A hackmeeting, many years ago. A conference on various open-source projects. They were talking about Kiwix. The audience seemed interested, nodding, asking questions. I sat in the back of the room with a doubt that seemed legitimate but that I didn't dare express out loud: “what's the point of offline Wikipedia?” I mean: the internet is everywhere. If you need to look something up on Wikipedia, you open your browser, search, read. Done. Why would anyone download gigabytes of data to consult an encyclopedia offline? It seemed like a solution in search of a problem. Something for nerds nostalgic for CD-ROM encyclopedias.

It took me years to understand how naive I'd been.

There's a moment in the history of technology when everything changes. We don't always recognise it. Sometimes it takes years to understand that a small spark, an apparently insignificant detail, ignited a revolution that would forever change the way we live, communicate, and consume culture. In 1987, an American singer-songwriter named Suzanne Vega released a minimalist track called “Tom's Diner”. Two minutes and nine seconds of a cappella vocals, no instrumental accompaniment, no special effects. Just a voice telling the story of an ordinary morning in a New York diner. A song so essential, so pure in its simplicity, that someone on the other side of the world – a German engineer obsessed with #audio compression – would use it as a benchmark to create a technology that would shake the global music industry to its core. That technology was called #MP3. And that voice, that “warm a cappella voice” as Karlheinz Brandenburg would later describe it, would become the ultimate test to determine whether a compression algorithm actually worked or not.

When the world woke up astonished in November 2022 to this “magical” chatbot, few realized that this magic was the result of decades of research. The history of artificial intelligence begins in 1943, when Warren McCulloch and Walter Pitts proposed the first mathematical model of an artificial neuron. In 1956, at the Dartmouth Conference, John McCarthy coined the term “Artificial Intelligence” and the discipline was officially born.

The '60s and '70s were characterized by excessive optimism: people thought strong AI was just around the corner. Two “AI winters” followed – periods when funding disappeared and research slowed – because promises weren't materializing. But some continued working in the shadows. Geoffrey Hinton, Yann LeCun, Yoshua Bengio – those we now call the “godfathers of deep learning” – continued their studies on neural networks when no one believed in them anymore.