Artificial Intelligence: learn how it works.

Artificial intelligence is the ability of computer systems to perform tasks that would otherwise require human intelligence , such as recognizing patterns, making decisions, solving problems, and learning from experience.

It is an area of ​​computer science focused on creating machines capable of simulating human cognition.

The technology’s main objective is to develop solutions that operate autonomously and efficiently , promoting productivity gains and facilitating processes in various sectors.

Today, AI-based systems are present in business routines, mobile applications, service platforms, and even home devices, transforming the way people and organizations interact with the digital world.

Its recent impact is remarkable, but artificial intelligence is not exactly new.

The origins of AI date back to the 1950s, when researchers like Alan Turing and John McCarthy began exploring the idea of ​​“thinking” machines.

Since then, the field has evolved rapidly, driven by advances in computing power , data availability and algorithm development.

The history of artificial intelligence and its evolution shows how the technology has gone from theoretical experiments to concrete and indispensable applications.

With this trajectory, what artificial intelligence is has become a central theme in debates about innovation , ethics and the future of work, in addition to inspiring public policies and strategic investments around the world.

How does artificial intelligence work?

Artificial intelligence works by combining algorithms , large volumes of data and computing power.

Its operation involves steps such as data collection, processing, analysis and automated decision-making, imitating human cognitive processes.

The conceptual basis of AI lies in computer science , statistics and mathematics.

With this, systems are programmed to recognize patterns, make predictions and adapt over time.

Some of the basic concepts behind how it works are:

• Algorithms : sequences of logical instructions used to solve problems or perform specific tasks
• Machine Learning : technique that allows the system to learn from data, without the need for explicit programming
• Artificial neural networks : structures inspired by the human brain, used to recognize complex patterns
• Big Data : Large-scale data sets that feed AI systems.

Still regarding how AI works, it is important to say that it relies on different learning models.

They define how technology interprets data and improves its performance over time.

This includes:

• Supervised Learning : The system is trained with labeled data, learning from examples
• Unsupervised Learning : the system identifies patterns without the data being previously labeled
• Reinforcement Learning : AI learns through trial and error, receiving rewards or penalties
• Transfer Learning : using knowledge acquired in one task to solve new, similar problems.

These mechanisms give rise to technology and enable applications such as personalized recommendations, virtual assistants, medical diagnoses, among others.

That’s what makes a difference in your life, therefore.

Understanding how AI works also helps you understand the advantages and disadvantages of artificial intelligence in different contexts, as we’ll see later.

What is the concept of generative AI?

One of the most widespread applications of artificial intelligence recently is the so-called generative AIs .

They are so named because they are capable of not only answering questions, but also generating content in different formats .

Conceptually, generative AI is any technology in the form of a platform or application that can create content, including creative content.

We already mentioned two of them at the beginning of the text, ChatGPT and Gemini, platforms capable of creating texts and answering questions .

There are also generative AIs that can create images and videos, such as the Leonardo.ai platform , and that generate music, such as Soundful .

Further on, you’ll see practical examples of artificial intelligence in everyday life, including its generative model.

What are the technologies behind artificial intelligence?

A technology does not develop without others to support it .

In the wake of artificial intelligence, many solutions needed to be developed before we reached the level we are at today.

Since the 1940s, when Alan Turing propagated the concept, countless technologies have been added that have made AI what it is today.

In 1956, the Dartmouth Conference in Hanover, United States, launched artificial intelligence as an autonomous field of knowledge.

Since then, studies have intensified more and more, with emphasis on the last decade, in which other concepts, techniques and tools have given new impetus to this area.

Below, learn about some of the technologies that, combined, have led to AI developing on an unprecedented scale.

Machine Learning

An AI would not be an intelligence if it were not also capable of learning as new information is assimilated.

This process happens through Machine Learning techniques, in which machines are enabled to learn almost like humans.

It is true that this learning, although partly autonomous, always depends to some degree on people, even if the famous robots Ameca and Sophia “think” differently.

No matter how advanced AI is, it will always be linked to some type of programming , which is developed from the concept of Machine Learning.

Deep Learning

Phenomena like the robot Sophia are possible thanks to the applications of deep learning in the development of artificial intelligence and associated robotics.

They work according to the neural network model, a type of algorithm that simulates the structure of human neurons.

We will talk about them later.

Deep Learning is essential because, otherwise, the answers and solutions generated by AIs would quickly become outdated.

In other words, to provide relevant answers , machines also need to adapt to the challenges of their time, just like human beings.

This is only possible thanks to deep learning technology.

Natural Language Processing (NLP)

One of the most fascinating examples of artificial intelligence is the one that can decode human language .

This “miracle” is possible because Natural Language Processing (NLP) technology exists.

To achieve this, the machines are equipped with powerful Machine Learning and Deep Learning solutions, so that they can not only understand languages, but also perceive the nuances of each expression.

The latest version of ChatGPT, for example, can now perceive a person’s emotional state through tone and even tell stories with variations in tone of voice .

AI technologies developed with NLP represent a major advance, even improving accessibility for people with some type of physical limitation.