Innovation is not the end. It just changes its shape.

Does AI destroy program development? Or, does AI destroy innovation? That is a good question. We must realize that there is no endless need for computer software. Not even games have a space or markets in the endless innovation and new products. This means that there is not. A possibility to create new things endlessly. There is a point that we can call: the Omega point. There is no room to continue the R&D process on that path. This is one of the things that we must realize. The AI is a tool that can make many things faster than humans. 

Wikipedia determines innovation like this: “Innovation is the practical implementation of ideas that result in the introduction of new goods or services or improvement in offering goods or services. ISO TC 279 in the standard ISO 56000:2020 defines innovation as "a new or changed entity. Realizing or redistributing values". (Wikipedia,https://en.wikipedia.org/wiki/Innovation)

Others have different definitions; a common element in the definitions is a focus on newness, improvement, and the spread of ideas or technologies.” (Wikipedia,https://en.wikipedia.org/wiki/Innovation)

Soo. If. We think about. In software development, humans are the things. That makes innovation. The economically successful innovation itself. Needs somebody interested in the product. But then we must realize. That. The innovation forms from an idea. Innovation requires an idea. And need impact.  If innovation and customer meet, and the customer feels the need for that thing. 

The innovation can turn economically profitable. But. If people think. That they don’t need some innovation, that destroys innovation. The fact is that we don’t need endlessly new software. And that is the thing that we must realize. If we make programs for the garbage, that is programming for nothing. If we work for nothing, that is a loss for the firms that we are working for. 

Programming and innovations are not over. But they get a new shape. Tomorrow, people will give. The requirements specification for AI. Which responds to those needs. And turn them into parameters. That allows it to make things. 

The purpose of the firm is simple. It must bring profit for its owners. This means that the programming is not an absolute value. There must be somebody who buys software. In modern firms. There are only a couple of people who really innovate the things that the firm sells. In games and other programs, the user interface and graphical design are important. And then the programmers must make the code. 

That is fit for those models. Most of the programs. Are games. And games. They look very much alike. Like each other. This means that. There is a question. Is there room for new ideas in the programming industry? And is it possible to create new ideas in that sector? The big thing is that. Customers care about whether the program works, not who made it. 

So, AI brings new things to the software industry. But. New things cannot be built on the old ones. The old models must someday be crushed. That brings space for new innovation. We must realize. That we cannot endlessly run. On the antique methods. And using antique production tools. The new tools bring effective methods. And the AI is a tool that can replace people who do mechanical work. Like copy-paste codes. And this means. The people who know what to do have a job. But. That causes loss to the trainees and junior coders. This means that the AI will do more. And more programming work in the future. This means programming is not over. But it gets a new shape. 

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

The next step in generative AI is interactive generative AI.

The next step in generative AI is interactive generative AI.

The interactive AI means that the person just talks to AI and then AI follows the orders. The ability to use the natural language makes it easier to communicate with robots. The human operators can give instructions to robots on what they should do next. 

The interactive AI-based translator makes it possible. People can use their languages in communication whenever they want. The translation program can installed on cell phones. And then people can use it like any other social media program. The communication could happen through central computers where the server program translates words to the target language. 

Or the system can use the morphing network or cloud-based architecture where a cloud of cell phones shares their calculation capacity. Interactive AI can also be a powerful tool for programming and any other things like the R&D process of physical tools. 

The interactive AI can give instructions to programmers. Or it can generate the code from examples. Then the AI asks for the databases' names that want to connect with the program. If AI has access to hard disk, it can search those databases itself, and make the paths. 

There is the possibility that the AI has a multi-tasking user interface. If the names are not  said clearly. The AI can ask to write those filenames. Or it can suggest files that look a little bit about the name that AI heard. The AI can give lists about the found names and then the user can select the right one. 

The next big step in the development of AI is interactive, generative AI. Traditional generative AI just follows the order like "draw me a flower". And then the generative AI just creates that image. Interactive AI discusses with the user, it asks what colors and surfaces the user wants to use in the flower. 

The person can ask to make the yellow flower with crystal leaves and metallic surface and interactive AI just starts to make the flower. During that process, after every stage, it asks is customer happy. Is there something that wanted to change, or is there some hue of color that the user wants to use? 

If the user wants the AI to make a painting, the AI might ask if is there some painting, that the user wants to use as the base. Then the AI asks what parts are the best in the painting, and then it might ask what details the user wants to use in the AI-generated version. 

In the case of the R&D process, the interactive AI is the tool that can ask if is there some airfield where the aircraft must fit. Then it can ask some special variables what are the wanted payload and other abilities that the system must have. If AI creates drones it requires the computer code, that it uses. 

The complicated AI requires powerful computers, and those computers require cooling systems and other kinds of things. Also, the sensors and other things like the drone's purpose determine it's size. The things that the AI also requires are manufacturing tools and available materials. Interactive AI is a tool that discusses with people during the generative process. 

If the interactive AI  drives a car it acts like a second driver. The system might observe a human driver, and if that person is tired or nervous, it can ask what's problem, is and tell that the person needs a break. The interactive AI can take information from the traffic control and adjust the car's speed to a level that it must not stop. The AI can also make a report to authorities if the person seems drunk or somehow angry and request traffic police to stop the driving. 

If a driver makes the mistake that takes the car into the traction. AI can fix that error. When AI takes control the clutch separates the wheel from the power steering so that the driver cannot turn the car. That thing is an important detail in robot cabs. If a drunk person can take a car in control, that thing causes a terrible situation. 

When every single wheel is operated in separate electric engines the AI can adjust their rotation direction and rotation speed. These kinds of systems can installed in hybrid and electric cars. This type of vehicle can use diesel- (or combustion)-electric driving systems. And those systems make them very fast. 

https://www.analyticsinsight.net/interactive-ai-a-step-closer-to-conversational-artificial-intelligence/

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

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

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

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

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

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

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

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

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

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

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

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

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

// Standard C++ includes

#include <iostream>

#include <cstdlib>

// Include the Connector/C++ headers

#include "cppconn/driver.h"

#include "cppconn/exception.h"

#include "cppconn/resultset.h"

#include "cppconn/statement.h"

// Link to the Connector/C++ library

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

// Specify our connection target and credentials

const std::string server = "localhost";

const std::string username = "root";

const std::string password = "";

int main()

{

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

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

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

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

    try

    {

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

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

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

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

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

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

        {

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

        }

        delete res; // Delete the result set object

        delete stmt; // Delete the statement object

        delete dbConn; // Delete the connection object

    }

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

    {

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

    }

    return 0;

}

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

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

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

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

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

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

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

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

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

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

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

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

The black box problem

   

The black box problem

When we see the black box, we see only the core of the thing. And the thing that is in the box remains a mystery before we open it. 

The black box problem is the thing that we know that there are bites in the box. We know that there is the possibility that there is a DVD. Or any other merchandise in the box. But we don't know what kind of merchandise or item is in that black box. The thing is that. We know what kind of merchandise we order or what should put in the box. There is the possibility that the deliverer has made mistake and sent the wrong box to the wrong place.

We know what should be in the box. But only the physical observation confirms the information. The fact is that we are just assuming the thing that should be in the box. We cannot be sure and confirm the information before we see what is in the box. 

We can predict that there is a certain thing. But we don't know what exactly is in the box. The "black box" testing means that only the functions of the computer program are tested. So there can be many mistakes and errors in the code. 

When we are thinking of the working day it's like a black box. Many things can happen during our day. But we don't know exactly what is happening when we are beginning our day. 

The useless information is the problem.

When we are thinking about the information that we need when we are ordering the things from the net we need to know the color or we need to know the material. But there is one thing that is ever imagined. That thing is what kind of surface that material has. 

What does the material or merchandise feel when we are taking it in hand? And of course, nobody mentioned how large the box is, where the sender packs the merchandise. The information that we get is what the merchandise looks like and what it should feel like? 

But that kind of data would not help us when we go to a shop and buy a box of coffee. That is an example of how specific the data we use is. The same data matrix that is used for ordering merchandise from the internet. Is useless when we are visiting the shop. 

And both of the data matrixes are useless when we are walking on the streets. We don't know anything about the price of the coffee packet. And the color of the skirt while we are crossing the zebra crossing. That is an example of how the information that we use is specific. 

The problem with information is that most information that we get during our lifetime is useless in everyday life. We never imagine how large databases we need. When we are making robots we must program every single action to that robot. 

When we are making a program for the robot that can walk on the streets and open the door the programmer must determine every action that is necessary for those actions. When the robot opens the door it must know how to turn the knob? And then, the robot should know should it push or pull the door. But here we are always, forgetting one thing. That is the power that the robot should use when it opens the door. If the robot uses too much power it will break the locks. 

We want to make robots for making our life easier. And those machines are planned to replace humans in simple, dangerous, and boring missions. But when we are thinking about the possibility to make a robot that helps us in everyday life. Those kinds of systems are quite complicated to make. 

Like hat cleans our house and goes shopping for us. We are facing one thing. Those kinds of systems are quite hard to make.  But when we are thinking about things like robots that are serving us in the future making those systems act safely is problematic. The paradox is this: we can make the artificial intelligence that can find exoplanets near other stars. And we can make a drone that can flight independently in the military area and avoid enemy fire. But we have problems making the robot that goes shop for us. 

The day is like a black box.

When we are making robots that are serving us in everyday actions. We are facing the so-called "black box" problem. That means there is a lot of things that can happen when a robot visits shopping. There can be a car that is parked to the route of the robot. And a robot must evade that object. There is the possibility that there is a zebra crossing where is no light. And in that case, the robot must estimate the distance to cars independently. 

Those things are the most usual things that are happening in everyday life. But then the robot can see the seizures and it should know how to act in that case. There is a lot of things that are happening and what could be happening in everyday life. And the greatest challenge for robots and AI makers is to create robots that can operate in normal life. Is harder to make a robot that can visit to shop for us, and clean our house than some kind of automatic killing machine. 

If that killing machine operates in a conflict zone it must know what the enemy vehicle or an armed person looks like and if the IFF signal of those targets will be red. That robot opens the fire. But when the robot must clean the house. It must follow many things like is there enough garbage bags and make reports of that thing. 

https://thoughtsaboutsuperpositions.blogspot.com/

Deep-learning networks are the ultimate tools.

"Most applications of deep learning use “convolutional” neural networks, in which the nodes of each layer are clustered, the clusters overlap, and each cluster feeds data to multiple nodes (orange and green) of the next layer. Credit: Jose-Luis Olivares/MIT"(1)

The deep-learning network is one of the most interesting things in machine learning. When we are talking about deep learning, we should describe what that term means. Deep learning means that the creature knows how to make something. But also the reason why that thing is done, and when it must do that thing. 

In the case of deep learning, the creature knows the background for some regulations. But the thing is that machine learning allows that the AI would collect data about everything from the internet. The system can simply copy-paste the texts from the homepages and then turn that text into speech. Learning new skills means that the system connects the databases to new entireties. 

So the deep learning means that the creature knows what to do when to do and where to do something. When we are thinking about deep learning from the point of view of artificial intelligence. We know that AI can make impressive things. Artificial intelligence can make things like movement series but the question is, does it know what it does? 

We all can make things like a series of movements and talk about many things. And we might know nothing about the things that we are talking about or doing. In the case of machine intelligence, deep learning means that the system records the actions like macros. 

For robots, the movement series are the macros that are turning to the movement series. When the robot sees the person who is injured that thing activates a series of movements. Whose mission is to save the life of that person. The thing that activates the movement series is the details like blood. Or something else that is stored in the memory of the computer. 

So the cameras of the robot are sending images to the computer. And if there is a match with the accidents that thing activates the help mode. The robot might ask "are you ok"? And if the person answers "hurts" or is quiet the robot would give first aid. If the person can talk the robot would ask what happened? If the injury is caused by violence. 

The robot would activate the protective mode. When the robot is searching criminals some details are activating the attack mode. Even if the robot seems like a human. It can use infrared and radar scanners. For searching things like firearms and knives. When the system detects a weapon. That thing activates the attack. The idea is that when the system detects some image. 

That image activates the workspace. The operation is quite similar to operating systems in which locking can open by using an image. In that kind of system, the image activates the movement series. And the thing is that those movement series are programmed similar way. Without depending. If those movement series meant for opening the door.

Or if they meant for the use of weapons. The programming of the movement series is always similar. If the robot uses a drill machine the image of the drill machine activates the program how to use that thing. And the same thing is useful in the cases that the robot must use any other tools or weapons. 

The robot can take the gun, but it can also have ultrasound or microwave systems or internal weapons like shogun in the hand bones of the artificial skeletons. The image of the gun is acting like a trigger that activates the attack mode. The thing is that the robot itself is a multipurpose machine. And the programming determines what it can do and what it cannot do. 

(1)https://scitechdaily.com/deep-learning-ai-explained-neural-networks/

Innovation and programming

When we are thinking about innovation. We must realize that there is needed financial support for that kind of thing. The world is full of ideas and many of them are turning to theoretical innovation. But then those things vanish because they are felt as "boring". Or they are giving benefits to nobody. Innovation is the next step from the idea. The idea is the thing that people are sometimes writing on a sticky note. 

But then the idea vanishes because the thing is that the person who got that thing is not to remember it. If we want to make something real, we need time and financial support for that thing. That means we should tell the supporters, what is the interest why they should support some project? The innovation and R&D processes are needed time. And when the prototype is starting to form that thing needs room. 

In the cases where the innovation is not involving physical forms. Like in computing or sharper saying, software development the only thing that is needed is time. Everybody can download the development software to the computer. 

Then that person can make code if the skills are high enough high. But that kind of development requires time. And every people in the world requires something to eat. 

When we want to make complicated artificial intelligence-based software. We need to have time and money to make that R&D process. Things like interesting computer games require complicated code. And the AI makes those games interesting. That thing eliminates the possibility that the virtual "robot enemies" are not coming all the time from the same points. That thing should keep the game interesting. 

But that kind of system requires complicated programming- and database structure. The test process for that kind of thing is not very simple. And that means the developers need the time and resources for making that thing well. If there are bugs in the codes, that means nobody buys programs. When we are thinking about artificial intelligence and quantum computers the quantum computer is the hardware. 

The most interesting hardware on the internet is quantum computers. The capacity of quantum computers is enormous. And the power of those systems is higher than any other computer in the world. 

The predicted power of full-scale quantum systems is a million times higher than all binary systems that are connected to the internet. And that thing means that all data security tools that are made before quantum computers will be broken in seconds. And that means all the data stored on the internet is unsecured. 

And the thing is that without perfectly working programs the quantum computers are useless. That is the thing that we must remember when we are making the new quantum computers. Those things are impressive, but also the computer programs and interfaces that are cooperating with quantum computers. And things like screens and other output devices are working perfectly. Without those programs the quantum computer is useless. 

The computer programs and operating systems are the "soul" of computers. The program is the thing that the computer should do and the operating system is the layer that translates the operands to the microprocessor. And that thing means that software development is a very important thing in the world of quantum computers. 

If programs and operating systems are not supporting quantum computers. Those systems are not so effective what they should be. Of course, quantum computers are offering real processor-based multitasking. 

Think of software development from the point of view of Windows is an interesting thing.  We must remember that the lowest layers of that operating system are made by using tools that do not exist anymore. That thing means that Windows requires updating that it can work with quantum systems. That thing means that the quantum systems should allow driving programs alone without the assistance of binary computers. 

Could somebody activate "ARTICHOKE"-programming by accident?

https://metsantarinoita.blogspot.com/

Kimmo Huosionmaa

In the movie "Manchurian candidate" the psychological specialists program the soldier to make assassinations by using simultaneous repeating infrasound, the medicines, and hypnosis. In the elder version, the trigger was the heart queen, and that launched the effect, what caused the assassination. Or it causes the "dance effect", what makes the human, who is targeted for the brainwashing take the gun and shoot the targeted person. And that process is called as "brainwashing". The "dance effect" causes because the trainer teaches the victim the "katas", series of movements, what can be very dangerous. That kind of things are learned in the martial arts like karate, and that makes those self-defense skills so effective.


In the most advanced method would the brainwasher can use also Virtual Reality for making anger in the person's mind. The anger reaction is called as "trigger", and it would make the person act violently against some other person. In the worst scenarios, those psychological operators might play some kind of police or even play the victims own family. In the VR-method the consequence would be lowered by using chemical stimulants, that the victim would not even realize about that suggestion. Also, the feet or arms can be numbed during that thing.


That suggestion method was tested in the "PROJECT ARTICHOKE", and even if those experiments were ended in 1970's somebody might have thought those methods to some private military corporation. In the real world of science, the scientist, who makes the invention can teach that methodology to other persons, who are so-called the field team. In this case, somebody can play some kind of newspaperman or some activist and then ask about the methodology, what was used in ARTICHOKE-program.


The suggestion is the most attractive method when somebody would be wanted to give money to some other person. In this case, the methodology, what have been used in those mind control programs are using in the normal criminal activities. The trigger, what is used to make person murder, might use to suggest other people get the money to somebody else. But in fact, somebody has been targeted for that kind of brainwashing in "PROJECT ARTICHOKE", and if the trigger is the number 666 in the receipt, would the result be very devastating.

Difference between killer- and an industrial robot is only in their programming.

(Picture I)

Kimmo Huosionmaa

In the real world, we all want to say "no" to autonomous combat robots, what might be the greatest threat for peace today. The artificial intelligence makes possible to make robots, what are looking innocent, and they can be used in some normal work, but when they would see the targeted object, what have ordered to exterminate those robots would attack that target immediately. In this case let's say as an example the gardener robot would noticed something treating, that robot can be transforming as the combat robot, and maybe in that robot's arms is hired machine guns or laser weapons, and when something, what is ordered to exterminate would come in sight, would the wrist turn down, and uncover the nasty surprise.


This example, what I just gave, is one of the most feared things in the world of robotics. It is known as the "ghost protocol", and that means that normally the peaceful working robot would turn to combat robot, when it notices the target, what is dangerous for it or it masters. When some nation would say "no" to killer robots, they have forgotten that only programming would make difference between peaceful and the killer robot.  And in the real situation, the operators of the robots would just upload combat programs in those working robots by using the Internet. And this means that there is a change, to make the full army of robots in seconds by using industrial robots, what are equipped with those combat programs.


The Russians are always against this kind of programs because they have no experience in building the sophisticated robots, but their way to make new nuclear missiles authorizes Western world to make autonomous killer robots. And this is the problem with robotics, the same machine can do many missions, like working in the mining sites and other dirty and dangerous places. If the robots are made looking like humans, they could use same tools as humans, but in this case "one model fits all" can get the notorious shape because those human-shaped robots can also be used as the warriors because they can operate with normal infantry weapons. And the use of those weapons is needs only the program update, that those robots could transfer as the combat models in one second, by sending those programs by using the Internet.

Sources:

https://futurism.com/germany-pledges-not-killer-robots/

https://www.defenseone.com/threats/2014/08/top-six-strategic-threats-worry-about-todays-global-headlines/92000/

https://www.digitaltrends.com/cool-tech/un-told-to-ban-killer-robots-before-they-become-a-reality/

Picture I

https://cdn.defenseone.com/media/img/upload/2014/08/20/shutterstock_190737419/medium.jpg

The speed of the supercomputer is not alone made ultimate computing.

(Picture 1)

Kimmo Huosionmaa

Problem with the quantum computer is not only in building the new kind of microchip. Another problem is to create the program or operating system, what can use all power of the supercomputer. And one solution would be used multi-layer kernel, where the top layer is normal Windows or Linux layer, and that layer communicates with processor thru the lower layer, what is specially designed for those ultimate processors.


The speed of microprocessors is not the only thing, what makes the ultimate computing and ability to make the sharp and powerful simulation. Another important thing is that the programs can communicate and control that electric equipment. In the production of microchips might use nanotechnology, what allows to make the three-atom size of transistors. In those transistors, the foot, collector, and emitter are made of the single atom.


And the super fast computers can also cool to the temperature where it turns to superconducting. It would give it ultimate clock frequency because that superconductor would eliminate the heating of the processor. But then the temperature must be near absolute zero-point or zero Kelvin temperature. Those ultra small and fast components need also new kind of kernels.


This means that if the computer programs and kernel, what makes the layer, where computer microchips are communicating with computer software have no ability to drive computer with full speed, or is not otherwise capable to exploit the full power of those computers, the superfast computers are useless. This is one of the greatest problems with the creating the quantum computer.


There are no programs, what can exploit the capacity of this new kind of supercomputer. One version to solve that problem is to make multilayer kernel, where the top layer is normal Windows or Linux kernel, what would control the lower layer of the kernel. This lower layer of the kernel would be made for communicating with that quantum processor. That would be one solution for that ultra-fast computer.


The ultra-fast computers are needed also in everyday computing because mobile solutions use so-called pre-processed computing, where all calculations happen in the server. This allows making the mobile systems, where are the long-term batteries. The mobile computers like tablets are usually quite weak processors. The calculations must do in somewhere, and those process would happen in the memory of central computers. But the servers must have powerful processors. And this would raise the need to develop the new kind of extreme fast computers, what can be used also for code-breaking.

Sources:

http://www.wired.co.uk/article/quantum-computing-explained

https://thestack.com/data-centre/2017/12/15/australian-engineers-design-silicon-based-quantum-chip/

Picture 1:

http://www.newequipment.com/sites/newequipment.com/files/styles/article_featured_standard/public/brain-quantum-computing-1620.jpg?itok=DQ7rP_xZ

The dance of robots

Kimmo Huosionmaa

The modern way to teach robots is not similar than making programs. It could be like teaching children. In this scenario, the programmer would take the robot by hand, and then make the movement of robot’s hand with it. After this, the system will record the movements, what are needed to take the example the glass from the table. But how to teach the robot to dance. This is the question of the week.


 And there is needed the dancer, whose character would be digitized by using laser-scanners. Then the movements of this character would be transmitted in the robot’s digital mind. After this, the robot’s computers would control it’s hydraulics like the way, that the robot makes dance movements. This is the very effective way to teach the things to robots, and the same way we can teach the language to the computer. There would be a dictionary book in the memory of this machine, and then we are starting to talk to the system.


First, we must write the answers to the computer, but when we are asked many questions, and wrote enough answers, the computer starts to work more and more independently. In this program might be three layers of answers. The first answer could be the text, what is written by the user, but when the computer learns more words, that would ask only if the answer is correct. This computer would record the questions and compile it with answers, and then compile those answers in many other things, what are involved with similar actions.


Then the robot is asked to bring the milk to the table, would the action be first, that the programmer would take the robot to the freezer, and then the robot would take the milk bottle. But when the programmer asks to bring the screwdriver, would the computer or robot uses same actions when it used in the case of the milk bottle. But now it must find that thing from somewhere else. So it starts to open the doors of lockers, and look for the things, what looks like the screwdriver.


For this action, the robot needs the picture of the screwdriver. After that robot compiles the picture in its memory to the real situation. The system, what is used in Digital Scene Matching Area Correlation can also compile the shape of the other things, and that would make those machines more independently than ever before. The bases of learning are the ability to make networks with words and actions.


And the first things in this process are the most difficult. When the first world and the action for it are made, the robot, what is controlled by speech comes near to us, by step by step. This network would give the opportunity to make the robot, what learns things itself. And this kind of robots might be dangerous in wrong hands. In real life, robots might have access to Internet dictionaries, and they can compile the orders to the databases. In this case, the robot would get orders to get the spoon.

Then robot would find what to do if it is given the order of getting something and then look for the spoon from the Internet. This makes robot easier to learn everything. And in real case robot could find the orders to use some equipment from the Internet, and in this case that could make robot very dangerous, because the programmers don’t know, what robot have been learned. In the case of robotics, the extremely important thing is to control what robot can do. There would be robot what have learned city warfare tactics and knowledge of using weapons without that the programmers even know about this, will the situation became very dangerous. Self-learning brings the uncontrollable element to tests, and this might even cost human lives.