How machine learning is powering our next generations?
Artificial intelligence in general terms refers to software or computer programs that allow a machine or robot to work. There are two major types of artificial intelligence: Machine Learning and Deep Learning. Both of these types of software have specific computer instructions called "algorithms". Machine learning software processes the data provided, takes instructions from it, and thus performs its responsibilities. For example, a robot has been given the software to clean a room. Since it will only clean the room and it doesn't have the ability to work.
Deep learning software has more complex algorithmic instructions. They look like a network of nerves in the human brain. That's why this software is also called "Artificial Neural Network". These are advanced and sophisticated. Their advantage is that they can "learn" new things by processing the data provided.
This means that the software is also somewhat independent and free. They learn new things with the help of new data, just as a growing child learns to do new things from the environment. It is as if the technology of deep learning is capable of inventing such a machine. It can learn new things from the data obtained like a child. It is an amazing and revolutionary invention.
The earliest computer software was invented seventy-eighty years ago. In the 1970s, experts from American companies, IBM, Microsoft, Oracle, etc. began to create general use software. Gradually more innovations came into this field and powerful software came into being. After 2000, colorful computer programs began to be created and the Internet delivered them from house to house. For example, bitcoin is a software that introduced digital currency. When this software came into existence, the value of bitcoin was zero. Today a bitcoin is worth thousands of dollars.
Only after 2000 experts start trying to create deep learning software. In 2014, they finally succeeded in inventing the first such revolutionary software. For the last nine years, scientists around the world have been developing such deep learning software that can mimic the human brain as much as possible in theory and practice. Their goal is to create a deep learning software that is similar to the human brain in every way.
Deep learning software is still making human tasks easier in many fields. For example, computer programs have been invented that are capable of listening to commands and performing them. This ability was given to them by deep learning technology. Cameras installed in self-driving cars have the same technology. With the help of these cameras, cars were able to run without a driver. Tick tock software, a popular Chinese app for children and adults, has been developed with deep learning technology. The technology is also helping medical professionals create new medicines.
Experts say that in the coming years, more efficient and better software for deep learning will be developed. It is very possible that after ten years, this technology will be able to create new software. It is as if then machines will start making software for human beings. Even at this stage, human beings will be involved in some process. This change will be revolutionary anyway because the software created by machines will be more excellent and sophisticated. But the downside is that this process will make many experts unemployed. However, one idea is that more new fields of computer science will be created at that time. Therefore, experts will be able to become associated with them.
Scientists have dubbed machine-made software "2.0". The software that man-made software is now called "1.0". One of the features of deep learning software is that they use a lot of electricity. As a result, they will not work in countries where there is a shortage of electricity. However, these software are becoming increasingly popular in rich western countries. There, these are being installed in everyday items to make them more efficient. It is thought that the value of this sector in the western world will reach "twenty billion dollars".
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