How artificial intelligence works

How artificial intelligence works
How does artificial intelligence work? (Image: Pexels)

Alan Turing wondered: can machines think? What makes “something” smart? See below, how artificial intelligence works , the science that aims to solve these questions with practical experiments that are helping humanity to take its next steps.

What is artificial intelligence?

The main limitation in defining artificial intelligence or AI simply as “building machines that are intelligent” is that it does not really explain what artificial intelligence is. What makes a machine smart?

AI is an interdisciplinary science with multiple approaches, but advances in learning and deep learning are creating a paradigm shift in virtually every sector of the technology industry.

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How does artificial intelligence work?

Contemporary AI authors, Stuart Russell and Peter Norvig, define the concept as “the study of agents that receive information and perceptions from the environment and perform actions”.

Currently, there are several techniques that are used to work with artificial intelligence. Depending on the application and the objective, some are more explored, but all can act in a complementary way.

Machine learning (learning by experience)

It is an AI application that provides computer systems with the ability to automatically learn and improve with experience, not being explicitly programmed. Machine learning focuses on developing algorithms that can analyze data and make predictions.

In addition to being used to predict which Netflix movies the user might like or the best route for an Uber car, machine learning is being applied to the healthcare, pharmaceutical and life sciences industries to aid in disease diagnosis, medical image interpretation and accelerate drug development.

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AI seeks to bring computers closer to the human intelligence standard (Image: Pixabay/Pexels)

Deep learning (self-taught machines)

Deep learning is a specific subpart of machine learning . Its big difference lies in employing artificial neural networks that learn by processing data. Artificial neural networks mimic the biological neural networks of the human brain.

Multiple layers of artificial neural networks work together to determine a single output from many inputs, for example identifying the image of a face in a mosaic of tiles.

Machines learn through positive and negative reinforcement of the tasks they perform, which requires constant processing to progress. It is the technique that leads to speech recognition.

Neural networks (making associations)

Neural networks enable deep learning . They are computer systems modeled after neural connections in the human brain. The artificial equivalent of a human neuron is a perceptron. Just as bundles of neurons create neural networks in the brain, stacks of perceptrons create artificial neural networks in computer systems.

This process analyzes data many times to find associations and give meaning to the undefined. Through different learning models, such as positive reinforcement, the machine learns that it has successfully identified the object.

Cognitive computing (context analysis)

Cognitive computing is another essential component of AI. Its goal is to mimic and improve the interaction between humans and machines. Cognitive computing seeks to recreate the human thought process in a computer model, specifically through understanding language and the meaning of images.

Together, cognitive computing and artificial intelligence work to give machines human-like behavior and information processing abilities.

Meta's new artificial intelligence can translate up to 200 languages

Artificial intelligence (Image: Pixabay

NLP (Natural Language Processing)

Natural Language Processing or NLP — in free translation, natural language processing — allows computers to interpret, recognize and produce human language and speech.

The purpose of the technology is to enable seamless interaction with the machines we use every day, teaching systems to understand human language in context and produce logical responses. A good example is real-time language translators like in Skype.

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Computer vision (“active” machine eyes)

Computer vision is a technique that implements deep learning and pattern identification to interpret the content of an image. The action is done among the most diverse types, including graphics, tables and images in PDF documents , as well as other texts and videos.

Computer vision is an integral field of artificial intelligence, allowing computers to identify, process and interpret visual data. They become more active in defining which data will be used for greater precision in the response. The medical sciences are the area of ​​greatest effectiveness of this technique — “clinical eyes”, we might say.

Artificial intelligence addresses, so far, all these sets of specific techniques that may or may not add forces to expand its functionality. Each aspect is so rich, it would be possible to make individual posts.

Benedict Onyeka

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