Neural networks – Is computing capable of imitating the functioning of the human brain and, with that, can it increase its processing potential ? This is the premise behind a neural network, an almost century-old concept, but one that has never been in such evidence as it is today.
To understand how neural networks work, first of all we need to understand how the connection between information takes place in our own brain.
From this opens up an invaluable potential for technological advances, but many of them are still in the field of theory.
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Neural networks: an invention of almost a century
The first concepts of neural network were established in 1943 by researchers Warren McCulloch and Walter Pitts. In an article, they made an analogy to the functioning of neurons in the brain and, based on this concept, indicated the creation of a neural network with electronic circuits.
The understanding of these mechanisms made possible the development of research, until in the 70s Kunihiko Fukushima established the first multilayer neural network. These principles were the starting point for the development of technologies such as artificial intelligence and deep learning.
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What is neural networks and what are they for?
What is the advantage of simulating the functioning of a human brain with circuits or programming language? The complexity of the possible operations to be performed is the key to this answer. The way information is structured in our brain is different from how it is on computers.
When working with an immense volume of data, crossing them to define standards, machines “suffer” if they follow lines of operation similar to those they use today. Neural networks come into play to minimize this problem and enhance the possibilities.
Some sectors that have been using neural network techniques in their services include credit card fraud detection, transportation logistics and quality control and processes.
The proposal is to predict occurrences beyond logic, which allows computers to go beyond their processing capacity.
Deep learning: a revolution based on neural systems
You have certainly heard of the term deep learning . It is an expression in English that, translated into Portuguese, would be something like “deep learning”. In practice, we speak of a branch of machine learning systems.
In this sense, computers “learn” to “learn alone”. Based on the feeding of a database, the machines create patterns, each time more exact, when making connections between the most varied elements. This is how, for example, your operating system comes to understand the context of a conversation.
For example: by saying “what will be the temperature tomorrow in USA” you are giving a direct order to the cell phone – and it is easy for the operating system to perform this action and display the answer.
However, when you say “temperature tomorrow”, the system must first understand where you are. From the context – your location – he implies that this is the temperature tomorrow where you are.
This simple example illustrates well the advance that artificial intelligence systems have brought to users.
Today, it is possible to talk with a computer or a cell phone in natural language, that is, as if we were talking to another person, something that was practically impossible in the past, given the amount of calculations necessary to arrive at these answers.
An infinite world of possibilities
From the development of deep learning, a practically infinite world of possibilities opens up. Connected cars able to move around automatically and avoid accidents, smarter systems capable of spontaneously crossing data and predicting the most viable alternatives are just some of the possibilities.
However, as much as advances are continuous, responses will always be based on the functioning of the human brain. Our brain structure is so complex that it is still unknown exactly how it works.
However, the more scientists get deeper into the research, the more incredible the results seem.
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