The Oxford researchers said. They archived teleportation between two quantum computers.

The quantum neural network is similar to regular morphing neural networks. But the difference is that the quantum neural network the qubits or quantum computers make the network. That means the quantum neural network would be the fastest and the most powerful computing system in the universe that we can imagine. Data travels in that network in the form of qubits or quantum entanglements between superpositioned particles. 

That teleportation happened between two quantum systems. That happened without moving qubits. So the researchers shot information in the form of quantum tape. Or wave movement through the quantum channel. That helps to scale quantum computers. 

In old quantum systems, the qubits were unique. Quantum teleportation means that the data travels in quantum channels in the quantum entanglement. The data can travel faster in the quantum channel than outside it. That channel can be like an electromagnetic shadow between two particles. 

And that means quantum entanglement can be extremely fast. And secure data transmission method. The idea is that data travels in the qubit or in the quantum string between two points. And that makes it impossible to eavesdrop on those signals. Quantum computers are tools that will change computing. 

But they have one problem. Their power is so high, that only another quantum computer can check their calculations. The quantum computer can make calculations in hours, which the regular computer requires for the rest of the existence of the universe. The weakness of quantum computers is that. 

They have not been scalable. Scalable quantum computers can check their solutions. The quantum channel is one kind of wormhole. Those channels are the things that are cleaned from molecules and crossing electromagnetic fields. And that thing means that. Light travels faster in quantum channels than it travels outside them. 

The Einstein-Rose bridge or gravitational wormhole is only the most extreme version of the wormhole. Things, like nanotubes and Faraday cages can make electromagnetic wormholes where some side-coming electromagnetic fields are removed. That thing protects the quantum entanglements from outside effects. Quantum entanglement can exist only when another side of the entanglement is at a lower energy level. 

The only known thing that can create the stable entanglement is the low-mass primordial black hole. The idea is that the photon would be in frame and that hypothetical black hole would be behind it. Then the transmitting side starts the data transmission between two photons. The black hole behind the receiving photon pulls energy into it. And keeps the stable entanglement in its form. 

That system requires a black hole. That is not possible to get. But maybe in the future that technology is possible. 

When the system makes the quantum entanglement it traps two photons in opposite frames. Then the system makes them oscillate synchronously. Then the system starts the data transmission. There are problems in putting mode complicated systems like atoms into quantum entanglement. 

The system stresses some electrons that they send the photon. And then it puts photons in the superposition and entanglement. The system can freeze those photons on the atom's quantum field which is one way to make quantum teleportation. 

The thing that could help the existence of the quantum entanglement would be a super cold environment. The idea is that the difference between those photon's energy levels should be as high as possible. 

That maximizes the differences between energy levels in that quantum entanglement. There are two ways to decrease the energy level of the receiving part. The first way is to decrease the energy level before and the second is to decrease the energy level after the quantum entanglement is made. 

In the last one, the system pumps energy out from the receiving part of the particle pair when the quantum system starts to transmit the data. The problem is that the quantum system must control the vibrations and oscillations of those particles. And energy pumping can cause non-controlled vibrations. 

https://www.independent.co.uk/news/science/oxford-teleportation-quantum-computing-supercomputer-b2695851.html

https://www.sciencealert.com/teleportation-achieved-between-quantum-computers-in-a-world-first

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

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

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

The ant-shaped robots are moving large stones.

Robots are multipurpose tools. And even small robots can move large objects if they act as groups. Ant-shaped miniature robots are excellent tools for many purposes. They can take samples from ant nests and search for things like fungus between walls. The miniature robots can make chains and deliver information from cramped places. 

They can observe cables and search for damages from tubes and electric wires. The use of those robots is almost unlimited. They can act in medical operations where they can operate as miniature surgical tools. The jaws of those robots can act as surgeon knives. The miniature robots can carry miniature sensors that can search for many things. The cloud-based calculation systems are tools that can make miniature robots operate independently. 

The non-centralized data architecture makes it possible to turn those robot's computers into one entirety. And that turns those robots into a deep neural network where they share their calculation capacity. 

That gives those systems the ability to drive quite complex algorithms. This gives them very high independence. Maybe one part of those swarms doesn't have very high-power processors. But if they act as an entirety, those systems can be very effective.

Those robot ants can go inside houses and deliver information about the enemy headquarters. In the military world, those small robots can slip into the computer centers and then cut wires from those computers. Or they can deliver the oil spill response microbe to fuel storage. The same microbes can be used against oil damage. But in the fuel tank, those microbes destroy the fuel.  

Miniature robots can also act as testbeds for larger-size robots. Large robots can also operate in swarms. That makes the robot swarm technology suitable for large systems. The car or lorry-size robots can also operate as an entirety. 

The new robots can act as legos. They can form larger structures that can remove themselves. The self-assembly materials make it possible to create self-assembly and self-repairing surfaces and structures. In those structures, the material is formed of the separated robots that can touch each other. 

https://scitechdaily.com/watch-ant-like-robot-swarms-lift-heavy-objects-with-herculean-strength/

Programmable DNA can be the tool that revolutionizes computing and nano-machinery.

"A new DNA computing method enhances speed and reusability by simulating natural gene processes and using a solid glass surface for reactions, reducing completion time to 90 minutes. Credit: SciTechDaily.com" (ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

"Researchers have developed a new, fast, and rewritable method for DNA computing that promises smaller, more powerful computers." (ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

"This method mimics the sequential and simultaneous gene expression in living organisms and incorporates programmable DNA circuits with logic gates. The improved process places DNA on a solid glass surface, enhancing efficiency and reducing the need for manual transfers, culminating in a 90-minute reaction time in a single tube." (ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

"DNA carries the instructions for life, guiding everything from physical traits like hair color to disease susceptibility. Its ability to store vast amounts of information and perform complex biological processes has inspired scientists to explore DNA-based computers. These futuristic devices could be faster and more compact than today’s silicon-based computers. In a new study published today (December 11) in ACS Central Science, researchers unveiled a new DNA computing method that is both fast and rewritable — much like modern digital computers." (ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

“DNA computing as a liquid computing paradigm has unique application scenarios and offers the potential for massive data storage and processing of digital files stored in DNA,” explains Fei Wang, one of the study’s co-authors."(ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

"Folded, origami-like DNA attached to a glass surface, as shown in this illustration, store data for fast, rewritable DNA-based computation. Credit: Adapted from ACS Central Science 2024, DOI: 10.1021/acscentsci.4c01557" (ScitechDaily, Beyond Silicon: How DNA Is Powering Next-Gen Computers)

DNA can replace the silicone in the next generation of computers. The programmed DNA circuits can make fundamental things in the miniaturized technology. The ability to reorder the DNA makes it possible to create cells that can input data to computers in the form of electric impulses. 

The programmable DNA circuit can turn the cell to operate as a robot. Or it can make small machines act like cells. The miniaturized robots can be the tool. 

That makes fundamental things in cancer treatment and many other things. The problem is how to make those robots close and select the cancer cells and release their chemicals or start to destroy the internal structures of the cancer cells. 

The nanomachine can destroy mitochondria from the cancer cell. Or it can cut the protein wires. That makes immune cells' shells low voltage and denies their ion pump operation. The thing is that the nanorobots blur the line between living organisms and robots. 

Nanotechnology is an extremely good tool for medical purposes. Or it would be an extremely good tool. If it can be fully controlled. The nanomachine can be the cell that cannot create descendants or divide. The cell can be the bacteria that creates enzymes that destroy the cancer cells. The nanomachine can be the long protein that travels into the targeted cells and fills them. 

Or it can be one cell from a cell group that cannot divide. That cell can created from cloned cells.  The cell can have a programmed suicide gene and when it slips into the cell group there it is cloned. That cell can die. That thing pulls all of those cells into the low-voltage that touches the cell. There are many ways to destroy wanted cells. But the problem is always how to make nanomachines to search and destroy only wanted cells. If nanorobots go out of control it causes dangerous situations in the human body. 

https://scitechdaily.com/beyond-silicon-how-dna-is-powering-next-gen-computers/

New tools like memory plastics are used to create fundamental nanotechnology.

Shape-shifting membranes that change their shape and profiles are tools that can change things like pollution removal. The same things can also make it possible to create intelligent medicines. Self-assembly structures can be used to analyze neural structures. The self-shaping structures can also operate as extremely sharp loudspeakers and be used in stealth technology. 

Those fundamental materials require new ways to create computers. Things like memory plastics and knowledge of the memory in human brains are things, that make it possible to create intelligent materials that react with their environment. Researchers found that memory is not limited to the neurons. Tissues around them participate in the memory process. 

That means there are structures in those tissues that can store information, and those structures can be transferred into the plastics and nanomachines. The intelligent proteins that control the self-assembly process of the nanomachine and nanostructures are tools that can make them more powerful. 

Advanced nanotechnology requires new types of microchips and memory solutions. The DNA and mRNA molecules are excellent tools for data storage and data transmitters. But how to transfer that information into molecules that should interact with outside effects?

"New phase-transformable porous materials with metal-organic polyhedra that can change their phase among crystal, glass, and liquid. Credit: KaiLi Chien" (ScitechDaily, Shape-Shifting Membrane Transforms Carbon Capture Technology)

The intelligent proteins can recognize things like target cells. When they see them. The protein can open its structures. And release the medicine into those cells. The protein can simply fill the targeted cell. Or it can send the DNA or RNA bite to the cell. And those genomes can simply order those cells to die. 

The nanomachines are sensitive to magnetic fields and non-controlled thermal energy. When ions and anions move in the reaction chamber the outside magnetic fields and IR radiation can cause catastrophic situations. Things like enzyme reactions require extremely well-controlled environments and things like thermal conditions must be fully controlled. 

That means traditional microelectronic systems can disturb those molecules. The problem is similar to quantum computers. The traditional microchips cannot control the system as they should. They form sometimes too much heat and too high high-level EM-fields that can cause non-wanted oscillations in the reactions. Those oscillations destroy the structures. 

For controlling the system controller must have complete knowledge of it. When nanotechnical systems make the nanomachines. They must have systems that observe the movement and reactions in the chamber. 

AI and neural networks make it possible for the system can control multiple points in reaction at the same time. The system can use miniature lasers, ion cannons, and phononic acoustic systems to push and pull atoms and molecules in the reaction chamber. Things like ultra-sharp scanners that can observe electrons at their orbitals are things, that allow the system to observe the nanomachines. 

https://scitechdaily.com/astrocytes-the-brains-hidden-memory-architects-revealed/

https://scitechdaily.com/could-data-be-stored-in-plastic-heres-how-it-works/

https://scitechdaily.com/mind-blowing-discovery-scientists-discover-that-memories-are-not-only-in-the-brain/

https://scitechdaily.com/neural-nanotechnology-nanowire-networks-learn-and-remember-like-a-human-brain/

https://scitechdaily.com/shape-shifting-membrane-transforms-carbon-capture-technology/

Quantum computers and AI threaten data security. The only thing we can do is to be prepared for that threat.

"Researchers at the National Center for Supercomputing Applications are developing new cryptographic standards to protect against quantum computing threats. Their work includes measuring adoption rates and implementing quantum-resistant protocols, with early results indicating gradual progress." (ScitechDaily, Quantum Computing Threatens Cybersecurity: Are We Prepared?)

Mathematicians found the new prime number. (2^136,279,841 )− 1. That is a large number. If the computer uses Riemann's conjecture to break the code, that thing means that it takes a very long time to break the encryption that is made by using prime numbers. The system must try every known prime number for the message. 

That means traditional computers may take years to break the code. The neural networks can start simultaneous calculations at multiple points on a number line.  And that shortens the time very much the system can consist of thousands of personal computers. And that makes it possible to solve complex cryptological problems in a short time. 

The thing that connects neural networks to quantum computers is that neural networks might look like single, solid-core, or monolithic computers. But those networks are multiple computers. Those computers can operate independently. As well as. They can operate as an entirety. 

That thing means that when the neural network takes on a new mission, it must not stop. The traditional Turing machine must stop before it takes the new mission. If one unit of the neural network gets stuck, that means other participants will help it. That means the computer that is stuck can clean up its memories. And before it, the other computers can download that data into them. 

In the morphing neural networks, the system can analyze what caused the overleak. The morphing neural network means that the role of the participants changes. The AI-based control makes it possible to create a system with advanced self-diagnostics. That kind of system allows to use same systems for multiple uses. 

If the system also backs up the RAM- memory to independent hard disks. That denies the data loss if some units must be rebooted. Quantum computers can make similar things. It doesn't need to stop. But the quantum computers are new tools. And there is a long need to use binary computers. 

Three most powerful computing systems. 

1) PC-computer based neural networks 

2) Supercomputer-based neural networks 

3) Qauntum computer-based neural networks. 

Another thing is that quantum computers are coming. Maybe the NSA already has those systems. But also Chinese and their company states have their quantum computer projects. Those nations have money for that kind of system development. 

And that means our data security is endangered. The major problem is that things like RSA encryption are made to protect information against single computers. The major problem is that the RSA encryption algorithms are created for binary computers. It took years to create prime numbers using supercomputers. 

The quantum computer can create those prime numbers in less than a second. And that makes them the ultimate problematic tools. Those systems can also create an ultimate defense. The AI-controlled neural networks can also make it possible to create prime numbers more effectively than single computers. 

A supercomputer is a powerful tool, but neural networks are more powerful, especially in cases where the system must create the prime numbers from the number line. When somebody asks what is the most powerful computer system in the world, I would answer that the neural network of quantum computers. 

https://scitechdaily.com/quantum-computing-threatens-cybersecurity-are-we-prepared/

The photonic chips are the new tools for computing.

 

Things like quantum computers require ultra-fast data handling systems to control them. The quantum computer is the most powerful calculation system in the world. The problem is that the quantum computer requires binary computers to input and output information to the system.  Researchers cannot connect things like screens and keyboards straight to the quantum computer. That's why there is needed a binary computer between the quantum state and input-output devices. 

When the controlling system notices some anomaly it must react immediately. Another thing that the system requires is that. The system that controls the quantum entanglement should not disturb the quantum entanglement and sensors. 

That downloads and uploads data in and out from superpositioned and entangled photons. Or some other particles. All electromagnetic systems cause electromagnetic fields that can affect data that travels in the qubit. 

So the answer is the photonic microchip. The photonic microchip can load data to photons and then deliver it to the quantum computers. There is one little problem with photonic computers. The system needs regular quantum computers to drive information to photonic computers. And, the new nanomaterials can make it possible to change photons to electricity and backward. 

In this model, the quantum computer has three stages. 

The regular binary computer. 

The photonic binary computer

Quantum computer. 

Image 2

The input will happen through the regular binary computer, which decodes it to the photonic binary system. And then the photonic binary system transfers data to the quantum state. When the quantum state makes its duty, the system will return the data to the regular binary computer through a photonic binary computer. 

This model means that the system is scalable and it saves energy. The binary system calls those other layers or states to work with a mission that takes too long time for the first level. If photonic computers cannot solve the problem in a certain time. The system transfers the problem to the quantum state. 

Image 3 

Those photonic processor rings look like token ring architecture. (Image 2)The processing system can involve many processors. That allows it to drive multiple databases at the same time. Or they are hybrid systems. That uses mesh-protocol-based architecture (Image 3). 

In that system, the central processor shares the missions with the other processors. The neural networks use mesh protocol. The mesh- or distributed networks have one benefit to centralized networks. If one processor has problems or damages, the data can pass that processor. 

When we think about the primary computers the photonic microchips can make the ring where they drive information. The system can involve two photonic microchip rings. It can compile the intermission after each processor drive. And if there are anomalies like different results there is something wrong. 

After a certain time. The system can transfer data to the next processor. And when the processor transfers the mission to the new processor. It can make the backup. 

Then there is the control system between those two rings that can compile the data. And that can be the new tool for systems that drive complex data structures. Things like the large language model. The LLM-type systems require. The new physical tools to handle information. New systems must support quantum calculation more effectively. 

The system must start to drive multiple databases at the same time. The photonic systems allow researchers to make new systems. That supports machine learning more effectively than traditional systems. 

https://scitechdaily.com/harnessing-light-quantum-materials-supercharge-data-transmission/

https://scitechdaily.com/integrating-photonics-with-silicon-nanoelectronics-into-chip-designs/

https://scitechdaily.com/microscopic-marvel-a-photonic-device-that-could-change-physics-and-lasers-forever/

The new nanomaterials can make it possible to change photons to electricity and backward. 

When requirements grow, programs grow.

The main problem with computing is when developers make something. There is needed new solutions almost immediately. Those new solutions make the application interesting. And many times. Those new solutions mean new abilities for applications. New skills require new libraries. And that thing cumulates the size of the program. 

The new libraries require more space and more effective computing. The thing is that AI is going to more detailed program code. When we think about the first AI "chatbots" the simple programs that asked people some questions, and then the program gave some pre-programmed answers, we must realize that those programs looked intelligent. 

One example of those programs is a program that asks: 

Are you a boy or a girl?

A: Boy

What's your name"?

A: John

How old are you?

A: 23

Where do you live?

Bristol

Then the program said: 

Please to meet you: 

You are a boy, whose name is John. You are 23 years old, and you live in Bristol. And I'm your servant. 

Those things are quite easy to program by using C, Java, or C++. But that program puts answers to the right points in the programmed text. And the form of the text doesn't require us to notice things like "she" or "he".  That simple code is an example of pseudo-intelligence. One "else" command makes it possible to create an answer that if the answer is something else, the computer answers that "you must answer "boy" or "girl". That makes those programs look intelligent. If the programmer has time, it's possible to add all British first names and all the world's city names to the list of allowed worlds. And that gives an appearance of intelligence. 

The thing is that when we think about the modern AI that can control things like cars, we must realize that in the middle is a large language model, LLM. The LLM itself does nothing. But it transfers the data to the part of the code. That controls the self-driving cars. That LLM stays at a tolerable size. But the libraries that the system needs grow. That makes it hard to control data in the system. 

The network-based architecture means that the system can have multiple, limited AIs or LLMs that are connected into the entirety. That thing makes the system more flexible. Because the system has many separate operating cores. It allows the developers to create those cells as modules. Every module is an independently operating part of the structure. 

Above: Mesh network. In network-based systems, every computer runs its own LLM and modules connected to it. So every computer involves certain action series. And, each computer is responsible for its part of the system's skills. 

The structure might look like some kind of mesh topology. That means that there is a central LLM. That is called the specialized LLM to make the mission. The system operates like a mesh topology. When as an example a robot car drives a robot to the shop it sends a mission to the next operator. 

That operator is the robot that goes into the shop. The mesh model means that the system must not bother the central actor all the time. That means that if the central processor or LLM is busy or the system is out of connection the sub-system can continue its mission without the central actor's support or control.  

When a user gives orders to the central LLM. That can transfer the mission to the sub-LLM that has data to complete the mission. The networked structure makes it possible that one mission doesn't keep the entire system busy. When one module operates with some mission. Other parts of the system can perform other duties. 

In modern neural networks, the middle of the system is the LLM. The LLM is connected with sub-LLM systems. The system looks like a neural network. When an owner calls, the car to the door. The central LLM gives a mission to the LLM that controls the car. The car's AI system can interact with surveillance cameras and the surveillance system tells if there are some dangers in that area. 

Or if there are no surveillance cameras the owner can send a drone that looks if there is something behind corners. The drone can hang over the vehicle and send the image to the computer where the car's corners are going. The car requires a 3D camera system and radar. That it can drive safely. 

And then it requires large-size databases that tell what the car should do in all situations that it can face on the road. There are lots of things that the system must avoid. When we think about the models of the complex systems we must create the systems using the cell- or neural-based networked architecture. For these reasons, I told you before.