The brain is the most incredible organ in the human body. It dictates the way we per‐ ceive every sight, sound, smell, taste, and touch. It enables us to store memories, experience emotions, and even dream. Without it, we would be primitive organ‐ isms, incapable of anything other than the simplest of reflexes. The brain is, inher‐ ently, what makes us intelligent.
The infant brain only weighs a single pound, but somehow it solves problems that even our biggest, most powerful supercomputers find impossible. Within a matter of months after birth, infants can recognize the faces of their parents, discern discrete objects from their backgrounds, and even tell apart voices. Within a year, they’ve already developed an intuition for natural physics, can track objects even when they become partially or completely blocked, and can associate sounds with specific mean‐ ings. And by early childhood, they have a sophisticated understanding of grammar and thousands of words in their vocabularies.
For decades, we’ve dreamed of building intelligent machines with brains like ours— robotic assistants to clean our homes, cars that drive themselves, microscopes that automatically detect diseases. But building these artificially intelligent machines requires us to solve some of the most complex computational problems we have ever grappled with; problems that our brains can already solve in a manner of microsec‐ onds. To tackle these problems, we’ll have to develop a radically different way of pro‐ gramming a computer using techniques largely developed over the past decade. This is an extremely active field of artificial computer intelligence often referred to as deep learning.
