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What Is Thought?
In What Is Thought? Eric Baum proposes a computational explanation of thought. Just as Erwin Schrodinger in his classic 1944 work What Is Life? argued ten years before the discovery of DNA that life must be explainable at a fundamental level by physics and chemistry, Baum contends that the present-day inability of computer science to explain thought and meaning is no reason to doubt there can be such an explanation. Baum argues that the complexity of mind is the outcome of evolution, which has built thought processes that act unlike the standard algorithms of computer science and that to understand the mind we need to understand these thought processes and the evolutionary process that produced them in computational terms. Baum proposes that underlying mind is a complex but compact program that corresponds to the underlying structure of the world. He argues further that the mind is essentially programmed by DNA. We learn more rapidly than computer scientists have so far been able to explain because the DNA code has programmed the mind to deal only with meaningful possibilities. Thus the mind understands by exploiting semantics, or meaning, for the purposes of computation; constraints are built in so that although there are myriad possibilities, only a few make sense. Evolution discovered corresponding subroutines or shortcuts to speed up its processes and to construct creatures whose survival depends on making the right choice quickly. Baum argues that the structure and nature of thought, meaning, sensation, and consciousness therefore arise naturally from the evolution of programs that exploit the compact structure of the world.
494 pages, Paperback
First published December 19, 2003
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Displaying 1 - 5 of 5 reviews
January 23, 2021
The essence of life
Author Eric Baum proposes an interesting theory that the mind is the result of evolution, and thought processes is rooted in DNA that represents a natural algorithm. DNA code programmed the mind to construct few meaningful possibilities among countless of possibilities. The nature of thought and consciousness is built on this compact code.
DNA is a language connecting two parts of the cosmos, the matter (non-living) and life (living) in a circle. The initial time-forward process of cosmos corresponds to disorder and entropy driven physical system, and the second part is conscious awareness, the semantics of DNA information of the living cell, which corresponds to increasing order and lowering of entropy. This classical projection of the semantics of DNA encryption is analogous to the famous Double-Slit Experiment that demonstrates the quantum nature of existence, the wave-particle duality of matter and the probabilistic nature of quantum reality. In this experiment when each photon hits the screen, its location in classical space appears random and disorderly. But the wave interference pattern leads to a conclusion that the random outcome of photon hits in classical space becomes an ordered image on the screen through conscious interaction. Indeed, life which reflects a transition from disorder (matter) to order was termed as negative entropy by physicist Erwin Schrodinger.
the Informational model of consciousness is the acquisition and transmission mechanisms of certain traits to the future generations without affecting the DNA sequences. These epigenetic mechanisms are described as signal transmission agents embodying or disembodying information. Mechanisms of epigenetic inheritance could include DNA methylation, histone modification and small RNA transmission. The epigenetic mechanisms allow body adaptation in terms of the computation informational system.
The author is a developer of algorithms based on machine learning and Bayesian reasoning. Some chapters are technically more challenging than others, the overall read is a little bumpy, but the take-home message is well described.
Author Eric Baum proposes an interesting theory that the mind is the result of evolution, and thought processes is rooted in DNA that represents a natural algorithm. DNA code programmed the mind to construct few meaningful possibilities among countless of possibilities. The nature of thought and consciousness is built on this compact code.
DNA is a language connecting two parts of the cosmos, the matter (non-living) and life (living) in a circle. The initial time-forward process of cosmos corresponds to disorder and entropy driven physical system, and the second part is conscious awareness, the semantics of DNA information of the living cell, which corresponds to increasing order and lowering of entropy. This classical projection of the semantics of DNA encryption is analogous to the famous Double-Slit Experiment that demonstrates the quantum nature of existence, the wave-particle duality of matter and the probabilistic nature of quantum reality. In this experiment when each photon hits the screen, its location in classical space appears random and disorderly. But the wave interference pattern leads to a conclusion that the random outcome of photon hits in classical space becomes an ordered image on the screen through conscious interaction. Indeed, life which reflects a transition from disorder (matter) to order was termed as negative entropy by physicist Erwin Schrodinger.
the Informational model of consciousness is the acquisition and transmission mechanisms of certain traits to the future generations without affecting the DNA sequences. These epigenetic mechanisms are described as signal transmission agents embodying or disembodying information. Mechanisms of epigenetic inheritance could include DNA methylation, histone modification and small RNA transmission. The epigenetic mechanisms allow body adaptation in terms of the computation informational system.
The author is a developer of algorithms based on machine learning and Bayesian reasoning. Some chapters are technically more challenging than others, the overall read is a little bumpy, but the take-home message is well described.
May 29, 2017
Eric Baum points out that until recently, most scientists thought biological life could never be rationally explained but today few people doubt that a scientific explanation of life is possible. In the same way, we should now believe that the mind can be explained in terms of physics, biology, mathematics, and other scientific principles. This book claims to provide that explanation.
Baum chooses the theory of evolution and principles of computer science to sculpt a remarkable image of the mind as computer program – not a mind like a computer, but literally a computing program. What does it compute? Understanding of the world, leading to behavior for genetic propagation. Who was the programmer? Evolution by natural selection.
One of the most important things DNA does, he says, is to create a brain as an algorithm, a recipe for dealing with the world. The recipe does not contain facts about the world, but instructions for getting around in the world. Instructions are much simpler than facts, just as the recipe for a cake can fit on one 3x5 card but a specification of its chemical composition would take up many pages.
What about the mind though? The brain is the mind, in Baum’s narrative. The terms are used interchangeably, without qualification, throughout the book. Since science can only deal with physical things, the mind must be the same as the brain for Baum’s thesis to work.
One standard objection to that idea is that thoughts don’t seem like brain processes. Baum says thought occurs when we are aware of the brain-computer working, but that doesn’t seem right. When I think about the world, I am not aware of my brain at all. Baum has no serious answer for that and seems not to grasp the objection.
Another well-known objection points out that a computer program is a syntactical system, a kind of grammar. Semantics, the meaning of the words, is independent of the syntax. (“‘Twas brillig, and the slithey toves…” is syntactically correct but meaningless). Grammar does not reveal what words mean and likewise, a recipe doesn’t know what the cake tastes like. Even if the brain was a computer program, as a syntax, it would have no capacity for meaning.
Baum addresses that objection by re-defining semantics to be appreciation of perceptual invariants. An invariant is something that does not change when things around it change. Invariants are essentially, Platonic essences. The idea that the brain deals in invariants goes back decades. J.J. Gibson proposed a theory of perception based on detection of the invariant structures of the world. In physics and mathematics, invariant theory is well developed.
DNA was imprinted, through evolution, with the world’s invariant contingencies and that causal relationship gives DNA semantic capability (as semantics is now redefined). The DNA program in turn generates the brain program, so the brain/mind also refers the world by being susceptible to its invariants.
It’s true, there are neurons in a frog’s brain that fire when a moving dot (a “fly”) moves across the visual field, and neurons in a cat’s brain fire differentially to horizontal and vertical stripes, but that seems a far cry from explaining why I might prefer democracy over fascism.
Baum calls the process of invariant recognition “exploitation,” which is no more helpful than Gibson’s term for the process, “resonance.” So if meaning is exploitation of invariants, we don’t know how it works.
Baum declares nevertheless, “…I am offering a theory that is, in my view and I hope by now in the reader’s as well, capable of explaining everything” (p. 435). Well, yes. If my only tool is a hammer, all the world is made of nails.
Why should anyone take seriously a theory of mind that includes the principle that theories have no meaning? Words are simply labels for environmental invariants, according to Baum, and that is their only meaning (and we must disregard questions about how language fits into this formulation). By his own rights then, the contents of this book are the traces of somebody’s muscle spasms as that person confronted his world. Why should anyone else care about that?
The book could profitably be used in an introductory interdisciplinary course cognitive science, psychology and philosophy. As a persuasive argument, it does not succeed, but the journey is interesting.
Baum chooses the theory of evolution and principles of computer science to sculpt a remarkable image of the mind as computer program – not a mind like a computer, but literally a computing program. What does it compute? Understanding of the world, leading to behavior for genetic propagation. Who was the programmer? Evolution by natural selection.
One of the most important things DNA does, he says, is to create a brain as an algorithm, a recipe for dealing with the world. The recipe does not contain facts about the world, but instructions for getting around in the world. Instructions are much simpler than facts, just as the recipe for a cake can fit on one 3x5 card but a specification of its chemical composition would take up many pages.
What about the mind though? The brain is the mind, in Baum’s narrative. The terms are used interchangeably, without qualification, throughout the book. Since science can only deal with physical things, the mind must be the same as the brain for Baum’s thesis to work.
One standard objection to that idea is that thoughts don’t seem like brain processes. Baum says thought occurs when we are aware of the brain-computer working, but that doesn’t seem right. When I think about the world, I am not aware of my brain at all. Baum has no serious answer for that and seems not to grasp the objection.
Another well-known objection points out that a computer program is a syntactical system, a kind of grammar. Semantics, the meaning of the words, is independent of the syntax. (“‘Twas brillig, and the slithey toves…” is syntactically correct but meaningless). Grammar does not reveal what words mean and likewise, a recipe doesn’t know what the cake tastes like. Even if the brain was a computer program, as a syntax, it would have no capacity for meaning.
Baum addresses that objection by re-defining semantics to be appreciation of perceptual invariants. An invariant is something that does not change when things around it change. Invariants are essentially, Platonic essences. The idea that the brain deals in invariants goes back decades. J.J. Gibson proposed a theory of perception based on detection of the invariant structures of the world. In physics and mathematics, invariant theory is well developed.
DNA was imprinted, through evolution, with the world’s invariant contingencies and that causal relationship gives DNA semantic capability (as semantics is now redefined). The DNA program in turn generates the brain program, so the brain/mind also refers the world by being susceptible to its invariants.
It’s true, there are neurons in a frog’s brain that fire when a moving dot (a “fly”) moves across the visual field, and neurons in a cat’s brain fire differentially to horizontal and vertical stripes, but that seems a far cry from explaining why I might prefer democracy over fascism.
Baum calls the process of invariant recognition “exploitation,” which is no more helpful than Gibson’s term for the process, “resonance.” So if meaning is exploitation of invariants, we don’t know how it works.
Baum declares nevertheless, “…I am offering a theory that is, in my view and I hope by now in the reader’s as well, capable of explaining everything” (p. 435). Well, yes. If my only tool is a hammer, all the world is made of nails.
Why should anyone take seriously a theory of mind that includes the principle that theories have no meaning? Words are simply labels for environmental invariants, according to Baum, and that is their only meaning (and we must disregard questions about how language fits into this formulation). By his own rights then, the contents of this book are the traces of somebody’s muscle spasms as that person confronted his world. Why should anyone else care about that?
The book could profitably be used in an introductory interdisciplinary course cognitive science, psychology and philosophy. As a persuasive argument, it does not succeed, but the journey is interesting.
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August 3, 2008an intriguing read. Baum's basic thesis is thought is a computer programming. Much of the basic semantics of our thought processes are coded in our genes. Essentially in our DNA exists meta-learning algorithms with an inductive bias to direct us towards learning certain things and perceive certain structures in the world. He analyzes the computational capability of evolution to produce the type of intelligence in humans it has produced.
February 1, 2014
Wide ranging with many interesting points, though more enlightening for readers unfamiliar with the things Baum is talking about. However: too much reliance on massive modularity (let's face it: it's nonsense) and too little focus on embodiment.
Want to read
April 15, 2017reviews a variety of interesting issues related to AGI
Displaying 1 - 5 of 5 reviews