The Intelligence Age: A Story of Evolution
Before the Industrial Revolution, if you wanted power, you needed to build by a river, or own a horse.
So when the steam engine appeared on the scene, power suddenly became available everywhere, cheaper and easier to use than ever before. Industries flocked to ride the new wave, and it changed industry and the landscape itself, forever.
James Watt understood this better than anyone. He didn't just sell engines — he rented them, charging his customers a fraction of the savings they gained from retiring their horses. That commercial insight gave us the term “horsepower” — a measure born not from a stable, but from a brilliant business model. The lesson was clear: those who harnessed cheap power reshaped the world. And they got rich doing it.
Since the invention of clay tablets, humans have been storing thoughts and memories as data. World War II saw the culmination of these manual data systems, in which buildings full of women and men called “computers” processed through mountains of data on paper sheets. When IBM started deploying servers and electronic data systems, it made access to data hundreds of times cheaper.
Where the steam engine made power portable, the database made information instantly accessible. A search that once took weeks of manual effort could now be completed in seconds. Data was no longer a physical burden to be hauled and filed — it was a digital asset that could be queried, sorted, and recombined at will.
Herman Hollerith understood this principle long before the electronic age. Tasked with processing the 1890 U.S. Census, he invented a punched-card tabulating machine that completed the job in one-third the time — and saved the government millions of dollars. His company later merged into what would become IBM. The lesson was clear: those who could capture, organize, and retrieve data faster than their competitors would shape the world. And they did.
We now stand at the dawn of the Intelligence Age.
Just as the steam engine made power portable and the database made information instant, the large language model has made intelligence accessible to anyone. A task that once required years of training — drafting a contract, analyzing a dataset, writing software — can now be accomplished in minutes with a prompt. Intelligence is no longer a scarce human resource; it is a commodity that can be summoned, scaled, and directed at will.
Alan Turing understood this before the first AI program ran. In 1950, he proposed what he called the “imitation game” — now known as the Turing Test — and predicted that machines would one day think. The establishment dismissed him; few could imagine intelligence outside a human mind. But Turing saw that if a machine could process information the way a mind does, the implications would rival the steam engine or the computer itself. The lesson of our own age is becoming clear: those who harness artificial intelligence — who build systems that learn, reason, and decide — will solve problems we once thought unsolvable. And that future is being built right now.