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Jeff Hawkins (born June 1, 1957 in Long Island, New York) is the founder of Palm Computing (where he invented the PalmPilot) and Handspring_(pda) (where he invented the Treo). He has since turned to work on neuroscience full-time and has founded the Redwood Neuroscience Institute and published On Intelligence describing his memory-prediction framework theory of the brain. He holds a bachelor's degree in electrical engineering from Cornell University. In 2003 he was elected as a member of the National Academy of Engineering "for the creation of the hand-held computing paradigm and the creation of the first commercially successful example of a hand-held computing device."
Since he read a special issue of Scientific American on the brain, Hawkins has always been interested in studying how brains work. Initially, he attempted to start a new department on the subject at his then-employer Intel, who refused. He also attempted to join the MIT AI Lab, but they rejected him. He eventually decided he would try to find success in the computer industry and then try to use it to support his serious work on brains.
In 2002, he did just that. After finding that there was little interest in doing large-scale theoretical work in neuroscience, Hawkins founded the Redwood Neuroscience Institute in Menlo Park, California, California. This institute was officially moved to the University of California, Berkeley on 1 July, 2005 and renamed the Redwood Center for Theoretical Neuroscience. It is now administered through the Helen Wills Neuroscience Institute. This dissolution is a direct result of the formation of Jeff Hawkins' new company, Numenta.
In 2004, he published On Intelligence (with New York Times science writer Sandra Blakeslee), laying out his "memory-prediction framework" of how the brain works.
His unified theory of the brain argues that the key to the brain and intelligence is the ability to make predictions about the world by seeing patterns. He argues that attempts to create an artificial intelligence by simply programming a computer to do what a brain does are flawed and that to actually make an intelligent computer, we simply need to teach it to find and use patterns, not to attempt any specific tasks. Through this method, he thinks we can build intelligent machines, helping us do all sorts of useful tasks that current computers can't achieve. He further argues that this memory-prediction system as implemented by the brain's cortex is the basis of human intelligence.
- "If you look at the history of big obstacles in understanding our world, there's usually an intuitive assumption underlying them that's wrong. In the case of the Solar System it was intuitively obvious that the Earth was at the center of the Solar System and things moved around us, but that just turned out to be wrong. ... And it intuitively seems correct that the brain is just some sort of computer -- it just seems natural. ... But it has undermined almost all of our work to build intelligent machines and understand thinking. It's just wrong ... the brain isn't like a computer at all."
- "This has been a long personal endeavor of mine. Twenty-five years ago ... I just fell in love with brains. ... I decided to dedicate my life to it. It has been a long road, it's up and down, it's actually not an easy thing to do, to say I'm going to work on large-scale theories of brain function. It was not something you could do in the 1980s. There was no place you could go. ... Nobody was doing the large-scale theory. That's changed in only recent years and I started my institute, the Redwood Neuroscience Institute, to create a place where you could focus on this problem. And, I think, that's really all it took."
- Hawkins, Jeff (2005). On intelligence, Times Books, Henry Holt and Co. ISBN 0-8050-7456-2
- On Intelligence
- Crazy about Brains Cornell Engineering Magazine, Spring 2005
- Jeff Hawkins: The man who almost single-handedly revived the handheld computer industry, Pen Computing
- Jeff Hawkins Stanford Entrepreneurial Thought Leaders lecture Podcast
- Video lecture: Can a New Theory of the Neocortex Lead to Truly Intelligent Machines?