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10 months ago (28/01/22) 514 Views

Machines of the future more intelligent than humans


In the future, machines will be more intelligent than humans? Find out the details


One big breakthrough in machine learning would be the equivalent of ten Microsoft. It’s not about me, it’s about Bill Gates.


And today we will talk about this technology. Many people may have heard the name of this technology. Again many may not have heard, but you are using it unknowingly but you do not know what is this machine learning technology? Will the effects of this technology add value and benefits to society as a whole? Today we will discuss. I hope you like today’s article.

Machines of the future more intelligent than humans

Machine learning technology has been working successfully for many years and at the same time creating all the powerful applications. Friends, we are all unknowingly using machine learning technology but not many of us know about it. For example, Google‘s Allo application, or Apple‘s iMassage, Google Photos app, Virtual Assistants, etc.


Friends, our computers are helping to analyze space-based calculations in seconds. A computer can easily solve any problem at the speed of light. But even then we do not consider computers to be “intelligent” because traditional computers cannot do anything on their own, unless a program is included in the computer.


that case, if we want to teach a computer like our brain so that it can be as intelligent as us. This means that if human intelligence, emotions, techniques can be taught to a computer, then that is machine learning. A computer can never understand anything. This is possible only with the help of machine learning.


The places where machine learning is being applied at present are like web search, computational biology, finance, e-commerce, space exploration, robotics, information extraction, social networks, etc.


Friends, first of all, why do we need machine learning? For example, it is not possible for a human being to sit outside the earth before. But at the present time people can easily go out of the world, but as a supporting material, such as oxygen cylinders, foods, technical accessories, etc. have to be sent, which is very costly and time consuming. In that case, scientists thought, what kind of machine can be developed? Who can achieve thinking capability like a human being? This means that a machine can do exactly what a human being can do!


For example, before we used to copy using carbon paper. But nowadays that manual system or (handwritten method) has been converted to photocopy machine. Machine learning is the act of enabling a computer to build capability at that very moment.


Friends, the most important thing about machine learning is that this technology allows the machine to change its solution with the calculation of time. For example, a game of chess is a program in which a machine decides a new movement on a single experience basis each step.

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Now think about it, Google’s Allo application, Apple’s iMassage, mobile phone will read the full screen and tell you what you are writing very easily. Let’s say again, about the Google Now Tap application. If you go to your phone and tap on Google Now, Google Now will scan your phone screen and tell you what you are working on and Apple ‘s Siri, Windows Cortana are all successful applications of machine learning. After uploading the image to Facebook, it automatically detects the car’s image. All of this is the result of the use of machine learning.


Let’s say in a little detail, when you do a search on Google, for example, if you search for a mobile phone which is between Rs. Suppose again that the sensor used to reverse a car is machine learning based.


Machine learning is a kind of Artificial Intelligence (AI). Which provides the computer to develop learning capabilities without any programming, for example, if you perform a task with a computer, where you do not have to write any programming code.


Let me explain a little. Suppose you write a programming code and if you enter any new data input inside that code, then the machine will be able to change that algorithm automatically. And what we call developing this programming is machine learning.


Machine learning technology is very different from traditional programming. For example, in the case of traditional programming, the programming that was done through the computer meant that the program that was written or the input that was taken gave the output through the computer.


But in the case of machine learning I give my machine some data and output (which we want to see). And computers give us programs based on this data and output. This means that we are giving data as well as output. And this is programming of machine learning.


Let’s give another example. Suppose you type in a Google search box or something like “machine learning algorithm”. Which will show you that relevant data.


Now let’s look at how the human brain and computer work. If you want to watch a movie on your computer, click on the place where you have placed the movie. And that command immediately goes to CPU and where you put the movie means hard disk drive, it will find and display you from there.

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So we know that a computer has a hard disk, where data is stored or where there is a processor unit, calculations are done. Again there is a display area. Where, takes input or gives output. And that’s exactly what our brains can do.


Suppose a person remembers his past. That’s why we hold it, hard disk. Again, a person can do calculations. That means we have the CPU to handle the processing power. After that we can tell the result with our mouth. Or we can write it by hand. We can hold it on the display.


Then it is understood that the human brain and a computer can be considered the same. But one of the biggest gaps between the human brain and the computer is learning capacity or thinking power. The way our brains are made to learn or think or perceive emotions. Let’s take a small test.

If I say that the height of the jackfruit tree is equal to that of the mango tree and the height of the mango tree is equal to that of the litchi tree, then at that moment you will immediately say that the height of the jackfruit tree is equal to that of the litchi tree. But I did not say that the height of the jackfruit tree is equal to that of the litchi tree. But you think the jackfruit tree and the litchi tree are the same! You are right! There is an argument in this! Is that so? This is exactly how people learn. Which we don’t know before but we have to learn.


Now if we want to teach the machine something, then the machine has to acquire the ability to learn like a human being. That means learning power must be included in the processor of the computer. And once the learning power can be included, then that machine can be converted into a learning machine. It is a very small task. But scientists have figured out how to incorporate this learning power into machines. Then the scientists did an experiment. So what was that experiment?


The experiment that the scientists did was through pictures of 15 dogs. When scientists show a picture of a dog to a machine, the machine will save that picture immediately. Since scientists have included learning power. Therefore, that machine will create a data table or chart on its own.


Scientists again showed another ball to the same machine. Then the machine will save that image immediately. Since the learning capability in the machine is silo, the machine will create its own data table or chart. Let’s find out how a machine or robot can create data tables or charts.

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For example:


  1. Rule number 1 is not a dog round. But the ball is round.
  2. . Rule number 2 Dogs have ears. But the ball does not have ears.
  3. Rule 3 has a dog’s mouth. But the ball does not have a face.

This way a lot more data is included. Here I have briefly discussed.

Then after teaching everything, the scientists saw a ball in that machine and said what is it? Then the machine will apply all the rules and say it is a ball. Again if a picture of a dog is shown then the machine will analyze those rules and give output and tell it is a dog. Thus a robot has to build learning ability about the end number of objects.

Machine learning algorithms can be divided into four main categories.

  • Supervised Learning.
  •  Unsupervised learning.
  •  Semi-supervised learning.
  •  Reinforcement learning.

Supervised Learning: The program is trained on some pre-defined datasets.  Gives program decisions based on train data. This is supervised learning. Whether the mail is spam or not, this decision is based on some previous data. This is an example of supervised learning.

Unsupervised learning: Unsupervised learning program provides some data. The program makes decisions based on that data. There is such a basket of fruit. The program will divide different results into different categories, this is an example of unsupervised learning.


Semi-Supervised learning: Semi-  supervised learning is a combination of supervised and unsupervised.


Reinforcement learning:  How do we learn in childhood? If I feel good after doing something, I do it more. If I get hurt by doing something again, I don’t do it anymore. In reality, the way a person or an animal learns, the training is done in the same way in any program in Reinforcement Learning.


At present the use of machine learning is increasing day by day. Everyone is talking about this. We have seen machines fight with situations where it is impossible for humans to get around. In the future, our cars will be driven by artificial intelligence. Our work will be done by robots. In the days ahead, machine learning is going to bring a huge revolution.


Happy ending


If machine learning can be applied more efficiently, then our whole technology world will change. Not that not being tried. This sector is being developed regularly. We hope that successful application of machine learning will make our daily life easier, and yes, if you like this article, you must share it with your friends and stay with us by liking our page to get more technology related new articles and visit our website to read our old articles.


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