This theory describes the process of how the brain makes predictions of future events by matching sensory inputs to stored memory patterns. Inputs that are processed from the bottom-up interact with expectations from the top-down to generate predictions. When a particular level recognizes a pattern, a label is associated and forwarded to the next level in the hierarchy.
Jeff Hawkins was inspired by an issue of Scientific American dedicated to the brain. He saw that neuroscience lacked a comprehensive framework to describe the operation of the brain and embarked on an effort to build one. In this TED video, he describes his ideas and their implications on artificial intelligence and machine learning.