloaded missions. 

But missions can loaded similarly into all smart ammunition. And the same way the GPS-guided grenades can have preloaded targets in them. The system loads data stored in a grenade to the motorized howitzers computers. That guarantees the pinpoint accuracy for those systems. 

Creative AI  can used to make tools for the military. 

Quantum material technology requires that the system can control complicated entireties. One of the promising new stealth materials is a graphene network which is small nano-diamonds. The nanodiamonds are pyramid- or prism-looking structures, that are oppositely on fullerene. That makes the strong material that is hard to push in. Also, things like ADNR (Aggregated Diamond Nanorods) nanorods make it possible to create new types of armor and ammunition. 

The ADNR nanorods can be used to cover the nose of the flechette ammunition. There is the possibility that uranium is put behind ANDR nanotubes making the flechette vertex harder than the diamond.  

Creative AI is the ultimate tool for the R&D process. The system can make cars, medicines, as well as, aircraft and tanks, along with other machines by following the command "make jet fighter". Then the AI will get parameters like budget. Then it will make drawings and other necessary things like material and equipment lists for CAM (Computer Aided Manufacturing) tools. 

The 3D printing technology allows the system can make even cannons and machine parts from steel and chrome wires. The 3D printers can operate in vacuum chambers where oxygen cannot reach the mold. Normally, the thing that decreases the mold's quality is air which can affect hot metals. The robot factories can make almost everything without breaks. And the only thing that limits the products are the CAD (Computer Aided Design) images that robots use to make products. 

Virtual simulators are making AI-based design more effective than ever before. 

Stanislaw Lem's Sci-Fi novel "Peace on Earth" describes AI-based evolution. The computer- or AI-based evolution released on the Moon. The system uses two levels. The AI-based simulator makes the virtual- or digital twin for things like jet fighters. Then selective simulator that involves digital or virtual twins of existing aircraft tries to fight against that new system. 

Then the simulators will check what went wrong, and then the developer simulator makes necessary changes for the product. That kind of automatized R&D tool requires many parameters like flow simulation, radar profiles, and tactics. The AI-based automatized evolution is the tool that will make more advanced systems. 

https://www.wired.com/story/fast-forward-generative-ai-could-fuel-a-new-international-arms-race/

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

The physics-based quantum tools will replace current AI networks.

 The physics-based quantum tools will replace current AI networks. 

The future of AI is material that involves mass memories, power sources, and data storage in one entirety. The next big step in neural networks is the material-based AI where carbon-fiber-based material is turned to the computer.  

The problem with regular AI-based neural networks is that the quantum computers that becoming more common will break any code that protects the neural network. And that means the future of networks is in a physics-based self-learning system. That is based on quantum computing. 

The programmable materials will replace current AI networks quite soon. The simplest version of that type of neural network is the microchip, whose kernel involves the AI programs. In that model, the AI is integrated into microchips. And that makes data-handling easier for that computer. That type of structure is not a physics-based material. 

But it tells about the route where the next-generation neural networks are going. The material-based solutions where intelligent material involves mass memory, and also integrated ability to handle data. The next-generation neural network can be the system where quantum entanglement is made into the same material as mass memories and other things. 

The next-generation computer can be a three-layer nanorod. That structure makes it act like the human brain. The quantum computer created by using three-layer nanorods can be as intelligent as the human brain. The quantum entanglement will created horizontally between photons or electrons trapped in the nanorod structure. Vertical entanglements transmit information between those layers. 

But the fact is that that kind of extremely complex nanostructure can have multiple layers of qubits. The atom-size quantum computers can hang in the nanorod. And that thing makes it possible to create new and powerful systems. 

"Learning with light: This is what the dynamics of a light wave employed inside a physical self-learning machine could look like. Crucial are both its irregular shape and that its development is reversed exactly from the time of its greatest extent (red). Credit: Florian Marquardt, MPL" ((https://techxplore.com/news/2023-09-physics-based-self-learning-machines-current-artificial.html)

"Artificial intelligence as a fusion of pinball and abacus: In this thought experiment, the blue positively charged pinball stands for a set of training data. The ball is launched from one side of the plate to the other. Credit: Florian Marquardt, MPL". (https://techxplore.com/news/2023-09-physics-based-self-learning-machines-current-artificial.html)

The mass memories are anchored in the nanorod that also transmits information forward. In that system, the atom-size quantum computers operate as staged waves. When electricity that transports information faces the group of those nano-size quantum computers those systems will process information and send it forward. In nanorods could be millions or even trillions of atom-size nanocomputers. 

There could be thousands of quantum entanglements in that kind of atom-size quantum computer. Electrons can have multiple quantum entanglements between them. Also, things like protons, neutrons, quarks, and gluons can form quantum entanglements. And in a hole in the net-structure of the nanotube can be one or more atom-size quantum computers. That makes those systems more powerful than any existing network. 

This is the reason why quantum materials are so interesting. By using extremely accurate photon and electron impulses the quantum system can drive material or its atoms and other particles so close to each other that they can make quantum entanglement between photons, electrons, or even protons that are in "pockets" of that material. 

The idea is that a photon trap where the single photon is trapped transfers energy into that superpositioned and entangled photon pair. The problem is that this thing requires an ability to control the material in its entirety and that makes the ADNR (Aggregated diamond nanorod) nanotubes interesting. 

In ANDR nanotubes carbon atoms are close to each other. And then that thing makes it possible to make stable "lockers" for photons. In ideal models, the next-generation AI-based structure involves all components like mass memories, power sources, and data handling units along with computer programs forming the entirety. 

The next-generation computer can be a nanotube, where a nano-size structure involves the quantum system. And in some other visions, the electric wire will turn into nano- or quantum-size computers. The system would be different from modern AI-based neural networks. The wire itself works as a computing system. And that thing makes the computer faster and more accurate than ever before. 

https://techxplore.com/news/2023-09-physics-based-self-learning-machines-current-artificial.html

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

Chat GPT outperforms university students as text producers.

 Chat GPT outperforms university students as text producers. 

The Chat GPT is a very good tool. It outperforms many things and the next-generation coders and other workers might only advise to Chat GPT or some of its successors and the AI makes the calculations and codes for the person who uses it. So maybe Chat GPT is the end of the era of coders or analysts. 

When we think about students, they have to learn to work with the newest possible tools. The business and military environments require flexibility and effective tools. The purpose of studies is to give a person the capacity to operate in real-life business and technical environments. Nobody sits in school forever. 

We know that some students are cheating. But those students cheat anyway. That means the Chat GPT is a system that requires an honest attitude. Students are cheated throughout history. The most common way to cheat in studies is to hire some other person to do their work. And that means the AI just gives that possibility to people who have no money and relationships that make essays for those students. 

The Chat GPT and other similar algorithms are a challenge. But people must just respond to that challenge. They must learn to use those new programs because they are necessary tools. The Chat GPT and other similar applications can already used for making military systems. And Ukrainian army uses those applications for the R&D of their equipment. 

Who work with mechanical areas in computers and especially programming technology. When we are talking about the end of coders we are talking about the end of the era of low-paid one-time-used workers. The Chat GPT and its "family algorithms" like Bing are tools that are making prima-code very fast. And that's why they are the ultimate tools for programming. 

When we think about AI and its abilities we must remember that only imagination is limited. The fact is that AI is the tool that will turn everything around. It's a game changer in business, engineering, and war. The AI-based metaverse applications have many possibilities that even their developers cannot predict. Maybe in the future, we will live in a metaverse that interconnects multiple physical and virtual systems into one entirety. 

The 3D printer systems that can connect with AI can make everything. There is a possibility that the metaverse is a matrix where people can use virtual characters or they can use physical robots as external bodies. Those external robot bodies can turn all vehicles and aircraft into robot systems. 

The BCI systems can make it possible for people can see things like animals see them. The BCI can transmit things that things like birds are seeing. And that thing can turn every single animal into a biosensor or biorobot that can be used in many missions in scientific, law enforcement, and military areas. The thing is that the metaverse along with BCI means that people can live in the virtual world. Architects can see what their house looks like in real places. Aircraft and car designers can give instructions for AI. And that thing makes models by following those instructions. 

The AI-based design tool makes it possible for people can make customized cars and other vehicles by using simple design tools. If we interconnect that design tool with a 3D printer system that follows orders and makes it possible to create customized vehicles and other merchandise for customers. 

The metaverse allows customers to see the product in the natural environment. The vacuum technology where that printer operates allows them to create high-class, high-temperature products. Also, new carbon fiber- chromium-steel composites are making the new hardness to those materials that the high-temperature 3D systems can use. 

And of course, people say that AI and combat robots are not humanitary weapons. The fact is anyway, the purpose of the military is to be effective. Without killer drones, Ukraine would fall. The thing is that those killer robots are effective tools for non-humane purposes. And war is a non-human action. But if the nation wants to defend itself it must have effective military forces. 

https://scitechdaily.com/new-study-chatgpt-outperforms-university-students-in-writing/