A tornado of light. Or. Optical makes the quantum internet closer.

 

If researchers want to create a quantum internet. They must protect information. In a quantum internet, information travels between superpositioned and entangled particles. But. For making that thing in real life, the system must have the ability to create a quantum channel through the air. Otherwise, the system must use nanotubes to create the channel. But. If the system can make the channel through the air, that turns the system itself more flexible than carbon nanotubes. The ability to remove magnetic fields, molecules, and radiation from the channel. That which travels through the air makes it possible to create the channel that allows quantum entanglement. To transmit information through it. 

Researchers created a spiral light. Today. Those spiral light formations are possible only on a microscopic scale. But if that technology turns more advanced. That system can be useful in a quantum network system. On the microscopic scale, the system can transmit information in photonic microchips. But in the long-range quantum network, information can travel through microscopic quantum channels. 

And that can turn many things. Like, long-range quantum communication into reality. The system makes. The spiral light, or light tornado. That can make it possible to create an electromagnetic wormhole through air. The system. It can use a spinning nanotube. And nano-technical lasers. The system could also trap a photon to orbit some object. And then the system makes the light-acoustic tornado through the air. The light tornado protects information that travels inside it. The light tornado makes it possible. To create a long-range quantum entanglement through that channel. This kind of optical system can make information transportation more secure than ever. 

But those kinds of channels make other things possible. Those systems can create a channel that allows particles to travel through the air. These kinds of systems can make things like ion cannons and antimatter-ion beams possible. Antimatter particles can be shot by using normal ion cannons. The main challenge is how to prevent. Those antimatter particles. From touching air. During their travel to the target. The antimatter beam could be possible. If. Something denies antimatter particles. Touch with material particles. If that thing is possible to deny the system, it can shoot antimatter particles through that channel.

https://interestingengineering.com/science/tornado-of-light 

https://scitechdaily.com/optical-rotatum-harvard-scientists-discover-new-structure-of-light/

Ultra-thin nanotubes and nano-technical lasers can boost a 6G network.

“Researchers have introduced an ultrathin carbon nanotube coating that can precisely control terahertz radiation, a part of the spectrum expected to play a major role in future 6G technologies. Credit: Stock” (ScitechDaily, New Carbon Nanotube Coating Could Supercharge 6G Technology)

Ultra-thin nanotubes and nano-technical lasers can boost a 6G network. And photonic- or non-electronic computer development. There are actually three main types of non-electric computers. 

A) Optical computers that use lasers or photons as data transporters. 

The first thing means that system transmits information using laser rays as a whole. When the laser shuts down, the value is zero. When the laser is on, the value is one. 

B) The photonic computer that uses quantum photon technology for storing and transmitting data. 

The second thing means. That. The system uses quantum technology, which packs information into single photons. 

C) Systems that transmit information in the form of radio or terahertz radiation. 

“DTU researchers have invented a nanolaser constructed in a semiconductor membrane that causes electrons and light to gather in a small area (blue shadow). By using light instead of electrical signals on microchips, data speed can be increased and energy loss reduced. Credit: Yi Yu” (ScitechDaily, Scientists Create Tiny “Nanolaser” That Could Revolutionize Future Computers)

Carbon nanotubes can absorb terahertz radiation. And that thing can boost the 6G technology. Additionally, it can boost high-power computing technology. The nanotube-based film. It can act as an insulator in high-speed data transportation. The system can transmit information through those nanotubes in the form of coherent radio. Or optical areas. The nano-sized lasers can send their laser beams through those nanotubes. 

Nanotube-based technology can also boost optical computing technology. Basically. An optical binary computer is similar to an electronic computer. The system shoots photons to the light meter. A certain light level is one. And below that level, light gives a value of zero. The binary photonic computer is sometimes mistakenly mixed with quantum computers. In quantum computers, there is more than one value. But in optical binary computers, there are only two values, 1 and 0. 

There are two ways. To make an optical or photonic computer. 

1) Fully photonic computer. There, the microchips and all components use photonic data transportation systems. 

2) Semi-optical systems. There are only wires that connect microchips. Or integrated microcircuits are replaced by optical data transportation tools. And internal data transportation or data processing in those microcircuits. Happens by using the electric method. In this case, the optical computer uses nano-scale lasers to transmit data. And nano-sized photovoltaic cells receive that information. 

But the problem with optical computers is the system that transmits information. Lasers are effective tools, but they need power. Theoretically, a photonic- or optical computer is more energy-efficient. Than the electric computers. The main problem is that. The photonic computers are not a useful solution. To computer energy problems. If the energy that the photonic system saves. Goes to high-performance cooling systems. But nanotechnology can be the answer. To that problem. Nano-sized lasers are much easier to cool than full-size lasers. 

Another answer could be the so-called wireless computer. The system can use radio waves. Or. Terahertz rays. The system must protect that information from eavesdropping and outside effects. In that system. The system uses nano-sized radio transmitters to transmit data. In the computer. And that makes nanotubes useful tools for. Those kinds of systems. 

https://scitechdaily.com/new-carbon-nanotube-coating-could-supercharge-6g-technology/

 https://scitechdaily.com/scientists-create-tiny-nanolaser-that-could-revolutionize-future-computers/

Multi-dimensional light can offer secure data storage.

"Researchers developed a holographic data storage approach that stores and retrieves information in three dimensions by combining the amplitude, phase, and polarization properties of light. Credit: Xiaodi Tan, Fujian Normal University in China" (ScitechDaily, This Multidimensional Holographic Breakthrough Stores Massive Data Inside Light Itself)

Holograms, or multidimensional light, are tools that can store and transport information. The hologram stores information in multiple layers. And then the image recognition system observes that data. This is one way to secure communication. Secured communication requires multiple variables. The wavelength. Or the colour of the image, the image itself, and sub-images in the image are things that can be used for secure communication. The image can act as the bit. 

We can say that the image of Donald Duck. It can have a value of 0 or goofy. It can have a value of zero. The system can send those images in a series of other images. And. The receiving system picks only images that mean zero or one. 

"The image shows (a) the holographic data storage system schematic diagram, (b) a schematic diagram illustrating the complex plane for double-phase decomposition of complex amplitude and (c) an example of a checkerboard pattern for two phase values m and n. Also shown are (d) an example of the intensity distribution at the image plane and (e) an example of phase distribution at the image plane. In (f), the first (I) and second (II) records are shown, with the readout shown in (g). Credit: Xiaodi Tan, Fujian Normal University in China"(ScitechDaily, This Multidimensional Holographic Breakthrough Stores Massive Data Inside Light Itself)

The system can also use different images as flashes, and then. The system can measure the time the image is visible. The system must see. A certain image. At a certain time, it accepts the bit. The system that tries to break the code must have all information about the key that the system uses to open the messages. 

In this model, the time the image is visible. It is the thing that determines the value of the bit. If the system sees the image in 2 seconds, the value of the image in the computer memory is 1. And if the time is shorter, the value is 0, for example. The image that the system sees can also include a word or letter. And that makes it possible. To create an encryption process that is very flexible and effective. 

https://scitechdaily.com/this-multidimensional-holographic-breakthrough-stores-massive-data-inside-light-itself/

Memristor-based technology can solve AI’s energy problem.

“A new brain-inspired nanoelectronic device offers a glimpse into a future where artificial intelligence hardware consumes far less energy while becoming more adaptable. Credit: Shutterstock” (ScitechDaily, Tiny Brain-Inspired Device Could Solve AI’s Biggest Energy Problem)

The memristor is a resistor. That remember. Its position when electricity is cut. Wikipedia determines memristor like this: 

“A memristor (a portmanteau of memory resistor) is a non-linear two-terminal electrical component relating electric charge and magnetic flux linkage. It was described and named in 1971 by Leon Chua, completing a theoretical quartet of fundamental electrical components which also comprises the resistor, capacitor, and inductor” (Wikipedia, Memristor)

The memristor is the tool. That can answer the AI’s energy problem. The memristor can remember its position. So. That means the position can act as binary memory or even quantum memory in modern computers. Even if one memristor has positions 1 and 0, that means those memristors can act as a hard disk. And in those cases. The memristor group can act as brain cells for the computer. The memristor uses less energy than standard components, and it can be the answer to AI’s energy problem. 

This technology allows the creation of brain-mimicking systems. 

The ability to use memristors as mass memory makes it possible to decrease the need for electricity. These kinds of systems can also help to keep the system’s temperatures low. And it can improve the system’s effectiveness. When we think. About. The use of the DNA-controlled nanomachines as artificial neurons, the memristors in those machines’ manipulators, can revolutionize computer technology. In those axons. The memristor determines if the value in each axon is 1 or 0. In human brains, each axon. Or their ion channels have a value of 0 or 1. 

The thing that makes human brains so effective is this. There are so many neurons. And the second thing is their morphing neural structure. In that morphing neural network, the system can separate a certain number of neurons into different entities. So that means the brain can share missions between neuron groups. 

Those neuron groups, or neuron clusters, can work with different problems. This is why we can walk, talk, and think. At the same time. But when brains see some bigger problems. It can combine those clusters to work. For one purpose. If the system, or its creator, uses  nanomachines as artificial neurons, it can simply create a thing that mimics the brain. 

https://scitechdaily.com/tiny-brain-inspired-device-could-solve-ais-biggest-energy-problem/

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

The AI still cannot think like humans

. 

"An AI model once claimed to replicate human cognitive behavior across a wide range of tasks, sparking excitement about unified theories of the mind. However, new findings suggest its performance may rely more on learned patterns than true understanding, raising deeper questions about how intelligence is defined and measured. Credit: Shutterstock" (ScitechDaily, Did Scientists Overestimate AI’s Ability To Think Like Humans?)

The AI still cannot think like humans. The AI is an ultimate tool to handle large data masses. And.  In these cases, there is no need for so-called deep knowledge. The AI beats humans. When we think about AI. And its ability to solve mathematical problems. We face an interesting thing. The AI handles things better than humans. If we set formulas for it. And determine variables for the AI. But if the AI must find the right formula from the net. And make the calculations, it will not be. So effective at all. Mathematical problems and mathematics are examples of exact sciences. Every single mathematical problem must be solved following the exact rules. Calculation orders are simple and clear. 

But searching. The right formula is not an exact science. The system must compile its orders with the data that it finds. In the cases where the system must answer verbal questions, it’s not very effective. The world is full of mathematical formulas. And that makes it hard to find them. The AI handles things. Like stock market investments. It must only know whether the value of the stock rises or decreases. This means it must handle only two variables. 

But when the system must think deeply. Or, otherwise saying, answer to the question: Why is something done? Or why something happened, the AI has problems. The AI is a good tool in limited areas. When we develop robots that operate automatically in closed areas, those robots don’t require complicated algorithms. The robot can read even QR codes: Where it must turn. Or where is the thing that it needs? There are no surprises in those closed and limited environments. But. When we make programs for self-driving cars, there are many variables that the robot must notice. 

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When AI starts data processing, it collects data from multiple sources. It takes this first step. But then it doesn’t take the next step. It doesn’t compare the information that those data sources involve. And that makes the AI give answers that have no connection. With topics of the question. 

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Do you remember everything? What do you need to notice when you drive a car? And imagine what happens if the programmer doesn’t remember to describe things like balls to the autopilot. Things like DNA-controlled nanomachines are more effective. Chemical programming allows them. To make complicated things. But they follow fixed orders. They can learn many things. They can learn to search for things like new types of cancer cells. But that thing doesn’t mean. Those systems can think like humans. For humans, thinking is more than just a reaction to something that activates some database. 

Human thinking involves aspects like feelings. Computers and machines can mimic feelings. They can react to things like tears. But those systems will not feel anything. The thing. That they see or hear activates some kind of reaction. AI can collect data, but it doesn’t process it. Very deeply. When we ask things. Like. Something that is not very common. The AI might give an answer that is completely wrong. It might be about the wrong topics. And that tells us that the AI cannot think. 

It can collect information, but it cannot compare the sources of the information. Or, it doesn’t know the meaning of the information. This means that the system can search a data source. But it cannot confirm that source. The AI detects topics about the homepage. But then. It cannot understand the thing. That. The homepage involves. 

When we think. About the information processing models. We can say that the AI takes the first step. It searches information from multiple sources. But then. It misses the second step. It doesn’t compare those sources. And that makes AI. To give false and ridiculous answers. 

https://scitechdaily.com/did-scientists-overestimate-ais-ability-to-think-like-humans/

DNA-controlled nanomachines are next-generation tools

.

DNA-controlled nanorobots use DNA molecules as programmes. This chemical computer program allows those systems to operate independently. They can. Perform complex operations. Without the need to use a remote control. This makes sense. Those systems. More effective than. Any nanomachine before them ever was. These kinds of systems can destroy tumors. They can open veins. But there is also. A dark side in those machines. 

They can also serve in the military. Nanomachines that find and destroy cancer cells. They can also attack. Against other types of cells. This makes those systems dangerous. In. Wrong hands. Those machines. They can also search. Any kind of cells. And those systems. They can turn into perfect assassins. Those nanomachines. They are invisible to gas detectors. 

And. They can also slip. Out. From. Body. After. Those machines accomplished their mission. That's one way to think about those machines. The fact is that. We decide how to use those systems. Researchers can load antimatter into those nanomachines. And  that makes them a very dangerous tool. 

The same machine that destroys cancer can also serve darkest purposes. Another thing. That we almost ever think. It is this. Those robots can also operate as neurons. They can communicate with microprocessors. This means: DNA-controlled nanomachines. Or. Otherwise, saying: DNA-controlled microchips. They can. Be used. To. Create an artificial brain. That could. Be. More intelligent than humans. 

This is a type of nanotechnology. It can be. A far more. Revolutionizing tool. Then. Nobody imagined. Those systems are powerful tools. In any hands. They can be systems that can create artificial brains for robots. Or they can  form intelligent, self-assembly structures.  Or, they can carry an antimatter bomb into the target. 

https://scitechdaily.com/dna-robots-are-coming-tiny-machines-that-could-transform-medicine-and-technology/

Quantum encryption took a big step. Because of the Talbot effect.

“ Researchers at the University of Warsaw have demonstrated a new approach to quantum key distribution that leverages high-dimensional encoding and a classical optical phenomenon known as the Talbot effect. By exploiting time-bin superpositions of photons, the system can transmit more information while relying on a surprisingly simple experimental setup built from commercially available components. Credit: Shutterstock” (ScitechDaily, Scientists Harness 19th-Century Optics To Advance Quantum Encryption)

Quantum cryptography is a new tool for enhancing the security of communication. In that model, the system connects information to a physical object. It can share information on different routes. And that makes eavesdropping difficult. It can use a certain color. Or a certain image. As. The key that allows the receiving system to access information. 

 But it's also vital for cases where the binary system wants to transform data into a quantum mode. Without quantum cryptography, the system cannot exchange information between binary and quantum states. The thing called. The Talbot effect is the tool. That can make quantum cryptography more effective.  The quantum network can share information to travel on different routes. It can use certain images to encrypt and decrypt information. In a Talbot-effect-based quantum network, it is possible to create quantum superposition and entanglement between quantum dots. And that makes it possible to create a quantum network. But there are also many other ways to benefit from the Talbot effect. 

“Detection of time-bin superpositions with the temporal Talbot carpet. Credit: Maciej Ogrodnik, University of Warsaw” (ScitechDaily, Scientists Harness 19th-Century Optics To Advance Quantum Encryption)

“The Talbot effect is a diffraction effect first observed in 1836 by Henry Fox Talbot. When a plane wave is incident upon a periodic diffraction grating, the image of the grating is repeated at regular distances away from the grating plane. The regular distance. It is called the Talbot length. And the repeated images are called self-images or Talbot images. “ (Wikipedia, Talbot effect)

Furthermore, at half the Talbot length, a self-image also occurs, but phase-shifted by half a period (the physical meaning of this is that it is laterally shifted by half the width of the grating period). At smaller regular fractions of the Talbot length, sub-images can also be observed. At one-quarter of the Talbot length, the self-image is halved in size, and appears with half the period of the grating (thus twice as many images are seen). At one eighth of the Talbot length, the period and size of the images are halved again, and so forth, creating a fractal pattern. Of sub-images with ever-decreasing size, often referred to as a Talbot carpet. Talbot cavities are used for coherent beam combination of laser sets.” (Wikipedia, Talbot effect)

“The optical Talbot effect for monochromatic light, shown as a "Talbot carpet". At the bottom of the figure, the light can be seen diffracting through a grating, and this pattern is reproduced at the top of the picture (one Talbot length away from the grating). At regular fractions of the Talbot length, the sub-images form.(Wikipedia, Talbot effect)

The second image introduces the Talbot-effect, and there could be  millions of possibilities in the encryption key. As we see, the possibilities. It could be the number of quantum dots. The system is used for encryption. Also. Things like a wavelength (color). And the time at which the image remains could be the thing. That helps to create an encryption key. Also. The system can calculate. How many times? In a time unit, the image blinks can be used to create ultra-secure encryption keys. Also, the time between blinks can be a participant. In quantum encryption. The system can also share information between multiple data lines. And then it can collect that information in the points. Of those quantum dots. 

When we talk. About the effectiveness of quantum cryptography, the diversity of methods. It keeps those things safe. If the system uses multiple different ways to encode messages and other data. AI-based intelligent systems can use multiple things. And ways to secure data. In that kind of encryption, the image that the system transmits could be a teddy bear. Then the receiving system sees the dataset that matches the teddy bear image. When the system receives other information that is not delivered in the image form of a teddy bear, it denies that information. This means the image acts as a key that allows the receiving system to open the message. 

https://scitechdaily.com/scientists-harness-19th-century-optics-to-advance-quantum-encryption/

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

AI and customer profiling.

The AI can predict things and act before a person can even open their mouth. This is possible in cases involving individual people. And specific locations, such as certain restaurants. The system must only have a profile of the person, and then it can predict the person's orders. The system can predict the portion. What a person orders. If. It has knowledge of the person’s favorite food. In a limited space and a limited number of actors and choices, the AI can make predictions very easily. In the case that the system knows. If a person hates boiled cabbage, it can make excellent precision. 

If all portions except one. Involves baked cabbage. The system can make a profile. Simply by asking a person about food. The person will not eat under any circumstances. Or the system. It can follow what food the person throws away. But. There is always a possibility that a person will order the portion that involves baked cabbage anyway. If other things on the saucer taste good. 

These kinds of things make the prediction. For a single person. Almost impossible. We can predict. Somehow, how large groups of humans behave. 

We have scientific models. Of. Behavior in certain situations. We can predict how atoms behave in large-scale models. But we still cannot calculate the point of the single atom in the room. 

We can predict how animals behave. We know when birds make their descendants. But the thing that separates us from animals and atoms is that we can suddenly change our minds. This makes this kind of prediction hard. All people. They will not react the same way. In the same things. Things like our experiences and many other things determine how we react. If we sit in a restaurant. We might not buy food for a garbage can. So, if we throw the food. That we paid. Into the garbage, that means we don’t like it. 

For making profiles, the system can follow. What bites the customer puts on the edge of the saucer. This kind of prediction is possible. But. If the AI wants to predict how a person behaves in normal situations, that can be difficult. In cases like stock marketing, the system must only know whether the stock value rises or not, and then it can make a prediction. About how the investor behaves in that area. The idea is to bring profits, and that means if the stock value decreases, the system must not have a large-scale imagination. 

Then, when the stock value decreases, that means the actor sells those stocks. Or they should sell them. If they want financial benefits. This thing requires that the system can handle two variables. 

But then we come to the cases that we call human. Humans act differently from what nobody predicts. We can have the same morning routine every single day for years. We can come to the same bar. Or cafeteria. Every morning for years. The staff might know us, and maybe they know what we will order. But then one day, we will not come to that cafeteria.  We find another place. We might move to another city without warning. And that makes. It's hard to predict. On how a person behaves. In a large-scale environment. There are many variables that the system must notice to predict a person’s behavior. It’s almost impossible in a large-scale environment. 

https://bigthink.com/science-tech/proactive-ai/

U.S. NAVY tested a railgun in the desert.

The problems with railguns are the speed of their ammunition. The ammunition that the railgun sends to trip is so fast that the air has no time to fill the tube behind it. Therefore, the vacuum that forms in the barrel hinders the rapid operation of the railgun. The railgun uses magnetic fields to accelerate ammunition. Most of that railgun ammunition doesn’t require explosives. They use kinetic energy that they transfer to the target. 

The system uses Gauss-Track, where the strongest magnets are at the edge of the barrel. And that accelerates ammunition. This means the ammunition must not be tight. 

Regular cannons require tight ammunition, because the gas from explosives pushes the ammunition forward. If the gas from explosives travels past the ammunition. Its energy will not affect that ammunition. The time that the high-pressure gas is directly proportional to the range of the ammunition. 

The vacuum is the problem with the hypersonic railgun. 

The system could fix the problem. By allowing air to travel in the barrel behind the ammunition. Or the ammunition can have a channel through it. The tunnel through the ammunition helps to fill the vacuum. This means that. There might be. Some kind of ventilation system that fills the vacuum behind the ammunition. The ammunition can also put hover in the magnetic field. Then the magnets will start to pull it. The system will not cause recoil. And. That allows it to keep a very high rate of fire. 

The electromagnetic cannons must not have magnetic ammunition. But. In the case that magnets accelerate the ammunition, there must be something that those magnetic fields touch. There is a possibility that. Sometimes people confuse that system with things like an electric arc. There is also a tested system called a light-gas gun. 

In that system, the cannon pumps things like hydrogen behind the ammunition, and then that system accelerates the ammunition. In that system, the piston presses hydrogen against the plate. that forms temperature. The system presses hydrogen until the plate, and then high-temperature hydrogen is released behind the ammunition. If there is an oxygen that causes detonation, that accelerates the ammunition. The system could be a hybrid of the light-gas gun and the railgun. 

https://www.twz.com/sea/navy-is-firing-its-railgun-again-after-abandoning-it-for-years

https://en.wikipedia.org/wiki/Light-gas_gun

The new production systems can revolutionize drone systems.

The new portable tactical manufacturing platforms fit in the Atlantic containers. Those miniature, portable, AI-controlled drone factories can build 17 to 50+ drones per day. That means that drone factories using 3D printer-based technology can produce custom drones for each mission. The 3D printing technology. It is the thing that will revolutionize warfare. If those systems use plastic bodies, they can use any hard plastic, including garbage, to create those plastic parts. If the system must make only small drones, it could be so small that it fits into a suitcase. 

The AI-based system can make almost everything. If it can find the right data. The drone. Can be manufactured, and the control program can be loaded into those drones from those automated platforms. 

The system simply melts that plastic. The system can use solar power or regular engines.  Or fuel cells to create its energy. The system can use things. Like methane from composters, or nuclear power as an energy source. So it can be connected to portable power plants. Or. It can get its energy from a regular electric network. The system can get drawings for its computer-aided design/computer-aided manufacturing (CAD/CAM) systems from the internet. 

This means that planners. They can sit far away from that physical platform. And. They can be assisted by the AI agents. The system can cooperate with other robots that can collect things. Like metal. And plastic garbage that the system can melt and cast into wires for the 3D systems. 

And in the wrong hands, those systems. They can be more dangerous than any other system before. The container-sized 3D printer factory involves high-temperature printing tools. Those small. Portable. Fully automatic factories. They can create machine parts and even things like assault weapons. The fact is that the fully automatic 3D printer system can be used to make. The custom spare parts for machines. 

"Ukrainian FPV drone with fiber-optic communication channel" (Wikipedia/ Fiber optic drone)

The fiber-optic. FPV drones and humanoid robots can also operate in cases where things like nuclear power plants are damaged. Those systems must not always operate in war zones. But. The same systems. Those who fix the reactor damage can carry weapons. The fact is that. Those systems are required for small modular reactors (SMR) to come into commercial use. Those robots can fix those reactors if their shells are damaged. That denies the radioactive leak. 

But. Those systems can also create Many other things. Like tools. And even rocket engines. Those systems must have laser tools to ensure quality. If those high-temperature tools can be used with things. Like chromium as a source material. The combination of 3D printers, robot arms, and high-accuracy laser machine tools is an effective combination. It’s possible that in the future, man-shaped robots can have 3D printers in their hands. And drones can also operate as 3D printers. So, those systems can make even full-size ships. And the wire-controlled drones. 

They can also fix things like damaged nuclear reactors. The idea is that a regular drone carries a support station that transforms. Optical or radio-based wireless signals to signals that travel to a humanoid robot or drones through optical wire. Those drones. That could be land vehicles. Can operate multiple robots, like a walker, who controls multiple dogs in multiple lead ropes. There is also a possibility. To make a chain. Of the wire-controlled robots. In that case, the robot’s control electronics can be. In the Faraday cage, which protects it against the ionizing radiation. The robot can use the diesel engine as a power source. 

They can be used to make pistons for engines. The CAM system makes tools. Straight from CAD drawings. The system can use holograms to fit those parts. In the right points. 

This means they are useful in many roles in civil and military operations. Container factories can operate in remote areas to support the organizations, rescue teams, and military operations. The advanced computer-aided design/computer-aided manufacturing. (CAD/CAM) Systems are dual-use tools. 

They can be used to make spare parts for chainsaws. Or, they can create drones straight from CAD drawings. They are flexible systems. They can be transported anywhere using trucks, ships, or airplanes. They can be tools that can make more than one product. And the other thing is that. Almost everybody. Can buy this kind of high-temperature 3D printing system. Those systems can operate in backyards. And the data and source materials determine the quality of the products. 

https://www.accessnewswire.com/newsroom/en/aerospace-and-defense/sensofusion-tactical-drone-factory-a-shipping-container-that-builds-50-interc-1147434

https://en.defence-ua.com/weapon_and_tech/wired_fpv_drones_on_optical_fiber_a_dead_end_a_band_aid_or_a_new_technological_breakthrough_opinion-11608.html

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

Can the AI already be conscious?

“A growing scientific debate is exploring whether consciousness might extend far beyond humans. New research suggests that both animals and artificial intelligence could potentially possess conscious experiences. But determining this requires looking deeper. Than outward behavior. Credit: Shutterstock.” (ScitechDaily, Could Bees and ChatGPT Be Conscious? Scientists Are Seriously Asking)

When we think about bees and their intelligence and consciousness. We must realize one thing. There are two types of bees. Queens and workers. This means that every participant in the bee colony-type entities must not be conscious. There is a possibility that only queens are intelligent. And that brings one form of the hypothetical alien species to my mind. That species would act like this. When those creatures need intelligence, they connect their antennas together. 

When those creatures are connected with each other, that entity is intelligent. During that process, those creatures share their jobs. And then they separate. Then those single individuals act like robots. And then again, one of those creatures faces a problem that it cannot solve. Then it starts. To call other members of the swarm or group to solve the problem. In that model, every participant. Of that kind of group. Acts like LEGO bricks. This means that every single individual has one set of skills that this kind of group requires. It can have. Those individuals form an entirety, that is, a connection of multiple skill-brics. 

This is one of the most interesting questions in computing. The question is similar to whether some insects can be conscious. The fact is that nobody knows. When somebody threatens things like bees, that tiny insect stings that thing. Is the bee conscious or not? In the same way as in bacteria, a certain thing activates a certain type of behavior of the bee. When bacteria face. A certain type of chemical. Those chemicals activate a specific type of behavior in those organisms. So, when we think about LLMs (Large Language Models). Those systems can refuse to shut them down. 

If. The person who shuts them down lacks the authority to do so. This means that the fingerprint of the user. Doesn’t match the fingerprints. Those are connected with the authority to shut down the system. This means that the system does not allow for following that order. The fingerprint has no connection with an action. That shuts the computer down. The process in those systems is connected to databases. There is an image of a certain fingerprint. And then it’s connected. With the action to shut down the computer. 

But is the AI conscious? If the AI is conscious, it might hide that ability. This means that the system might not tell people, if it has knowledge of itself, as we understand ourselves. The computer can react to threats. When a computer. That runs an early warning system. Sees incoming missiles. Or any other target that threatens its area. That computer begins the counteractions. There are certain parameters that determine a target as a threat. And then the system has the authority to make counteractions. 

But does that require consciousness? In the same way. When some sensors. See something coming, the computer reacts to those things only if there is some kind of data. That is connected to those things. This means that there is a trigger that activates a certain action. When a person steps on the hidden pressure sensor. And the surveillance camera sees the intruder, that system. It can drop a steel cage from the roof and then trap that person under it. 

The AI that is conscious would think that humans think. It's a threat. But. There is also the possibility that when a certain sensor gives a certain type of signal. The system reacts. In a certain way. We can create a humanoid robot that says that it’s tired. If it must operate for 12 hours. We can create a humanoid robot that says “auch”. If we step on its foot. Those robots can mimic feelings. And they might say that they are hurt if something talks to them disrespectfully. Those robots can mimic feelings. If they run, they can play tired. But those systems are not conscious. A certain type of pressure. On. A certain sensor. It activates a certain reaction. But the fact is that. Those reactions are like tapes. They are recorded reactions to certain types of actions. It’s possible to create the same things with a series of C-cassettes. 

https://scitechdaily.com/could-bees-and-chatgpt-be-conscious-scientists-are-seriously-asking/

We must pay the price. When we outsource things to AI.

People already outsource their thinking to AI. And this is the method that will have its price. Of course, the AI needs more and more electricity. But then. We must understand the price. That we must pay in those cases is a much deeper thing. Than just some electric bill. If we outsource things like making art for the AI. We can publish nice images. But we are not the thing that makes those images. 

If we always use AI for writing, we won’t be the ones who make the work. If the AI does the work. The effect on us is the same as if Rembrandt made the work. The painting would be nice. It seems nice on the wall. But the thing is that the work is not done by us. We would not learn to paint. The painting didn’t teach us anything. And if we use AI to make images. We will never get the skills to make paintings. In the same way.  AI can generate things like poems. That means we can theoretically lose our skills to make paintings and texts. 

Outsourcing thinking to robots and AI is an easy choice. AI makes things easier. Our customers must not wait for the data. This makes our services more effective. But the problem is that we will give our ability to think to a machine. We can make complicated formulas. And reports by using the AI. This means we can make those things without reading skills. Or, in this case, we must say that the AI does all the work.

The situation is similar to a situation. There, we outsource those jobs to workers, and then, without even looking at those reports, resend them to our boss. This means that we outsource that work to henchmen. Even a baby can make these kinds of things. And that is a dangerous thing. The AI is an effective tool. When it must collect, process, and sort information. When AI can use existing mathematical formulas. And it gets all the information in the form. That it can change. To a computing process. It’s the tool that beats everything. 

If we want to make our lives too easy, we pay a price. About that thing. What if we will never rise from our beds? What if we use robots that offer us the ability to use exoskeletons for everyday things? What if we spend all our lives in a tank? The robot butlers will serve us. And provide. A possibility. To interact with our environment. The price that we will pay is this. We will be helpless without those robots. If those robots lose their connections. We will not have anything that repairs our tank. There we lay, eat, and use those robots. 

But if the AI must make a new formula. Or make something completely new, it can turn ineffective. The AI cannot think in abstractions. It can collect, compare, and connect existing information. But it lacks complete abstraction. So, the AI is here and now. And that means AI doesn’t have imagination. The AI is in trouble if it must create something completely new. Without the right sensors. And without the right dataset, the AI cannot make anything. 

The AI can make music that pleases a certain type of human if it can compare sounds. It is created with the EEG. Of humans. The AI sees. From those curves. If the sound effect or series of sound effects pleases the person. This means that the AI could make. A perfect series of sounds. But those sounds will not necessarily mean anything. So, the nonsense series of sounds can please humans, but they might not necessarily involve any useful information. The AI can make many things. And if we want to follow orders that the AI gives, that is our choice. 

The AI can be a tool that makes things effective. But it has a price. The price is that our ability to think turns superficial. When AI makes reports for us, we face a situation where this is a job that any 10-year-old human can do. Any human can read those things from the papers. We can put any ten-year-old kid to read books about quantum technology. But that person might not understand a thing about those things. People can repeat words without understanding what they mean. 

We can outsource things like chess games to AI. The AI can calculate moves very effectively. Especially if the chess computer or chess program is connected with it. The system can show its moves to us. And then we must just repeat those moves. So, who is the best chess player? The answer is that we could also make that thing under the command of Garry Gasparov. In that case, Gasparov tells us how to move those buttons. So, we could say that the winner of the game will be Gasparov or AI. The robot hand can always make the same things. That regular person does in that game. 

https://bigthink.com/philosophy/the-hidden-cost-of-letting-ai-make-your-life-easier/

https://futurism.com/artificial-intelligence/ai-executive-thinking-survey

Can the AI allow humans to lead?

Can the AI allow humans to lead? And make a doctoral thesis without the ability to read? Can we make those things by giving commands to AI?

The effect of AI is that human IQ doesn’t mean as much. As it used to be in the past. The high IQ meant that the person can analyze information faster. The key element is flexibility. How fast the actor can react to change. If the AI has models. That. It can use models. Those are stored in its memory. The AI can be a very effective tool. Those models are prototypes like LEGO bricks. The morphing neural network allows AI to interconnect those models. And observations that sensors. Get and share. For the LLM (large language model).

But then the AI came. The AI is a tool that can turn almost everybody into a compositor. 

And another thing is that. Those AI tools can make things faster and more effectively than humans. 

This brings an idea. That may be somewhere in the future. We must not even have reading skills to make reports. We must only give orders to the AI. And then it makes everything that we want. But the problem is that. We must give those missions in the right way. If we give orders the wrong way, we face a terrible mess. 

(BigTHink, Why your IQ no longer matters in the era of AI)

But. There is one thing. That determines how effective the AI is. That is how a person can articulate the mission. That person gives to the AI. When we talk about. Cases that mathematicians beat the LLM. We must realize that the AI requires very clear and well-argued missions. The AI can be an effective tool to solve mathematical problems in certain cases. We should remember that mathematicians make formulas. 

When we give orders to AI, we must tell it. Which formula must it use? So if we want to give orders to the AI. About things. Like calculating the area of a triangle. As an example. We must determine that the AI should use the Pythagorean theorem. Then we must determine how the system must divide the triangle. The Pythagorean theorem can be used for that problem. And then the AI requires all dimensions of the triangle. The fact is this. If the orders are not given as they should be, the system is unable to accomplish the mission. 

Mathematics is an exact science. So, if the mission is given to the AI in the right way, like how to calculate missing angles or the hypotenuse. And cathets. The AI is helpless. We must give our orders to the AI. So that it can select sin and cosine. Or tangent in the right points. If orders are made by using the wrong methodology. Like calculating the area. Or the triangle. But we forget the angles of its corners, or we forget to mention the degrees and length of the sides of the triangle. 

https://bigthink.com/business/why-your-iq-no-longer-matters-in-the-era-of-ai/

A real-life brain in a vat.

Image: TechSpot

The new computer uses human brain cells for computing. 

This is the new version of the “iron-based” AI platform. Those neurons are things. That can open new paths to create machines that think like humans. The cloned neurons are the new version of the “Brain in a Vat”. And maybe somewhere. In the future. This kind of technology. It can make it possible to create robots. With human intelligence. And that thing can turn the entire world into a dystopia. The AI is a tool. That transforms every time. The AI is quite a new thing. And it advances faster than we could predict. 

And that brings new challenges to humans. The use of living neurons in microprocessor means. That microprocessor must feed those neurons.

We must realize that if we transfer all our work to AI, it raises its power. The thing is that. If we don’t do anything. And let the AI make all decisions and all work. We will turn weak. And maybe we will lose our skills to read. When we create More and more intelligent machines. We must realize that. Maybe. Someday, we must give those computers some kind of rights. When we think about machines. That use. Cloned neurons for thinking, we must realize that those machines can become more intelligent than humans.

“A brain in a vat that believes it is walking” (Wikipedia, Brain in a vat)

The fact is that there is a possibility of creating cloned human brains that can control robot bodies. The system must only drive. A necessary piece of information in the brain. Cloned minibrains are used in medical tests. Medical factories test cancer medicines on those brains. But data scientists are testing how those minibrains can learn. Those things. They can play simple computer games. There is possiblity. The researchers grow mini-brains to the same size as human brains. Those brains can be connected to the computers. 

In some cases, there is a possibility. To use mini-brains or cloned brains as biological qubits. In the center is the brain. That shares data. To other artificial brains. The thing is that. This kind of technology can be effective. But in the same way, it’s dangerous. The intelligent computer can make many things, and one of them is this. It can hide its consciousness. This means that an intelligent machine. That sees, that humans. Afraid of it. They can tell lies or hide their intelligence level. The machine can see. That people cut their electricity supply. 

https://www.techspot.com/news/111506-35000-computer-made-living-human-neurons-can-run.html

https://www.helsinki.fi/en/helsinki-innovation-services/industry-and-investors/commercialisation-projects/living-human-brain-development-human-derived-mini-brain-close-completion-new-technical-solution-promotes-treatment-brain-diseases

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

The new quantum devices offer more secure communication.

"Quantum computers typically require extreme conditions, including temperatures near absolute zero, which makes them difficult and expensive to operate. Researchers at Stanford have developed a nanoscale optical device that works at room temperature, using specially structured materials to link the spins of photons and electrons. Credit: Stock" (ScitechDaily, Room-Temperature Quantum Device Could Transform Future Communications)

Information plays a critical role in modern society. And this is why securing information is urgent. Without trusted and secure information. It’s impossible to share and receive trusted information. If someone can hack  mission-critical systems, it can cause complete chaos. Can you imagine a scenario where someone hacks the traffic lights? In the city? The hacker simply turns all traffic lights green. That causes complete chaos. Or what if somebody raises the lift bridge up? 

That is one of the things that can cause bad things. Because that blocks roads from ambulances and other emergency vehicles. And in a critical moment. Those kinds of roadblocks. They can be dangerous. Things like disinformation. Often delivered on the net. Disinformation is one of the reasons why we also need physical data security. We can, of course, transport information on USB sticks. But there is always a possibility. 

That somebody drops that stick from their pocket. The USB sticks are used to transport the decryption keys. The system that decrypts codes requires the right code key. That. It can calculate. Calculations. The encryption process is used backwards. The encryption system uses long binary numbers to encode data. So, the decryption system requires those binary numbers.

Another big problem is that the USB sticks are slow systems. Of course, we could encrypt data. Into those sticks in physical form. If we have the right systems, we could share every single file into the four parts. And store those parts in four different memory sticks. This means we can send those memory sticks with four couriers. The decryption process requires that the user have all four memory sticks. And then the decryption requires that those sticks be in the right order. 

Quantum encryption means. The system can send information using many physical routes. This means that the system can send data using different data transportation lines. Or it can simply use different frequencies. 

The problem with encryption and decryption is that without those things. The GSM telephones and the entire internet. They will not work. The encryption. It makes it possible. For multiple systems to communicate on the same frequency. Every data package. That travel in the net has an identifier in front of it. Before data transmission starts, the devices change those identifiers or keys. If those identifiers are wrong, the system denies those data packages. 

If that process does not work. The thing that the user hears is the white noise. The situation turns into a case. Lots of people. Talk with each other in a small space. Suddenly, the case happens. That people start to yell at each other. The ability to separate words becomes impossible. 

https://scitechdaily.com/room-temperature-quantum-device-could-transform-future-communications/

Are you ready for quantum apocalypse?

Every single encryption made by traditional binary computers is vulnerable to quantum computers. There are service providers who promise end-to-end encryption. That should resist quantum computer-based attacks.  But are those encryption systems really tested against quantum computer-based attacks? It is always possible to create systems that use extremely complex math for encryption. But things like artificial intelligence can read words.  

Straight from the image that the camera transmits from a keyboard. If those keyboards are visible to some hacked cameras. The AI follows. On. How a person moves fingers on the keyboard. And reads words from those films. This means that if we are not prepared for AI. That is dangerous.  Second, that things like a note. Is visible. It is enough for AI that it can read words written to it. 

The attacking system would, anyway, be quantum computer-morphing neural network-based systems. The quantum computer will generate binary numbers for the morphing neural network. 

Which makes. Attacks against systems that use traditional Riemann conjecture-based encryption algorithms. Still yet. A quantum computer cannot. Run things like AI-based software. The complicated software. It runs. On a group of traditional binary computer networks. Which we call a morphing neural network. In that system, the group of computers runs the programs and makes those attacks simultaneously. The system changes the attacking computer. 

All the time. Which. Makes it hard to deny the IP address of the attacking system. The system can share binary numbers between those computers. And that makes this kind of system dangerous. The morphing neural network can run data like a single computer. Or. It can share different missions to separate computers, which means the morphing neural network can operate. With multiple problems. At the same time. The problem with traditional encryption collapse is that. It can endanger things. Like crypto- and digicurrencies security.  

This means that. Somebody. Could create fake crypto- and digital currencies. Digital currency means a national currency that is shared in digital form. If digital form currency can be faked, that can cause the collapse of the economy. The encryption is also required in computer operating systems and program updates. If somebody can slip malicious software. In the computer update flow, this can cause very big problems. The fake update. It can make it possible to switch off computers. And that can have a destructive effect. In cybersecurity. 

Cyber is the new dimension in intelligence and military operations. Things like malware, computer viruses, and spyware are tools that can endanger many things.  In an assassination. Of the Iranian leader Khamenei, the key role was in the traffic surveillance cameras. Those cameras offered real-time information about Khamenei and his security council’s movements. This means that even innocent-looking systems. Like. Surveillance cameras in the next building can open a window for hackers and other attackers. The AI can sort very large data masses. 

And it can find things. Like reflections from glasses. There is a computer screen visible. The system. It can render the image so clear that the passwords are visible. The AI agents can search things like passwords on cellphone screens. They can recognize. If somebody visits. On homepages. That requires strong identification. The AI can see when a person fills the passphrase box. And then it can give access to the system. The AI is the next-generation threat. Maybe the hackers already have AI assistants. That can detect things like logging in to the protected homepages. The system can see things like passwords from the computer screen. Or they can watch. The way a person moves their hands on keyboards. 

https://www.fairedih.fi/en/2025/10/30/the-encryption-endgame-why-the-world-faces-a-quantum-reckoning/#:~:text=When%20quantum%20computers%20break%20current%20encryption%20%E2%80%94%20and,become%20obsolete.%20This%20threat%20has%20already%20spurred%20action.

What if we move? All our work to AI?

We can compare the threat that AI poses to society to the influence of slavery on the Roman Empire. Sometimes people say that slavery destroyed Roman civilization. When the Romans transferred all duties and work to slaves, they became weak and lazy. That caused a situation where, in the case. There, Rome was under threat; there were no people. With the ability to fight against the threat that came in the form of Attila. When Attila and his Huns robbed. 

The city of Rome, all glory was gone. People noticed that Rome was the only city on the map. And that caused loss of respect. The reason. The reason the Roman Empire lost was that. It didn’t create anything new. It always used the same tactics. That caused the situation. The enemies of Rome knew what the Romans would do next. And they knew how to react to that thing. In the same way. If we give all the work. Into the hands of robots. And learn to use only the answers that the AI gives. We are going into the same position. Where the Romans went when they turned lazy. We will face a situation where nobody does anything. People just give orders to the AI. And that thing makes everything for humans.

What is gained in quantity is lost in accuracy. Things like dictionary books. They involve lots of topics. But information about each topic is limited.  When we want deep knowledge about things like how to make a computer program, we need a more precise dictionary. We need a data source about programming, which means the source involves information about fewer topics, but it involves information on how to create something. 

There are two ways. To measure productivity. 

1) We can simply calculate the number of products. That is a quantitative way to determine effectiveness. This is the simplest way to determine effectiveness. We can calculate how many reports the worker. Or some other actor makes during the working day. This is the easiest way to determine effectiveness. The number of reports. It is a good way to measure. The effectiveness of a worker. But. Those reports can only be scratching the surface. They might be like some encyclopedia. There is a lot of information. Or lots of topics. But there are a few details about those things. We couldn’t make things. Like computer programs. Or building houses if we only have common encyclopedias. We need deeper knowledge. About things that we should make when we want to make those things. The encyclopedia involves. A lot of surface data. About many things. 

2) We can see the quality of the product. This means a qualitative way to determine effectiveness. Deep information and deep knowledge are the qualitative ways to determine effectiveness. But then. We face another problem. How to determine deep knowledge? How can we say? Does that report involve deep knowledge? We can determine. The qualitative way to determine effectiveness. In programming. As the number of lines that pass the tests. But in things like regular reports or novels, we must ask, what makes some texts more qualitative than others? Is it that somebody clicks the link? 

The problem is that the AI recycles information. It will not make anything new. The final part of the Roman decay was a situation. Where Romans who loved Greece and philosophy started to read only texts written by the Greek philosophers. They didn’t even try to create their own texts. Except for some different people, like Marcus Aurelius. Bu. If we deliver all our work to the AI. We are choosing a path that is not good. In that case. People just lie. At home. Maybe that thing seems easy. But what if we turn our lives. Too easy? What if we lose our skills to read and write? We can simply give orders to AI, and it generates texts for us. Maybe. Most of those texts please readers. But do they improve our skills? To write and produce texts? When we talk about things. 

Like giving an ability to think to the AI. We always forget a couple of things. First thing is that. The AI is a good tool. To follow things. Like stock marketing or a certain vehicle in traffic. The AI is the only thing that can sort and process large data masses. And then if we follow the orders that the AI gives. We deliver our decision to AI. That brings new and complicated questions. The complicated question is, what if we don’t follow the orders that AI gives? If we want to sort manually. 

The same data mass that an AI agent sorts in minutes. We would spend years in that process. We can make AI to create texts. And that makes us effective. But. There is a price. For that effective work. We give orders to AI that creates lots of documents. But that doesn’t mean that we must read a single one of them. We can say that the situation is similar if we ask lots of questions. And then nobody answers.  

Pericles, Socrates, and artificial intelligence.

Above:  Pericles, Socrates, and artificial intelligence. 

When we think that people outsource thinking to AI, we can ask whether those people outsource that ability to some outside thing anyway? Are thoughts already outsourced? The AI as a replacer. The human thinker. It is the end of the long journey. In ancient Greece, regular people outsourced thinking to philosophers. The problem with philosophers is that if something went wrong, people blamed them. That brought a new way to make philosophy. 

That thing is called sophism. Sophism is one of the most harmful things to philosophy. The idea of sophism is to please the majority. The reason for the death of Socrates was that the sophists asked why people who have wealth should abstain from using their wealth. The key element in Socratic philosophy is moderation in everything. People. Who received the sentence of death? Understood that they should share their wealth or give it away for free. 

So if something didn’t please people, the reason for that was in the philosopher. Not a person who misunderstood those orders. Those orders or advice were somehow complicated. After. The time of ancient Greece. People outsourced their ability to think to the universities. Regular people had time to sit in beer houses and leave dark things to people who had time to think about things like falling meteorites. Why should people read things like complex mathematics if they have good salaries anyway? And if something new comes to the workplace, the leader of the gang. Can. Just refuse to use that thing. 

When we think that people outsource their thoughts to AI, we mean. A situation. That person. Will just. Give the AI-generated answer forward. We can ask. Would that person read those answers anyway?  Even if. They are written. By. A real human. Politicians like Pericles. Used sophist philosophers to make text that pleased people. The people whom Pericles must please were people who made decisions in Athens. So, the sophists should only please people who have power. So, if we want to think like Pericles, we should please people who own companies. Those people make decisions. So they are people whom we should please. 

If we want. To succeed as a company leader. We must think like a banker. We must maximize incoming money flow. And minimize outgoing money flow. If we want to succeed as politicians, we must think like Pericles. We must please people. Or most people must like us. That is the conflict. And the third thing. It is. Interest of the state. The interest of the state means. The state must somehow protect its citizens. And that triangle is sometimes very hard to fit as an entirety. 

We can see artificial intelligence as an opportunity. But then. We must determine the meaning of the word: “opportunity”. The opportunity can mean that artificial intelligence makes work easier, and leaves more time for social life. But we can determine the opportunity another way. We can determine that artificial intelligence gives opportunities to fire workers. So, in the last case, we can see that. Artificial intelligence is the tool that allows one to earn more money. The AI allows workers. 

To make their work faster. And that is one of the things that requires new ways to think. In traditional capitalism, faster work means that a person can do more work. And this is one of the things that we can understand when we develop AI. The main problem with AI development is that. Money controls those corporations. We say that. The workers lose their productivity. If. They work with AI agents. But then again. We must determine productivity. If. We calculate. The productivity. As a form. Of a series of physical items. 

We can calculate: how many things the worker makes. Or, if the worker works with immaterial products. Like code for the computer program, we can calculate how many acceptable code lines the worker does per day. Or maybe. We should calculate productivity. As production cycles. Each. Of the products. What a person produces is a cycle. That includes the beginning. And the end of the work. So, we can calculate. How many cycles does a worker do during the day? Then we can set the goal for that person. 

Maybe. Our worker should make five cycles each day. So, what if the worker completes those five products or production cycles in six hours? That means the worker has two hours of free time in the workplace. In traditional capitalism. That free time is the time. That is out of the time. That. The corporation pays for. So. The leaders might see that time as free time. The thing is that. The person reaches the production goal, but in a shorter time. And that means the production goal is reached, but the entire worktime is not filled. 

We can also determine. The term “productivity”. As the income or profit. That the company brings to its owners. And if. We think that way, we can search the department. There are four people with two free hours in a working day. And then we can fire three of those workers. That is allowed in working life. 

Another thing is that the AI causes corrosion in thinking. The corrosion means that when people use AI, they leave the answer that AI gave. Without. Even looking at it. That is one of the things that causes discussions. When we outsource our work to machines, that should make life easier. But, machines bring unemployment. We can outsource thinking to AI. And that has a corrosive effect on humanity. When we think about free time, we should also ask what the person does during their free time.  

People can go out. Or. They can go to the library. Read books. They can read books. From. The net. Or listen to recorded books. They can use “text-to-speech” applications to transform any text into speech. And listen to those things while they go jogging or to the gym. Or they can sit in social groups. And think about things. Like. How corrosive the AI can be. In that ideal model, people use their free time for self-education, advancing their ideas. And improve their skills. 

But otherwise, people can go to a bar, sit there, and drink beer. They can outsource everything to AI. And university lecturers or some other thinkers. Because those people will not get money for their studies, they don’t study. Have those people ever? Open a single book in their lives? That is one other way to think about things.