We can say that we are part of a great cultural, social, and informational revolution. And this revolution has a name: artificial intelligence (AI). We are facing systems capable of reasoning, learning, and acting in ways that would normally require human intelligence.

But when can a machine be defined as "intelligent"? To understand what it means to define a machine as "intelligent," we need to go back to 1950, when the mathematician Alan Turing published his famous article, "Computing Machinery and Intelligence." In this pioneering paper, Turing proposed a test (now known as the "Turing Test"), in which he outlined four key characteristics a machine should possess to be considered intelligent:

- processing natural language;

- representing knowledge and storing information;

- reasoning automatically, using stored information to answer questions and draw new conclusions;

- learning autonomously, adapting to circumstances.

Artificial intelligence, therefore, originated as a branch of computer science, but from the very beginning, it has embraced multiple disciplines: statistics, hardware and software engineering, linguistics, neuroscience, philosophy, and psychology. In the years that followed, artificial intelligence made tremendous progress.

A key moment came in 2017, when Transformers were introduced — an architecture of neural networks that revolutionized the field of natural language processing (NLP). Unlike earlier models, such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM), which processed text one word at a time, Transformers allow machines to analyze an entire sentence simultaneously, greatly improving the ability to understand context.

But how can a machine learn human language in such a complex way? The answer lies in Large Language Models (LLMs), a subgroup of AI that relies on vast amounts of textual data to learn and understand natural language. These models are trained on billions of words and are capable of generating text, answering questions, translating languages, completing sentences, and much more.

However, the topic of artificial intelligence doesn't end with the technical aspects. There are ethical, legal, and psychological issues that are rapidly emerging: as a society, are we ready to distinguish truth from falsehood, the natural from the artificial? Will we be able to maintain conscious control over these complex systems? Will we, in turn, be careful to pay attention to the implications of AI, just as these machines do with our words?

After all, what makes us human? What makes us human is our subjective experience, our awareness of existence, our emotions, and our feelings. As AI continues to evolve, it will be crucial to maintain our commitment to growing not only technologically but also as human beings: striking a balance between progress and ethical reflection. And in this great revolution, the key will be to preserve what makes us truly unique.