If you think AI started with ChatGPT, you’ve been tricked by good marketing. The dream of machine intelligence is actually ancient—older than the internet, older than electricity, and maybe even older than your morning coffee addiction.
Humans have always been obsessed with creating something that can think for them. Ancient myths tell of mechanical servants forged by gods, of talking statues and self-playing instruments. The Greeks imagined automatons powered by steam; in the 13th century, engineers built water-driven clocks that could “decide” when to chime.
Fast-forward to the 1940s. The Second World War gave birth to code-breaking machines and mathematicians who wondered: if a machine can solve logic, can it think? Alan Turing said yes—and designed the test that still defines artificial intelligence today.
Then came the 1950s and 60s, when computers filled entire rooms and optimism filled the air. Scientists promised thinking robots by the year 2000. Spoiler: they didn’t quite make it. Funding dried up. AI entered its awkward teenage years—a period politely called the AI Winter.
But the idea didn’t die. In the 1990s and 2000s, faster chips and more data quietly resurrected the dream. Machines learned to play chess, translate languages, and drive cars. They stopped being clunky calculators and started resembling pattern-hungry brains.
Now, in the 2020s, machine intelligence writes poetry, paints pictures, and answers existential questions about itself. It’s not science fiction anymore—it’s Tuesday.
The truth is, AI’s “overnight success” was hundreds of years in the making. It’s less a revolution than an evolution of human curiosity—a story of people who never stopped asking, “Can we teach machines to think?”
And judging by the fact that an algorithm probably suggested this article to you, the answer is now officially yes.
Every time we teach a machine to think, we’re really teaching ourselves how to understand.
