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What are the advantages? The main reason that neural networks are increasingly used for running and developing businesses is extremely simple. Artificial intelligence takes on the solution of many different tasks, thereby freeing people from routine.
What can it be used for? Neural networks can be useful in a variety of areas. They help establish contact with customers, predict consumer trends, generate content, increase targeting accuracy. And the list goes on.
The article explains:
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Options for achieving neural network scalability
Situations when a neural network is useless for business
Frequently asked questions about neural networks
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Algorithm of neural network operation
They are mathematical models that consist of artificial nerve cells connected in chains. Each of these neurons is an independent element that processes a specific input signal. Then it passes it on further along the chain. Together, the elements form a system that can perceive objects as a whole.
A neural network is capable of functioning according to a given algorithm or templates, memorizing information, learning independently, and generating reactions. Thus, it is a machine learning program that imitates the work of the human brain.
Algorithm of neural network operation
There are several levels at which these mathematical models operate:
Information entering the processing element is sent to other elements in the input layer.
All values and inputs are analyzed and then combined in the hidden layer.
The information is transformed into the desired result in the output layer.
Now let's look at two neural network models:
Semiotic. In this case, the neural network imitates human behavior. AI tries to be as similar to it as possible. Such models are often used to interact with clients.
Biological. The system is designed to perform a specific job. In this case, AI uses evolutionary algorithms, learns based on the experience gained.
Neural networks are also divided into:
Weak. Such systems are capable of solving only strictly defined tasks. For example, processing images, communicating with clients. A weak neural network can only learn within the framework of a given logic and algorithms. For example, if such AI is designed to process images, it will not be able to search for a target audience for a store.
Strong. These systems can solve even those tasks that they were not taught. At the moment, there are few strong neural networks. However, experts are confident that this type of artificial intelligence is the future. For example, the International Data Corporation company made a forecast according to which the volume of investments in the development of AI and neural networks by 2024 will amount to 110 billion dollars.
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Mathematical models can work with probabilities and draw conclusions within the information available to them. AI is trained on historical data. Thus, the accuracy of the neural network's response is affected by the quality and volume of information.
At the moment, neural networks are effective tools for working in various fields. Users interact with such systems every day without even noticing it. For example, voice assistants on the hotline, chat bots and many other programs are AI products.
AI can perform almost all tasks related to information analytics and content generation. However, it cannot do without a person, since someone must properly configure the neural network.
AI is used to automate routine tasks, reduce costs and advertising budgets, and reduce time costs.