Elon Musk recently predicted the end of the smartphone. “In five or six years,” he said, “we won’t have phones in the traditional sense. What we call a phone will really be an AI edge node — no apps, no OS, just AI.” It’s easy to dismiss such statements as provocation, but he may be right for reasons that have nothing to do with hardware or his views on the mass adoption of AI-generated content.

Every technology revolution offers a brief window of unreasonable advantage—an era when the bold can seize opportunities that later become ordinary. This is that moment for AI. The cost of cognition is collapsing. The rules haven’t caught up. The field is open to anyone ambitious enough to rewire their work, their organization, or their industry around machine intelligence. But none of these conditions will hold for long.

If you drive past a new data-center build in Texas or Virginia today, you might catch a strange sight: a row of trailer-mounted jet engines idling beside concrete shells and cooling towers. They’re not there to fly—they’re there to think.

Yesterday, I spent the afternoon at NVIDIA’s headquarters in Santa Clara. It’s hard not to walk through those glass corridors without feeling that you’ve stepped inside the engine room of a new industrial age. Banks of machines hum like power plants. Engineers move with quiet precision, orchestrating what feels less like software development and more like manufacturing reality itself.

In the summer of 1956, a group of scientists gathered at Dartmouth College to do something extraordinary: decode the nature of human intelligence and recreate it inside a machine. It seems strangely naive now that a handful of white-shirted men, smoking pipes in the New Hampshire heat, believed they could solve consciousness in a few months, the way you might solve a crossword puzzle. Yet the impulse behind that meeting—the conviction that intelligence could be bottled, controlled, and productized—has never really gone away.