CAMBRIDGE – In his pathbreaking 2005 book On Intelligence, Jeff Hawkins proposed an alternative paradigm of how the human brain works. In his view, the brain is not a Turing machine that manipulates symbols according to a table of rules, which is the model on which computers and artificial intelligence have been based. Instead, the brain is a giant hierarchical memory that is constantly recording what it perceives and predicting what will come next.
The brain makes predictions by finding similarities between patterns in recent sensory inputs and previous experiences stored in its vast memory. It matches current fragmentary sounds in a sea of noise with a known song, or the face of a person in disguise with that of your child. The idea is similar to the auto-complete function in, say, the Google search box – constantly guessing what you will enter next based on what you have already typed in.
To see the hierarchy in this mechanism, consider that by perceiving just a few letters, you can predict the word; by looking at a few words, you can predict what the sentence means, or even the paragraph. In fact, right now you must be guessing where it is that I am going with this entire commentary. The hierarchy allows you to understand meaning, whether the input got to your brain by reading or listening. The brain is thus an inductive machine that predicts the future based on finding similarities, at many different levels, between the present and the past.
Hawkins’ alternative model of how the brain works has important implications for many fields, including the one that I spend most of my time thinking about: economic-development strategy.