When one robot learns, every robot knows if they can communicate

The robots are among us.

They’re carrying passengers through the streets of San Francisco, delivering parcels over the air, and working their way across farms, factories, mines, and industrial sites.

The collision we’re now witnessing between artificial intelligence and the physical world is often described as “Physical AI” – machines capable of perceiving their surroundings, making decisions, and taking action among us in the real world.

But every new machine that clocks in has a second job we rarely see.

It creates data .

Lots of it.

In the US, the Federal Aviation Administration expects the commercial drone fleet to grow from approximately 966,000 aircraft at the end of 2024 to around 1.18 million by 2029.

And in factories around the world, there was an estimated 4.66 million industrial robots working in 2024, while another half a million were installed during the year – more than twice the number installed a decade earlier.

Today’s autonomous machines are vastly more capable, but moving all that accumulated experience off them can still be surprisingly manual.

In 2026, the fastest way to move masses of data off a machine is still a person carrying a hard drive.

And as autonomous machines spread further into our cities and industries, keeping that information moving could become one of the defining infrastructure challenges of the robotics age.

Data runs both ways Imagine what an autonomous vehicle experiences.

Cameras watch the roads from multiple angles, sensors and AI measure and make sense of the surrounding environment, while on-board systems track position and performance of the vehicle itself.

Decisions are made and recorded in real-time as pedestrians cross roads, traffic lights change, and thousands of other vehicles and connected technologies move and exchange data around it.