Special report : Can we copy the brain? - What intelligent machines need to learn from the Neocortex

Computers have transformed work and play, transportation and medicine, entertainment and sports. Yet for all their power, these machines still cannot perform simple tasks that a child can do, such as navigating an unknown room or using a pencil. The solution is finally coming within reach. It will emerge from the intersection of two major pursuits: the reverse engineering of the brain and the burgeoning field of artificial intelligence. Over the next 20 years, these two pursuits will combine to usher in a new epoch of intelligent machines. Why do we need to know how the brain works to build intelligent machines? Although machine-learning techniques such as deep neural networks have recently made impressive gains, they are still a world away from being intelligent, from being able to understand and act in the world the way that we do. The only example of intelligence, of the ability to learn from the world, to plan and to execute, is the brain. Therefore, we must understand the principles underlying human intelligence and use them to guide us in the development of truly intelligent machines.

Learning by Rewiring

Brains exhibit some remarkable learning properties. First, we learn quickly. A few glances or a few touches with the fingers are often sufficient to learn something new. Second, learning is incremental. We can learn something new without retraining the entire brain or forgetting what we learned before. Third, brains learn continuously. As we move around the world, planning and acting, we never stop learning. Fast, incremental, and continuous learning are essential ingredients that enable intelligent systems to adapt to a changing world. The neuron is responsible for learning, and the complexities of real neurons are what make it a powerful learning machine.