The race for fully autonomous vehicles (AVs) is no longer just about better sensors or sleeker cars. It has become a battle for computational power and energy efficiency that is stretching from the asphalt of Silicon Valley all the way to low-Earth orbit. To understand the future of self-driving cars, we have to start with the fundamental data structure that makes them work, follow that data to the massive server farms where it’s processed, and finally, look up at the radical new solution Google is proposing to keep the whole system running. Here is the journey of an autonomous vehicle’s "brain," from the road to the stars. 1. The Universal Language: Tensors Before a self-driving car can make a decision, it has to "see." But a car’s computer doesn’t see a pedestrian or a stop sign the way humans do; it sees massive, multi-dimensional blocks of numbers. These blocks are called Tensors . Tensors are the lifeblood of deep learning. Every sensor on an AV fee...