how the artificial intelligence works

how the artificial intelligence works
Photo by Pavel Danilyuk from Pexels

Artificial intelligence is making more headlines every day. have you ever thought that how the artificial intelligence works? Artificial intelligence or artificial intelligence is a technology that enables machines to learn from their own experience and perform tasks similar to humans. Utopianists and dystopianists have very different opinions on current and future applications, or worse consequences. If there is no suitable anchor point, our minds will linger in the Hollywood waters full of robotic revolutions and self-driving cars, and we know little about the actual operation of artificial intelligence. This is mainly because artificial intelligence itself describes various technologies that enable machines to learn intelligently. In our next series of blog posts, we hope to learn a little about these technologies and clarify what makes artificial intelligence really smart.


 Application of intelligence? 

A common misconception tends to place AI on an island of robots and self-driving cars. Proach does not recognize the main practical application of artificial intelligence; it processes the massive amounts of data generated every day. Due to the strategic application of artificial intelligence in certain processes, information is collected and tasks are performed automatically at an unimaginable speed and scale.By analyzing large amounts of human-generated data, artificial intelligence systems perform intelligent searches, interpret text and images to discover patterns in complex data, and then take actions based on the acquired knowledge. 


What are the main components of artificial intelligence? 

Many revolutionary artificial intelligence technologies are common buzzwords, such as natural language processing, deep learning, and predictive analysis. Advanced technology enables computer systems to understand the meaning of human language, learn from experience and make corresponding predictions. Understanding the terminology of artificial intelligence is key to discussing the application of this technology in the real world. Technology is revolutionizing the way people interact with data and make decisions, and we should all understand this broadly. 


Machine Learning 

 Learning by Doing Machine learning or machine learning is an application of artificial intelligence that enables computer systems to automatically learn from experience and improve themselves without explicit programming. ML focuses on developing algorithms that can analyze data and make predictions. To predict which Netflix movies you might like or the best route to take Uber, machine learning is used in the health, pharmaceutical, and life science industries to diagnose diseases, interpret medical images, and accelerate drug development.


Deep learning | Self-taught machine

Deep learning is a type of machine learning that uses artificial neural networks that learn by processing data. The artificial neural network imitates the biological neural network in the human brain. Multi-layer artificial neural networks work together to determine the output from multiple inputs. For example, recognize face images from mosaic mosaics. Machines learn through positive and negative reinforcement of the tasks they are performing, which requires constant editing and reinforcement to move forward. Another form of deep learning is speech recognition. The assistant on the mobile phone can understand things like "Hey Siri, 


how does artificial intelligence work?| Neural network|Building correlation neural network to provide deep learning

As mentioned earlier, neural network is a computer model of a system based on the connection of human brain nerves. Human nerves The artificial equivalent of yuan is the perceptron.Just as an array of neurons creates a neural network in the brain, a stack of perceptrons creates an artificial neural network in a computer system. 


                 Video by Yaroslav Shuraev from Pexels


Train the neural network by processing training examples

The best example is a large data set, such as a set of 1,000 cat photos. By processing multiple images (input data), the machine can provide a result to answer the question, "Is the image a cat? In this process, the data is analyzed multiple times to find the association and give meaning to various overlapping learning paths." Models such as reinforcement tell the machine that it has correctly identified an object.

 It is concluded from the context that cognitive computing is another important part of artificial intelligence. Its purpose is to simulate and improve the interaction between humans and machines. 

Cognitive computing attempts to The reconstruction of human thought processes in computer models, in this case, is an understanding of the meaning of human language and images.

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