New Book:

What is Thought?
Eric B. Baum

MIT Press    495p   

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Can the strong AI/ Turing picture be extended to a plausible 
model of all aspects of mind, such as understanding, creativity,
language, reasoning, learning, and consciousness? I propose 
a candidate extension that is consistent with extensive data 
from a variety of fields and makes empirical predictions.
In my view meaning is the computational exploitation of the 
compact underlying structure of the world, and mind is execution 
of an evolved program that is all about meaning. I extrapolate 
computer science research on Occam's Razor to argue
that meaning results from finding a compact enough program behaving
effectively in the world; such a program can only be compact by virtue
of code reuse, factoring into interacting modules that capture real
concepts and are reused metaphorically. For a variety of reasons, 
including arguments based on complexity theory, developmental 
biology, evolutionary programming, ethology, and simple 
inspection, this compact Occam program 
is most naturally seen to be in the DNA, rather than the brain. 
Learning and reasoning are then fast and almost automatic
because they are constrained by the DNA programming
to deal only with meaningful quantities. Evolution itself is argued
to exploit meaning in related ways. Words are labels for meaningful
computational modules. Using the abilility to pass along programs
through speech, humans have made cumulative progress in constructing
useful computational modules built on top of the ones supplied
by evolution. The difference between human and chimp intelligence
is largely in this additional programming, and thus can be regarded
as due to better nurturing. 

The many aspects of consciousness
are also very naturally and consistently understood in this
context. For example, although the mind is a distributed 
program composed of many modules, the self emerges naturally
as a reification of the interest of the genes.
Qualia (the sense of experience of sensations such as pain
or redness) have exactly the appropriate nature and meaning that 
evolution coded in the DNA so that the compact program behaves 
effectively.

This book is highly relevant to the AGI agenda in many ways, 
surveying much of the progress of AI with an eye toward why it has
fallen short of general intelligence, proposing a theory of how mind
achieves general intelligence, and discussing what steps would
be useful to achieve general intelligence computationally. 
Because I argue that most of the computational work in producing 
mind was done by evolution, rather than in our brains during our 
lifetimes, I view the computational complexity of building an AGI 
as significantly more challenging than other authors. However, 
I also present results of evolutionary programming experiments
in the Hayek model, where we have succeeded in evolving, from
random code, programs that solve classes of difficult planning
problems in ways that seem to give intuition into how a program
can achieve understanding. We were able to achieve these results
because an analysis of evolutionary dynamics suggested mechanisms
that greatly speed such evolution.



---------------------------------------
>From the back cover:
 
"This book is the deepest, and at the same time the most commonsensical, 
approach to the problem of mind and thought that I have read.  The approach 
is from the point of view of computer science, yet Baum has no illusions 
about the progress which has been made within that field. He presents the 
many technical advances which have been made -- the book will be enormously 
useful for this aspect alone -- but refuses to play down their glaring 
inadequacies. He also presents a road map for getting further and makes the 
case that many of the apparently 'deep' philosophical problems such as free 
will may simply evaporate when one gets closer to real understanding."
--Philip W. Anderson, Joseph Henry Professor of Physics, Princeton 
University, 1977 Nobel Laureate in Physics

"Eric Baum's book is a remarkable achievement. He presents a novel thesis 
-- that the mind is a program whose components are semantically meaningful 
modules -- and explores it with a rich array of evidence drawn from a 
variety of fields. Baum's argument depends on much of the intellectual core 
of computer science, and as a result the book can also serve as a short 
course in computer science for non-specialists. To top it off, *What is 
Thought?* is beautifully written and will be at least as clear and 
accessible to the intelligent lay public as *Scientific American*."
--David Waltz, Director, Center for Computational Learning Systems, 
Columbia University

"What's great about this book is the detailed way in which Baum shows the 
explanatory power of a few ideas, such as compression of information, the 
mind and DNA as computer programs, and various concepts in computer science 
and learning theory such as simplicity, recursion, and position evaluation. 
*What is Thought?* is a terrific book, and I hope it gets the wide 
readership it deserves."
--Gilbert Harman, Department of Philosophy, Princeton University

"There is no problem more important, or more daunting, than discovering the 
structure and processes behind human thought. *What is Thought?* is an 
important step towards finding the answer. A concise summary of the 
progress and pitfalls to date gives the reader the context necessary to 
appreciate Baum's important insights into the nature of cognition."
--Nathan Myhrvold, Managing Director, Intellectual Ventures, and former 
Chief Technology Officer, Microsoft



Eric B. Baum has held positions at the University of California at
Berkeley, Caltech, MIT, Princeton, and the NEC Research Institute. 
He holds a BA and MA from Harvard and a PhD in physics from
Princeton. He is currently developing algorithms based on 
Machine Learning and Bayesian Reasoning to found a hedge fund.

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