Artificial neural network

The artificial neural network today they are the protagonists, or at least the co-protagonists, of a fast and technological evolution that can really change the lives of many people in various fields. Medical, economic, cultural and social. Let's see what lies at the basis of many devices or algorithms already in use today, the artificial neural network often works invisibly and we don't even know much how until we go and study it.

Artificial neural network

It is not as recent as one might imagine, the first theoretical model of a rudimentary artificial neuron, because it dates back to 1943. Two scientists, McCulloch and Pitts, set out to create an apparatus capable of receiving n binary input data in each of its elements to output a single data each.

Such a device could work on elementary Boolean functions but also on other types of functions and mechanisms, this meant that the idea became an object of interest in the following years and still is.

Neural network and artificial intelligence

Just the neural network and the artificial neural circuits that it compose they are the basis of many artificial intelligence realities. Especially in recent years, they have evolved to resemble the human mind more and more every day, something that scares some people, fascinates others. However, it is difficult to remain indifferent.

Faced with problems of various categories, the neural network and forms of artificial intelligence who go to form are able to find solutions as if they were a human brain or almost, the differences are less and less.

It also happens that, thanks to these networks, we come to identify solutions that alone, we and our neural network, would not even dream of. The evolution, still ongoing, of neural networks and machines with artificial intelligence, has changed the way of operating in many sectors by revolutionizing them and making us all step forward. I am thinking of the medical sector but not only that, just look around to take note of how much artificial intelligence is applied everywhere.

In humans neural networks are part of the brain who is able to understand the environment and its changes, providing adaptive responses calibrated from time to time. From the biological point of view, they are formed by a set of interconnected nerve cells, inside them there are different entities such as neuronal somes, ie the bodies of neurons, which receive and process information, neurotransmitters, responsible for modulating nerve impulses, the axons, communication workers out of a neuron, and dendrites, communication workers in

In the human brain they also happen many synapses that serve for the passage of information between neurons, their number depends on the stimuli that the neural network receives, the more the more synapses occur. Artificial ones also behave similarly. Among the many neurons perhaps the most famous are quelli mirror

Neural network: advantages

The advantages of neural networks are numerous although there are still those who are perplexed about their use and above all aboutUse of artificial intelligence. Meanwhile, let's see some "pros": neural networks can process large amounts of data relatively quickly and do not break down often, they have the ability to operate despite receiving inaccurate or incomplete inputs.

There are also some areas in which artificial neural networks are more essential that in others, I refer for example to data mining, to the processes of optimization or the development of predictive and simulation models. The beauty is that a neural network can become capable of self-updating in the presence of environmental changes.

Neural network: limits

There are also limits, at least for now, that they make the artificial neural network, a little human. For example, they are a sort of black box, their computation cannot be fully analyzed and the individual stages cannot be examined step by step. When using these networks, it is not certain that a solution will be found and, when we get some outputs, we must take into account that they are not the perfect solution.

The neural networks are the foundation of learning devices but there are occasions when they do it with worse rhythms than those of the most donkey schoolboy in the class, then there are occasions when even neural networks have to throw in the towel because they are not suitable for solving certain categories of problems.

Neural network: example

A very interesting book, which also explains the algorithms that hide behind our searches on Google, Amazon and Netflix, is "The definitive algorithm. The machine that learns by itself is the future of our world". It can also be found online and it is a volume that makes us reflect on when artificial intelligence is the basis of many objects that simplify our life in daily use.

Neural network: applications

Sectors more than others are pervaded by these innovations, in others it is almost absent. Finance uses them very often and increasingly, to make forecasts on market trends and to assess credit risk, for example.

Image recognition and speech recognition are also based on neural networks, also used for simulating biological systems and for making medical diagnoses, including CT and MRI reports. Always recently we find artificial intelligence used for quality control on an industrial scale and for data mining, as well as for simulations of various kinds.

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Video: What is a Neural Network. Neural Networks Explained in 7 Minutes. Edureka (December 2021).