📝 Summary Artificial neural networks, a family of ideas developed over 80 years, are the unsung hero behind current AI technologies such as ChatGPT, image generators, and voice assistants. These networks learn patterns from data and have been the core engine behind many AI systems, despite being largely invisible to the public. When people say “AI” today, many of them are thinking about ChatGPT, image generators, voice assistants, translation tools, coding copilots, or systems that can summarise documents in seconds. These tools feel new, powerful and sometimes mysterious. Yet the main engine inside many of them is not a sudden invention from 2022. It is a family of ideas that has been growing, failing, returning and improving for more than 80 years: the artificial neural network. This is why neural networks deserve to be called the unsung heroes of the current artificial intelligence (AI) revolution. The public sees the chatbot. The public sees the generated image. The public sees the smart search result. But behind the screen, the modern AI system usually depends on layers of artificial “neurons” learning patterns from data. Before ChatGPT, “AI” meant many things It is essential to remember that AI did not always refer to neural-network-based systems. Before the ChatGPT phenomenon at the end of 2022, AI was a broad umbrella. It included expert systems that used human-written rules, symbolic programming in languages such as LISP, fuzzy logic, image processing and recognition, search and planning, robotics, and optimisation techniques inspired by nature, such as genetic algorithms, ant colony optimisation, particle swarm optimisation and many others. All of these belonged to the larger story of AI: the attempt to make machines perform tasks that normally require human intelligence. But after ChatGPT became a global sensation, the popular meaning of AI changed. For many people, “AI” now