What exactly is AI and how does it work? A jargon-free guide
When we hear the term “artificial intelligence” (AI), many of us imagine futuristic robots. However, the reality of AI is much more mundane. In fact, AI is present in numerous tools and services we use every day. In this guide, we’ll explain what AI is, what types of AI exist (narrow, general, generative), and in what fields it’s used, all without technical jargon.
What is artificial intelligence?
Simply put, artificial intelligence is the ability of a machine or program to perform tasks that would normally require human intelligence. In other words, these are computer systems designed to mimic human cognitive abilities such as learning, reasoning, or decision-making. AI simulates human intelligence: for example, it can recognize images, write poems, or make predictions based on data. This doesn’t mean that machines think exactly like us; rather, they follow algorithms (mathematical instructions) that allow them to solve problems or perform tasks autonomously.
However, that doesn’t mean that machines think for themselves or have consciousness. Although we use the word “intelligence,” an AI is actually composed of mathematical algorithms, not a living brain. Your phone doesn’t feel or understand like a person; it simply runs very sophisticated automatic processes to mimic certain human functions and give us useful answers.
How does AI work in simple terms?
The magic behind AI is actually based on a lot of math and data. Instead of just following predetermined instructions, an AI learns from experience. This learning is achieved through machine learning methods, where the system discovers patterns in large data sets and adjusts its behavior accordingly. We can think of it like educating a child: instead of giving it all the answers, we give it many examples so it can figure out the general rules on its own. In fact, instead of manually programming all the instructions to solve a problem (as was done with traditional software), in AI, the system is trained by showing it many examples until it learns how to perform the task on its own.
For example, in the past, for a computer to play chess, programmers had to manually enter the rules and strategies. Today, however, an AI can learn to play by analyzing thousands of games.
For example, smartphones can group your photos by theme (beach, party, etc.) thanks to AI. The system discovers patterns in the images because it was trained with so many examples. If you see enough “bicycle” pictures, you will eventually learn what a bicycle looks like and be able to distinguish it from other objects.
Types of artificial intelligence
Not all AI is the same. We can classify artificial intelligence into different categories, but a common division is between narrow (or limited) AI, general AI, and generative AI, each with distinct characteristics.
Narrow or limited artificial intelligence (weak AI)
Narrow AI is AI designed to perform a specific or very limited task. It’s the most common AI today: in fact, all current AI falls into this category. A virtual assistant, a spam filter, or a chess-playing program are all examples of narrow AI: each one was trained for a specific function and cannot go beyond that scope. These machines can even outperform a human at their specialized task (for example, an AI can beat the chess champion), but they don’t understand or do anything beyond what they were programmed or trained to do.
Artificial general intelligence (strong AI)
General AI refers to artificial intelligence capable of understanding or learning any intellectual task, similar to human intelligence. In theory, a general AI could reason, plan, and solve problems in multiple domains, not just one. To date, no such AI exists; all the intelligent machines we use are narrow. General AI is more of a science fiction concept (e.g., the near-human androids in movies), and while some experts believe it could be achieved in the future, it remains a distant ideal.
Generative artificial intelligence
Generative AI is a type of artificial intelligence designed to create original content rather than just analyzing existing data. For example, ChatGPT can generate text (such as answers or stories), and other AI models like DALL-E create original images from a given description. These models learn patterns from vast amounts of data (e.g., millions of sentences or images) and then compose something new based on those learned patterns. ChatGPT writes sentence by sentence, predicting what word should come next (similar to predictive text on your phone, but on a much larger scale), resulting in highly coherent responses.
In what areas is AI used?
In our daily lives, if you use a virtual assistant on your phone (like Siri, Alexa, or Google Assistant) and ask it a question with your voice, that system uses AI to understand your speech and find the best answer. Similarly, on social media, AI decides what content to show you: algorithms analyze your activity and show you content tailored to your interests. Furthermore, photo filters that allow you to add fun effects (like dog ears on Instagram) use computer vision techniques to recognize your face and superimpose those effects.
Another everyday area where AI shines is navigation and maps. Apps like Google Maps and Waze use artificial intelligence to analyze traffic in real time (based on millions of data points from other users and sensors) and find the best route.
In short, AI has become part of our daily lives, mimicking certain human capabilities to solve problems and make our lives easier. All current AI is narrow and is present in virtual assistants, digital maps, etc. The idea of general AI with human-level intelligence remains the stuff of science fiction. Recent generative AI demonstrates the creative potential of this technology, but ultimately, artificial intelligence remains a tool created by humans. Used responsibly, it can bring us great benefits and advancements in the future.