Jeff Hawkins

On Intelligence

with Sandra Blakeslee

1
Contents
Prologue
1. Artificial Intelligence
2. Neural Networks
3. The Human Brain
4. Memory
5. A New Framework of Intelligence
6. How the Cortex Works
7. Consciousness and Creativity
8. The Future of Intelligence
Epilogue
Appendix: Testable Predictions
Bibliography
Acknowledgments
2
On
Intelligence
3
Prologue

This book and my life are animated by two passions.

For twenty-five years I have been passionate about mobile computing. In the high-
tech world of Silicon Valley, I am known for starting two companies, Palm
Computing and Handspring, and as the architect of many handheld computers and
cell phones such as the PalmPilot and the Treo.

But I have a second passion that predates my interest in computers- one I view
as more important. I am crazy about brains. I want to understand how the brain
works, not just from a philosophical perspective, not just in a general way, but in a
detailed nuts and bolts engineering way. My desire is not only to understand what
intelligence is and how the brain works, but how to build machines that work the
same way. I want to build truly intelligent machines.

The question of intelligence is the last great terrestrial frontier of science. Most big
scientific questions involve the very small, the very large, or events that occurred
billions of years ago. But everyone has a brain. You are your brain. If you want to
understand why you feel the way you do, how you perceive the world, why you
make mistakes, how you are able to be creative, why music and art are inspiring,
indeed what it is to be human, then you need to understand the brain. In addition,
a successful theory of intelligence and brain function will have large societal
benefits, and not just in helping us cure brain-related diseases. We will be able to
build genuinely intelligent machines, although they won't be anything like the
robots of popular fiction and computer science fantasy. Rather, intelligent
machines will arise from a new set of principles about the nature of intelligence. As
such, they will help us accelerate our knowledge of the world, help us explore the
universe, and make the world safer. And along the way, a large industry will be
created.

Fortunately, we live at a time when the problem of understanding intelligence can
be solved. Our generation has access to a mountain of data about the brain,
collected over hundreds of years, and the rate at which we are gathering more
data is accelerating. The United States alone has thousands of neuroscientists. Yet
we have no productive theories about what intelligence is or how the brain works
as a whole. Most neurobiologists don't think much about overall theories of the
brain because they're engrossed in doing experiments to collect more data about
the brain's many subsystems. And although legions of computer programmers
have tried to make computers intelligent, they have failed. I believe they will
continue to fail as long as they keep ignoring the differences between computers
and brains.

What then is intelligence such that brains have it but computers don't? Why can a
six-year-old hop gracefully from rock to rock in a streambed while the most

4
advanced robots of our time are lumbering zombies? Why are three-year-olds
already well on their way to mastering language while computers can't, despite
half a century of programmers' best efforts? Why can you tell a cat from a dog in a
fraction of a second while a supercomputer cannot make the distinction at all?
These are great mysteries waiting for an answer. We have plenty of clues; what
we need now are a few critical insights.

You may be wondering why a computer designer is writing a book about brains. Or
put another way, if I love brains why didn't I make a career in brain science or in
artificial intelligence? The answer is I tried to, several times, but I refused to study
the problem of intelligence as others have before me. I believe the best way to
solve this problem is to use the detailed biology of the brain as a constraint and as
a guide, yet think about intelligence as a computational problem- a position