What is AI, Really? Part I
AI will change everything, but most people can’t explain what it actually is… This module has been created to demystify everything you heard and read about AI. After reading this, AI will no longer have secrets, and I personally hope that you will have the ability to report what you learn in this article and explain with passion to the people you are close to.
In this module, divided in two parts, the first of AI Mind, you will learn, of course, what is AI, but also what it is not AI. If you are new to this, be reassured, we won’t talk code or practise maths, as it is not the purpose of the topic of the day.
What AI is NOT!
Firstly, AI is not a robot that thinks like a human being. It has its own way of thinking, which will be uncovered later in this module.
Secondly, AI is not magical or all-knowing. Even further, AI has limits easily overtaken by the human brain. Also, AI is certainly not a threat from the future that looks to wipe out the entire human race, as imagined in numerous movies such as Terminator from James Cameron and released in 1984.
Beyond these popular beliefs, AI is not just for engineers or data scientists. It concerns us all and everybody uses AI most often, sometimes without being aware.
So, What is AI?
AI is the acronym for Artificial Intelligence; it was first introduced in 1956 during a conference held in Dartmouth, New Hampshire. At the time, the leader, John McCarthy, described AI as “the science and engineering of making intelligent machines”. The event is widely considered as the starting point of AI research over the world. Of course, AI existed before, but the conference’s goal was to name the new science field with a specific term to enforce collaboration over the world!
The definition of AI has evolved since then, and many people still disagree on a single, precise definition. Put simply, however, AI is a system that learns from data in order to perform tasks. These systems can either follow a predefined set of instructions created by humans, or they can automatically learn patterns from data in order to make decisions, adapt their behaviour and improve their performance over time.
A filter spam is an example of AI because it is trained to recognise an undesirable email.
In 2026, we distinguish three types of AI:
- Machine Learning: When AI learns from example
- Deep Learning : When AI learns from large amounts of data to identify potential connections;
- Generative AI : Generate content (text, image, code…).
AI in your daily life
AI is already deeply embedded in modern computing systems, often without us even realising it. As individuals, we interact with AI technologies every day, in subtle and invisible ways. For example, platforms like Netflix use AI-driven recommendation systems that analyse our viewing habits to suggest content tailored to our preferences.
As well, Google Maps uses traffic data to find the best itinerary for you to get to the destination. For this, AI analyses your style of driving and matches it data from the destination to calculate the perfect estimated time of arrival.
I’m sure you already knew, but ChatGPT’s technology is AI-driven. It collects data to give you the most appropriate answer to your initial demand.
In short, you already used AI, many times of day, mostly to generate personalised content according to your habits.
Key Takeaways
1. AI is not magic — it's maths and data AI isn't some mysterious intelligence. It's a system that learns from data to carry out specific tasks.
2. You already use AI every day Netflix, Google Maps, Gmail — AI is everywhere in your daily life, often without you realising it. It's not reserved for experts and tech specialists.
The Second part of the module is available here : https://aimind-ft.com/article/what-is-ai-really-part-II/