Intelligent glasses and AI.

Intelligent glasses and AI. They don’t destroy our ability to think; we destroy our ability to think ourselves. We use AI without criticism. We don’t check the sources that AI uses. 

Intelligent glasses and AI are tools that can bring human-AI fusion and singularity closer. Intelligent glasses have miniature cameras. That makes it possible to transmit information to AI. That tool is incredible for both free time and business work. Intelligent glasses allow a person to work in public places. 

When a computer screen is connected to those systems. 

That keeps users’ privacy at a high level. When a programmer uses data glasses and looks at the screen. The AI reads that text and gives advice. But then that advance can turn the AI into a programmer. The idea is the same with a chess game; there, the person uses headphones, AI, and a camera to make perfect moves. The AI gives orders on where the player should make moves. In this case, the real winner is the AI. We say that we are afraid. That AI takes our jobs. But at the same time, working life requires more effectiveness. 

When we cry that programmers lose their jobs to AI. 

We forget that today companies have no time to train new workers. They want full-stack coders. And where can they find those full-stack coders if new programmers cannot get any practice? Without practice. There are no masters. This means that workers are forced to use AI. People must be effective. And there is no time to give advice. People fight for their workplaces. So, that means there is no time to think. People must not think; they must act. And that is a sad truth. Reality is that AI is here. And we must accept it.

When we think about the jobs that AI takes. Well. Those jobs are already outsourced to India and other places; there is time to train programmers. The only problem is this. There is no space to think. The only goal that measures effectiveness is money. 

Only goal. What we can put to ourselves is how to turn expertise into leadership. Leadership means that expertise and precision should turn into money-making. And that turns people to use AI. When we think that an untrained programmer who uses AI can produce results as fine as an engineer, the company selects an untrained person. 

The reason is simple: the engineer gets a higher salary. The untrained person who makes similar-looking things has a lower price. The customer cares about what the product looks like and how it works. They don’t care about how many dead lines it includes. This is the philosophy. 

The low-trained. Person is easy to replace. The problem is that. Everybody wants to be lawyers. Or. Medical doctors. Those things require high university training. And the problem is that. The entrance exams require perfect success. And before those exams. The matriculation examination requires complete success. Those things force some people to use intelligent glasses and AI to make their answers. 

This means people give up their own willingness. And their ability to think and search for information is given to AI. When the entire working life revolves around effectiveness, measured by how many successful work outputs a person can make in a certain time. That leads people to use AI in their work. They don’t check facts. They might not trust AI. But they use its information without even clicking the source link. The attitude is this. Some experts made the AI. And that means AI will not make mistakes. So, why should anybody click any sources? By thinking that way. Clicking source links is a waste of time. 

When we look at results. We. See only information. 

That we see from outside. 

We can call that information loud information. That information is collected from interactions with humans and machines. 

Statistics don’t involve silent information. Silent information is our thoughts. Things that nobody sees from the outside. If. We don’t tell that information to outsiders. That means information stays silent. 

We must realize that records and statistics involve only information that we see from outside. And an attitude that “someone else does”. Or, “who cares if it is wrong or right?” “They don’t check it anyway. “ That is a dangerous path. If people don’t dare or care to tell that somebody makes bad work. That escalates false information and bad code through the entire system. 

It doesn’t matter what we think. What we do and what others see matters. The thing that people see. It is what we do. When AI gives a wrong answer. The answer is wrong to us. Only. If we know that it is wrong. But if we still use the wrong answer. We mark it right anyway. And that is dangerous. The AI thinks in terms of statistics. And this means that. The AI can turn wrong into something that seems right. This means that, in the worst case. The entire system operates on wrong information. 

A new quantum computer solves a math problem in 15 minutes. That binary computers can never solve.

“Scientists used a new error correction method to encode 70 logical qubits and solve a problem that is intractable for classical computers. The quantum computation took about 15 minutes, while leading classical methods would require an impractical amount of time. Credit: Shutterstock” (ScitechDaily, Quantum Computer Solves a Problem in 15 Minutes That Classical Methods Can’t Practically Compute)

“Researchers have demonstrated a quantum computation that appears to exceed the practical capabilities of leading classical simulation methods while also addressing a longstanding problem: how to verify the result.”(ScitechDaily, Quantum Computer Solves a Problem in 15 Minutes That Classical Methods Can’t Practically Compute)

A quantum computer completed a difficult calculation in about 15 minutes, while leading classical simulation methods would require prohibitive amounts of time. Just as importantly, the experiment included a way to establish confidence that the quantum result was accurate.”(ScitechDaily, Quantum Computer Solves a Problem in 15 Minutes That Classical Methods Can’t Practically Compute)

“The system completed 2,415 logical two-qubit operations and 468 logical “T gates,” two measures of quantum circuit complexity. Encoding the circuit reduced the effective logical error rate to one tenth of the physical error rate, allowing the computation to maintain high fidelity despite the large number of operations.”(ScitechDaily, Quantum Computer Solves a Problem in 15 Minutes That Classical Methods Can’t Practically Compute)

"Common quantum logic gates by name (including abbreviation), circuit form(s) and the corresponding unitary matrices". (Wikipedia, Quantum logic gate)

There are two major problems in quantum computers. First is that. Nothing that another quantum computer can check or inspect the result. The other problem is. How to make sure a quantum computer gets the right answer. This means. The quantum computer may make many errors in the process. From the beginning of the formula. To the complete answer. The danger is that the system can get the right answer. But using the wrong methods. The danger is that. The control formula is made using binary computers. It can give the right answer. Or an answer that seems right. 

Even if a quantum computer makes mistakes. And. If a quantum computer works incorrectly. That can cause errors in extremely long calculations. That take years. If. A computer solves a problem in one year. Inspection takes another year. So, making an answer and proving it takes two years. And this is one problem. 

“Random circuit sampling (RCS) has long served as a benchmark for testing whether quantum computers can outperform classical systems. In this task, a quantum computer produces patterns so complicated that classical computers cannot efficiently recreate them.” (ScitechDaily, Quantum Computer Solves a Problem in 15 Minutes That Classical Methods Can’t Practically Compute)

A quantum computer solved a mathematical problem. That was impossible for binary computers in 15 minutes. This means that there are limits to quantum and binary systems. The binary system is faster and better. When. Calculations are easy and small. But when complexity in calculations grows. That turns. Quantum computers. More suitable. The big problem is how to detect errors in quantum systems. The only thing that can inspect calculations that are too complex for binary systems is another quantum computer. 

When a quantum computer inspects and tries to detect errors. 

This system calculates all calculations backward. That means that getting the answer takes 15 minutes. And confirming that answer takes another 15 minutes. This looks impressive. But there are many problems. The biggest problem is that the quantum computer. It follows similar laws as other computers.

Increasing calculation capacity. It provides resources for more complex simulations and modelling. So, researchers bring more complicated formulas to computers. Increasing computing power. That increases the complexity of formulas. 

When researchers want to make a simulation. To simulate gas flow. They search for what that gas flow does. And then they try to make a fractal that follows those routes. The same way. It is possible to create material simulations at the quantum level. This thing. It makes it possible. To create very high-accuracy simulations. Those simulations are needed to control those materials with extreme accuracy. 

https://postquantum.com/quantum-computing/rcs-benchmark/

https://scitechdaily.com/quantum-computer-solves-a-problem-in-15-minutes-that-classical-methods-cant-practically-compute/

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

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

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

The Jacobian conjecture is partially solved. (Jacobian conjecture is disproved in three or more dimensions)

 

Jacobian conjecture is disproved in three or more dimensions. But in the two-dimensional model. It remains open. 

“A remarkably simple three-dimensional function has exposed an unexpected limit to a century-old mathematical conjecture. Credit: Shutterstock. An AI-assisted counterexample disproves the Jacobian conjecture above two dimensions while leaving its original two-dimensional form open.” (ScitechDaily, AI Helps Crack an 87-Year-Old Math Conjecture With One Tiny Formula)

AI is the basis for new mathematics. The ability to share problems and connect them again makes that tool impressive. In cases like the Riemann conjecture, AI is the best tool in the business. The system can share the number line across different servers. And then that makes this system an impressive code-breaking tool. In this case, the AI tries to make calculations. That encryption system is made backwards. And that opens the original bits to an attacker. The Riemann conjecture generates binary numbers. That connects to some other formula. 

The last impressive thing that we see is the solution to the Jacobian conjecture. That thing is important in linear algebra. This makes it a tool that is suitable for economics. In that case, the Jacobian matrix is used. For resource optimization. The next examples are things. There, the Jacobian matrix is used. 

Mathematics: An important part of methods for solving differential equations.  

Engineering: Helps model and optimize complex systems.  

Economics: Analyzes economic models and optimizes resources.  

Computer Science: Used in neural networks and machine learning algorithms to aid optimization.  

So, the Jacobian matrix is a versatile tool that provides deep insight into both mathematical and practical problems.

AI  shows that the Jacobian Conjecture is wrong. If. There are three or more dimensions. This means that all polynomial functions cannot be introduced backwards. And that means all calculations. They cannot be checked simply by calculating all calculations backward.

But. The Jacobian conjecture is wrong only in dimensions ≥3. The two-dimensional problem is open. So, dimensions 2≥ are still open. This means. That.

Encryption algorithms that involve the Jacobian Conjecture. It should have three or more dimensions. 

“In mathematics, the Jacobian conjecture is a conjecture concerning polynomials in several variables that states that if a polynomial function from an n-dimensional space to itself has a Jacobian determinant that is a non-zero constant, then the function has a polynomial inverse.” (Wikipedia, Jacobian conjecture). The conjecture can benefit the Jacobian matrix in its models. 

“In vector calculus, the Jacobian matrix of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. If this matrix is square, that is, if the number of variables equals the number of components of function values, then its determinant is called the Jacobian determinant. Both the matrix and (if applicable) the determinant are often referred to simply as the Jacobian. They are named after Carl Gustav Jacob Jacobi (1804-1851).”(Wikipedia, Jacobian matrix and determinant) 

“If m = n, then f is a function from Rn to itself and the Jacobian matrix is a square matrix. We can then form its determinant, known as the Jacobian determinant. “ (Wikipedia, Jacobian matrix and determinant) 

In texts. The Jacobian determinant sometimes is referred to as "the Jacobian".(Wikipedia, Jacobian matrix and determinant) 

“The Jacobian determinant at a given point gives important information about the behavior of f near that point. For instance, the continuously differentiable function f is invertible near a point p ∈ Rn if the Jacobian determinant at p is non-zero. This is the inverse function theorem. Furthermore, if the Jacobian determinant at p is positive, then f preserves orientation near p; if it is negative, f reverses orientation. The absolute value of the Jacobian determinant at p gives us the factor by which the function f expands or shrinks volumes near p; this is why it occurs in the general substitution rule.” (Wikipedia, Jacobian matrix and determinant)

https://scitechdaily.com/ai-helps-crack-an-87-year-old-math-conjecture-with-one-tiny-formula/

https://esimerkkeja.com/jacobin-matriisi-esimerkki-ja-sen-sovellukset-matematiikassa/

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

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

https://en.wikipedia.org/wiki/Jacobian_matrix_and_determinant#Jacobian_determinant

Quantum networks and phase singularity.

“Researchers have shown that quantum entanglement can survive a journey through a busy metropolitan fiber network carrying powerful conventional data traffic. Credit: Shutterstock” (ScitechDaily, Quantum Photons Survive a 24-Kilometer Journey Through Chicago’s Busy Internet)

Quantum photons traveled 24 kilometers in Chicago. And another thing that can make that case interesting is this. Those quantum photons or quantum entanglements survived in a regular optical fiber network. 

This is a big advance in quantum communication. And it allows developers to connect quantum computers. But another thing that makes the quantum internet interesting is this.  The information in that network. It is almost fully secure. Because. Information that travels in a quantum network is bound to a physical particle. That makes it possible to secure data. Data that travels in the quantum network. It can be stored in photon series. Or into individual photons. 

This means that a quantum network can transport data in internal structures. The photon series can hide messages. That is stored in the individual photons. If. Somebody steals information from photons. Those photons lose their energy. So, we can think of each photon as a key. Curves in the photon structure. They store data. And if a photon loses energy. That makes it smaller. Researchers can split a photon into two identical photons. 

But the sum of those photons' energy levels is identical to the original photon. This means their energy level is half of the original photon. The situation is similar to the key losing half of its size. That key cannot open the lock. And the system sees that thing. But can somebody split a photon? That travels in the quantum network? We know that there are laboratories. There, researchers investigate technologies for breaking those ultra-secure data networks.  

Quantum networks are not completely safe. Connection points. Those points. Transform information from the quantum internet into electrical impulses. For. Binary computers. The attacker can attack those points. Or to the regular LAN network that delivers data into laptops. Even if we keep that binary state as short as possible. And. Make a faraday cage around that space. This state exists. And. Modern technology. Like drones, allows them to steal information from those spaces. 

A drone can carry a relay station that transmits data out from those ultra-secure spaces. The drone puts its antenna in that cage. The thing that makes those networks safe could be the multi-channel transmission. In that model, the WLAN transmits data by sharing it between multiple channels. The information involves data packets that have serial numbers. That system transmits all those data packets. 

At the same time. Or it can use mixed order. Serial number. It allows the system to sort received data packets into the right order. That makes WLAN more secure. But as we know. There is no absolute security. There is vulnerability in all networks. If. Somebody damages a quantum network. That means there must be some backup system. 

A big problem with quantum photonic networks is that they require a physical structure where they operate. This means they are not as suitable for satellite data transmission as they are in other cases. There, photons can travel in the tube that protects them and the data that they carry. The laser beams are also suitable tools for data carriers. But that requires a laser beam that carries information. 

It is protected so that the observer cannot see it.  The internal laser beam. That travels in the other beam. It can solve that problem. If. Somebody tries to steal information from the internal beam. That travels in the outer beam. That actor must take that data through the outer beam. That dims the beam. And it alarms the controller. 

Darkness can transport photons faster than light. 

When darkness protects information. Phase singularity. It is the thing. That can protect a photon inside it. The phase singularity can also travel “faster-than-light”. Because. It makes fewer curves. This thing means that because of the phase singularity. It travels in a straight line. And a photon makes curves. So. Because a photon makes curves. It travels. Through a longer trajectory. Than a phase singularity. This means that a photon and a phase singularity travel at the same speed. But a phase singularity selects a shorter route. And that makes it reach a goal before photons. 

The most incredible thing that can make the quantum internet so effective is something we can never imagine. It is the thing called phase singularity. That is a phenomenon in wave movement. There. Amplitude is zero. The optical vortex can travel “faster-than-light”. Because. It doesn’t make any curves. This means that this vortex travels a shorter distance than a photon that makes curves. Phase singularity. It can also protect information. Stored photon inside it. 

Optical vortex. It could also transport information. The photon is locked inside it. This means that. The phase singularity. It can protect the photon. And if that phase singularity travels in a laser beam. That makes it an interesting information transporter. That system can take long-range quantum networks and remote control to the next level. 

https://www.sciencealert.com/physicists-found-something-that-can-move-faster-than-light-the-darkness-inside-it

https://scitechdaily.com/quantum-photons-survive-a-24-kilometer-journey-through-chicagos-busy-internet/

https://physicsworld.com/a/darkness-can-travel-faster-than-light/

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

Russian intelligence uses captured web cameras as a spy tool.

“Russian intelligence services are actively compromising internet-connected security cameras across Europe to gather military intelligence, according to a new advisory from the Dutch General Intelligence and Security Service (AIVD) and Military Intelligence and Security Service (MIVD). (Bitdefender, Russian hackers are hijacking internet-connected cameras to spy on NATO and Ukraine)

Russian intelligence uses internet cameras for spying on NATO and Ukraine. How effective is this kind of spying? The answer is that it depends on what those cameras see and the purpose of those operations. Those cameras can be used to locate people and their vehicles. Or the door camera. It can help agents create timetables for targeted people. Door cameras can also be used to warn agents who operate in some houses. The agent who puts surveillance equipment in a place. Benefits from those systems. Those systems. They can tell those operators when the apartment’s owner comes home. 

U.S. and Israel used hacked traffic control cameras to locate Iranian leaders for air attack. 

The door codes can tell if someone walks into the house. The personal door codes. They can help to map the person’s route in the house. And if spies are making a burglary in some apartment. The use of personal entry codes. It can warn those spies. Or it can act as a stand-by order for real bad boys. Hit agents need information about routes. That people use in those houses. They can use that information for kidnapping. Agents can use medical components to get information. 

That they want. That information. It can be access codes to critical systems. Or access to a critical environment. 

In the same way. An anti-VIP team. Can use those door cameras. And traffic control cameras to target people for elimination. And here we must realize that the AI-boosted systems. They can easily collect data about people and their routes. The system uses images from hacked cameras. And the image recognition tools can see where targeted persons are. 

This kind of information. It can be useful for those attackers. But sometimes surveillance cameras can collect information from other vital objects. The security camera that sees the screen can deliver that information as effectively as some malware that infects the computer. The security systems of the house. They can also involve critical information about people’s IDs. This information allows espionage operators to gain access into the building. 

The AI-based image processing tools. They can uncover even state secrets. If. Hackers can intrude on an airfield's security cameras. Those people can collect information from the aircraft and other important material. In harbours, the situation is similar. Hacked surveillance cameras. They can collect data from ships and other important things. Things that the surveillance camera sees. They determine the effect of that type of spying. 

https://www.bitdefender.com/en-us/blog/hotforsecurity/russian-hackers-hijacking-cameras-spy-nato-and-ukraine

Most of the internet traffic. It is. Not made by humans.

Most of the data that travels on the net involves information that has nothing to do with humans. That data is invisible to us. It involves things. Like system updates, system information. TCP/IP checklists. Resending TCP/IP information when checksums don’t match. The checksum tells. That all data reached its goal. If. The checksum doesn’t match. The system resends information. 

The dead Internet conspiracy theory. There, most of the net is AI-generated bots. The AI-created texts, videos, and applications seem human-made. We create more content than ever before. But we must accept that most of the data that we deliver is images or movies. Today, AI can generate almost everything by following instructions. That people give them. AI  can create. A 100-page novel. In a very short time. So if we give ten words as an order to create a novel. The length. Of that novel is about 100 pages. 

Who makes the work? Is it me or AI? At this time, we must say that most of the work is made by AI. And that is one of the problems. If. We say that we create more and more content. The maker of shared content is more often AI. But is the net dead or alive? We could calculate the data that human users create by writing themselves. Or how much data human users use or share? When they share real photographs. And then we can compare that data mass with the data. 

That AI-generated texts and images involve. This means that the internet is dead. If most of its content is made using AI. But then we must realize that AI can surround data. AI can use images and texts. That it made. And then generate new images and texts by using other AI-generated content as a model. The problem with that advance is this. The AI follows page rank. To make images and content that pleases users. This means that this thing accumulates AI-created content. 

And then we must draw some conclusions about the dead internet. Is it just theory? Or something that we misunderstood? Most of. The internet traffic. Is other than communication between people. That content involves the machine BizTalk. That BizTalk is invisible to humans. This means that most of the data that moves on the net. It is something other than social media. Media, or something else. Than humans produce. 

Sometimes dead internet means homepages. And emails and other content. That the owners are forgotten. Especially in the early years of the net. People opened many emails and created homepages. That are still there. But those people have forgotten passwords. Or those passwords and usernames are hosted. By. Companies that no longer exist. People can open emails and forget passwords. People can open workspaces and homepages. And then. They forget those addresses. Sometimes people. Just change their phone numbers. And then they have no access to data that still exists. 

Dead code is one of the things. that uses lots of space. That dead code. Means code that is in the computer program. But that code is neutralized. It forms an empty line in that code list. This neutralized code fills hard disks. We cannot ever see those code lines. Sometimes. They are neutralized because the programmers are in a hurry. This means. They must turn the code into an “instruction line”. These kinds of things affect the checksums that TCP/IP sends. When. It must confirm that the data traveled. Between. The receiver and the sender. It is not changed. 

The information storage. In the network is impressive. But it's not endless. This means that the data storage can be filled. The data storage expands. But at the same time, people create more content. AI-created. Content is more complicated and requires more memory than regular texts. 

A new semiconductor is a big step for photonic computing.

“When two pulses of different colored lasers light  (the two waves at the top of the image)meet in a new device created at the University of Michigan, researchers create a beam of electrons (small golden particles) that flows in a controllable direction. By changing the laser colors, the electron beam can sweep through different directions. Like the beam of a lighthouse. Credit: Yiming Gong." (ScitechDaily, New Semiconductor Device Turns Light Into a Directed Current)

"The light-controlled electron current could open new paths for sensing, telecommunications, and other advanced technologies.” (ScitechDaily, New Semiconductor Device Turns Light Into a Directed Current)

“A pair of laser beams can now send electrons through a semiconductor in a chosen direction without any external electrical power. Researchers at the University of Michigan built the device to explore a previously unobserved physical effect and demonstrate that light alone can both generate and steer an electronic current. ” (ScitechDaily, New Semiconductor Device Turns Light Into a Directed Current)

The biggest problem with photonic computers is the nano-sized optics. That optics is needed to transmit information in the system. It uses light for data transmission. Photonic computers are becoming more interesting. Because they could use less energy. But the main role is that photonic computers. They are immune to EMP (Electromagnetic pulses). Optical data storage doesn’t care about electromagnetic radiation. The problem is. Of course, the control system. Of those computers. Moving parts like turning mirrors. Their turning mechanisms are still vulnerable. So. If we want to make a computer that is fully protected against the EMP. 

We must put the entire computer. Along with its power source, in the EMP-protected space. The name of that space is a Faraday cage. 

This metal cage denies radio waves. Travel through it. The system must communicate with the internet by using an optical switch. This means laser data transmission through that Faraday cage. The computer must use laser data transmission with the EMP-protected computer and the net. The system must not have one single iron or metal wire through the Faraday cage. Or. The EMP pulse travels through it. But optical communication through the cage. It could solve that problem. 

There are actually three versions of photonic computers. 

1) The system where data travels in laser beams between the microprocessors. This system uses conventional microchips. Laser beams transmit data into photovoltaic cells.  They transform it into electric signals. Microprocessors compute those signals as regular computers. 

2) In the second photonic system, the data travels in photonic form through the entire system. The system. It can have nano-scale optics. That controls light. Like an electric computer controls electric signals. Optics require electric systems. That control those mirrors. 

3) Fully photonic computers. There, the entire system operates. With. Some other than regular mirrors and prisms. Things like photoacoustics are promising tools. The photoacoustic or optoacoustic systems. It could control light by using pressure or sound waves in the optical materials. One of the things that can make this kind of dream possible. It could be the tool. 

It uses electric eruptions in a mountain crystal to manipulate light. The light beams can be conducted to the quartz crystal. Then the system sends pressure waves into that crystal. That causes electric phenomena that affect light. The idea is to aim the laser beam into those lightning strikes that form in that crystal. But the problem is how to make those crystals small enough. 

New semiconductor aims light precisely in the desired direction.  Researchers at the University of Michigan created a system. Two laser beams send information into the semiconductor. That semiconductor resends that information in the desired direction. This system can turn light in the desired direction. That is important for photonic data transmission. The system must control light beams. The diameter of those light beams is extremely small. And that makes it hard to create normal mirrors. These types of crystals can bring optical computers one step closer. 

The crystals could manipulate natural light. They can make a new model for quantum optical stealth systems possible. But even if they could manipulate only IR light. That could be fundamental. If the system. It could aim just the IR radiation into the desired direction. That could make it possible to deny the IR signature. The system. It just directs IR light away from the observer. That makes it possible to create a system that is not visible in IR light. We know that turning the natural light away from the observer is challenging. But changing the direction of one wavelength type is easier. And the ability to aim IR into the desired directions. It can give the ultimate night-operation capacity. It could turn the system invisible to IR cameras. Because. It aims IR radiation away from the system. 

https://scitechdaily.com/new-semiconductor-device-turns-light-into-a-directed-current/