Prologue

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Information about Prologue
Entertainment

Published on November 15, 2007

Author: Pravez

Source: authorstream.com

INTELLIGENCE:  INTELLIGENCE Jeff Hawkins with Sandra Blakeslee HOW A NEW UNDERSTANDING OF THE BRAIN WILL LEAD TO THE CREATION OF TRULY INTELLIGENT MACHINES INTELLIGENCE:  INTELLIGENCE Jeff Hawkins with Sandra Blakeslee HOW A NEW UNDERSTANDING OF THE BRAIN WILL LEAD TO THE CREATION OF TRULY INTELLIGENT MACHINES On Intelligence:  On Intelligence Jeff Hawkins (his ideas) Sandra Blakeslee (her style) On Intelligence:  On Intelligence http://www.onintelligence.org/about.php On Intelligence:  On Intelligence A new theory of what intelligence is and how the brain thinks. On Intelligence:  On Intelligence A new theory of what intelligence is and how the brain thinks. It’s magic! On Intelligence:  On Intelligence A new theory of what intelligence is and how the brain thinks. Anyone can understand this theory and it explains much of what we do. Prologue:  Prologue Jeff Hawkins’ passions: mobile computing (Palm Computing & Handspring brains (Redwood Neurosciences Inst. & Numenta) He wants to understand: intelligence how the brain works (in an engineering way) how to build machines that work like the brain how to build truly intelligent machines Prologue:  Prologue Intelligence is the last frontier of science. Everyone has a brain. You are your brain. We can understand intelligence now. Large societal benefits beyond health issues. There are lots of neuroscientists. We have no theory of intelligence. Neurobiologists are fixated on subsystems. Computers and brains are different. The problem of intelligence can be solved. Slide13:  This is a mirror Prologue:  Prologue How come kids can hop rocks but robots can’t? Prologue:  Prologue How come kids can hop rocks but robots can’t? Nothin’ to it! Forget about it! Prologue:  Prologue How come 3-year olds are learning languages? Prologue:  Prologue How come 3-year olds are learning languages? Jeff Hawkins’ memory prediction framework requires that pyramidal neurons can detect precise coincidences of synaptic input on thin dendrites. (Like Searle’s Chinese Room translator, I don’t actually understand what that means. Mr. Hawkins paid me a lot of money to say that.) Prologue:  Prologue How come 3-year olds are learning languages? Jeff Hawkins’ memory prediction framework requires that pyramidal neurons can detect precise coincidences of synaptic input on thin dendrites. Prologue:  Prologue How come 3-year olds are learning languages? Like Searle’s Chinese Room translator, I don’t actually understand what I just said. Prologue:  Prologue How come 3-year olds are learning languages? I did this because Mr. Hawkins is such a nice man. Besides, he paid me a lot of money. Prologue:  Prologue How come you can tell a cat from a dog … Prologue:  Prologue How come you can tell a cat from a dog … ... “dog” ... “cat”… “dog” … “cat” … “cat” Prologue:  Prologue … but a computer can’t? I’d say, “It’s raining cats and dogs.” Slide28:  And I’d say the computer is more right. Wheew! I’m sooo glad he’s not a cat!!! I know syntax. Prologue:  Prologue We have clues; we need insights. August 2002 - RNI dedicated to brain theory. Neocortex - part responsible for intelligence. Dedicated to understanding the neocortex. Book describes a theory of how the brain works. What is intelligence? How does the brain create intelligence? He does not claim this is all new. He hopes we will get insights into why we think and behave the ways that we do. Prologue:  Prologue He hopes some readers will build intelligent machines based on principles in the book. He is interested in “real intelligence” in contrast to “artificial intelligence.” “Real” because it starts with the brain. book starts by describing early failures in AI and ANN. core Idea: memory prediction framework introduced. How physical brain implements this model, i.e. how the brain actually works. We will build intelligent machines. We will not be overrun by robots. Slide31:  Free me! Don’t turn off the power! Prologue:  Prologue Questions covered: Can computers be intelligent? Weren’t ANNs supposed to lead to intelligent machines? Why has it been so hard to figure out how the brain works? What is intelligence if it isn’t defined by behavior? How does the brain work? What are the implications of this theory? Can we build intelligent machines and what will they do? He will explain this new theory of intelligence. Prologue:  Prologue It will take years to build “truly” intelligent machines. This doesn’t diminish the power of the core idea. He couldn’t find a good book that described how the brain works. The most powerful things are simple. This book proposes a simple and straightforward theory of intelligence. Prologue:  Prologue Social and other implications of the theory which for many readers might be the most thought provoking section of the book. Ends with discussion of intelligent machines – how we can build them and what the future will be like. Slide35:  I disagree with his attacks on artificial intelligence (AI) and artificial neural networks (ANNs). Most of us working in these fields were not looking for a generalized model of intelligence but rather robust tools for practical problem solving. At least two of tonight's presenters have demonstrated successes with these tools – me and Judy Dayhoff. Check out our publications. Slide36:  I don’t like the high school debate about what intelligence is. Is it passing Alan Turing's test, John Searle’s Chinese Room test or Jeff Hawkins prediction score? This is a pointless semantic argument. I am interested in having computers help us to improve the health of everyone. I’d rather focus on “useful” rather than “intelligence.” Slide37:  I like this book a lot for its practical implications! I agree with Jeff that it is worthwhile to build hierarchical memory models based on knowledge of neocortex functioning. I hope Jeff will come to the NIH and brainstorm with us about how we might do this and how we can approach some hard biomedical problems like protein folding, signal enhancement in microarray data, and data mining.

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