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Darwin Among the Machines

by George B. Dyson

Perseus Books. Reading, Massachusetts,1997. Available in paperback from amazon.com.

Chapter 1: Leviathan

LONDON, 1651. Thomas Hobbes' Leviathan is published. [Hobbes' prescient version of the mind/machine metaphor]

'What is the Heart, but a Spring; and the Nerves, but so many Strings... life is but a motion of Limbs....'

Thought cannot be separated from thinking matter.

"...and so the Mind shall be nothing but Motions in some Parts of an Organical Body..."

As God made us, so we, imitating Him with our Art, make machines and artificial animals. [A paraphrase of Dyson's opening quote from Leviathan]

"Human society, taken as a whole, constituted a new form of life, explained Hobbes, 'in which, the Soveraignty is an Artificiall Soul....'"

[Which, in Hobbes' view, is the Word of God embodied in flesh.]

Hobbes didn't seek to diminish God's creation, says Alexander Ross, but simply to suggest that our natural reason is the word of God.

[Mind is equated with Reasoning, which is equated with Computation.]

"All Ratiocination is comprehended in these two operations of the minde, Addition and Substraction." (Leviathan)

PARIS, 1843. [The metaphor is elaborated in] André-Marie Ampère's "Cybernétique"

Cybernétique, from the Greek, the steering of a ship, examines the processes that direct the course of organizations of all kinds.

Deconstructing the firmament of the mind.

Our formalization of logic in binary arithmetic and logical calculus has captured a [sort of] intelligence within a formal mechanical system.

Are these machines alive? Are they intelligent?

[Leave aside for the moment whether mind is fully comprehended by our notion of reason.]

[Emergence is a key concept.]

Biology and technology evidence parallel tendencies toward collective, hierarchical processes based on information exchange.

As information is distributed, it tends to be represented (encoded) by increasingly economical (meaningful) forms.

Emergent behavior is that which cannot be predicted through analysis at any level simpler than that of the system as a whole.

The emergence of life and intelligence from less-alive and less-intelligent components has happened at least once.

Emergent behavior, by definition, is what's left after everything else has been explained.

...it is in the larger networks that we are developing a more likely medium for the emergence of the Leviathan of artificial mind.

"'Emergence offers a way to believe in physical causality while simultaneously maintaining the impossibility of a reductionist explanation of thought,' wrote W. Daniel Hillis...

..."'For those who fear mechanistic explanations of the human mind, our ignorance of how local interactions produce emergent behavior offers a reassuring fog in which to hide the soul.'"

H.G. Wells: World Brain (1938): Memory is the substance from which intelligence is formed. [And the substrate of emergent behavior?]

As we develop digital models of all things great and small, our models are faced with the puzzle of modeling themselves. [The same puzzle we face...]

The initial wiring of our own brains appears to be random. Initial randomness, governed by a few simple rules, yields complexity and [sometimes] intelligence.

Computers may never embody mind at the level of human beings, ...but it is the difference that make symbiotic relationships work.

[Symbiosis, together with emergence, may be at the origins of life itself.]

'Life did not take over the globe by combat, but by networking,' observed Lynn Margulis, describing how life evolved from the exchange of information between primitive chemical microprocessors the first time round.

Life began at least once and has been exploring its alternatives ever since.

[And the symbiosis of humans and computers may be spawning a new form of life/intelligence?]

The cooperation between human beings and microprocessors is unprecedented, not in kind, but in suddenness and scale.

This new Leviathan signals an end to the illusion of technology as human beings exercising control over nature, rather than the other way around

Nature, in her boundless affection for complexity, has begun to claim our creation as her own [through the processes of emergent behavior and symbiosis].

[But note this: When we model computers, we model not ourselves, but our understanding of ourselves. Must computers, likewise, have self-understanding in order to spontaneously model any part of themselves?

And, if so, what would constitute that understanding?

Chapter 2: Darwin Among the Machines

See Samuel Butler's Darwin Among the Machines (1863), Erewhon (1872) and Luck, or Cunning? (1887).

Butler did not argue for creation from design. He argued that species "very gradually, but nonetheless effectually, design themselves."

Erasmus Darwin, Charles' grandfather, in 1794, wrote that

'The world itself might have been generated, rather than created; that is, it might have been gradually produced from very small beginnings, increasing by the activity of its inherent principles...'

Freeman Dyson, George's father, hypothesizes dual origins of life, distinguishing between replication (reproducing exact copies) and reproduction (reproducing similar copies).

He thinks reproducing proteins preceded self-replicating RNA. Most experts think it went the other way around.

If organisms truly replicated, or reproduced even an approximate likeness of themselves without following a distinct set of inherited instructions, we would have Lamarkian evolution, with acquired characteristics transmitted to the offspring. [How doe

In looking for signs of artificial life...one should expect to see signs of metabolism without replication and replication without metabolism first.

If we look at the world around us, we see a prolific growth of electronic metabolism, populated by virulently replicating code- just as the dual-origin hypothesis predicts.

Samuel Butler on the reproductive strategies of machines:

"..'why are [not] we part of that [reproductive system] of the machines?... We are misled by considering any complicated machine as a single thing:

"' in truth it is a city or society, each member of which was bred truly after its kind.'"

The origins of life as we know it-and life as we are creating it-are to be found in the cross-fertilization between self-sustaining metabolism and self-replicating code.

Chapter 3: The General Wind

The young Leibniz to the elderly Hobbes: "'I also wish that you might say something more clearly about the nature of the mind.'"

[What is] the invisible ingredient that leads from the predictability of logic to the unpredictability of mind?

In his Monadology (1714), Leibniz posited a universe of "little minds" that reflect in their own inner state the state of the universe as a whole.

According to Leibniz, relation gave rise to substance, not, as Newton had it, the other way around.

A minimum of laws would lead to a maximum of diversity of results.

'God, who created all things in the beginning, is himself created by all things in the end.' (Olaf Stapleton, 1948)

[Leibniz shared credit for development of continuous functions with Newton], while in combinatorial analysis- the study of relations among discrete sets- he had the field to himself.

Leibniz took first steps toward the arithmetization of logic...and predicted the arithmetization of thought itself.

His 'step reckoner' adding machine was inspired by one constructed in 1642 by Blaise Pascal.

He also worked on binary arithmetic, crediting the invention of binary notation to the binary hexagrams of the I Ching.

Charles Babbage (1791-1871) made a "difference engine" to calculate accurate navigation tables.

It was designed to be able to manipulate its own internal storage registers while reading and writing to and from an unbounded storage medium, strings of punched pasteboard cards, adapted...from those used by the card-controlled Jacquard loom.

George Boole (1815-1864) developed a precise system of logic that has supported the foundations of pure mathematics and computer science ever since.

Boolean algebra reduces logic to is barest essence, [a slim set of mathematical and logical operators that we can all recognize: +, -, x, and, "=", "or", "not", "and", "identity".]

Assumes as initial conditions only the existence of duality- the distinction between nothing and everything; between true and false, between on and off; between the numbers 0 and 1.

Boole's laws correspond not only to ordinary logic, but binary arithmetic..[They are] a bridge... [that] represents the common ancestry of both mathematics and logic in the genesis of the many from the one.

Boole also recognized that error and unpredictability...may be essential to our ability to think.

Kurt Godel (1906-1978) dealt with the fundamental question asked of any formal system: Does it correspond in whole or in part, to the real world?

Godel proved that no formal system encompassing elementary arithmetic can be at the same time both consistent and complete.

It is possible to construct true statements that cannot be proved within the boundaries of the system itself.

This distinction between provability and truth, and a parallel distinction between knowledge and intuition, have been exhibited as evidence to support a distinction between the powers of mechanism and those of mind.

Hobbes and Leibniz both believed in the possibility of intelligent machines; it was over the issue of mechanism's license to a soul, not to an intelligence, that the two philosophers diverged.

Hobbe's God was composed of substance; Leibniz's God was composed of mind. ... According to Leibniz, relation gave rise to substance...

Leibniz on Hobbesian materialism: 'One of their sect could easily persuade himself into believing that idea of some of the ancient writers...according to which souls are born when the machine is organized to receive it, as organ-pipes are adjusted

'...receive the general wind.'

Chapter 4: On Computable Numbers

[Note this ongoing interest in the idea of "soul", with no attempt to precisely define how it differs from "mind".]

' In attempting to construct such machines we should not be irreverently usurping His power of creating souls, any more than we are in the procreation of children;

'...rather we are, in either case, instruments of His will providing mansions for the souls that He creates.' (English logician Alan Turning, 1950)

Turing sought to prove the existence of noncomputable functions, but he had to establish the nature of computability first.

A computable function is a function whose values can be determined by a mechanical procedure performed by a machine whose behavior can be mathematically predicted from one moment to the next.

Recursive functions

A recursive function is a function that can be defined by the accumulation and strictly regulated substitution of elementary component parts. All recursive functions can be deconstructed into a finite number of elemental steps, as multiplication can.

Calculable functions

A function is calculable if it is possible to list all the answers by following a finite set of explicit instructions (an algorithm) that defines exactly what to do from one moment to the next.

Discreteness in time and space

Turing introduced two fundamental assumptions: discreteness of time and discreteness of state of mind... Logic assumes the sequence of cause and effect.

A Machine's State of Mind

In a Turing machine these step-by-step processes are represented by a sequence of discrete symbols encoded on an unlimited supply of tape and by discrete, sequential changes in what Turing called the machine's state of mind.

Turing assumed a finite number of possible states.

...'since the use of more complicated states of mind can be avoided by writing more symbols on the tape.'

Is there a non-calculable "more" to Mind?

[Through further logical analysis, see pages 56-59] Turing concluded that noncomputable functions exist.

'By a kind of miracle,' as Godel himself later referred to Turing's definition, 'the concept of computability transcends the formalism in which it is expressed.'

It is surprising that noncomputable functions, which outnumber computable ones, are so hard to find.

We either inhabit a largely computable world or have gravitated toward a computable frame of mind.

'In fact, it is difficult to find a well-defined example of a non-computable function that anybody wants to compute. This suggests...some deep connection between computability and the physical world and/or the human mind.' (W. Daniel Hillis)

A brisk trade ...develop[ed] around the rehashing of Godel's proof of the incompleteness of formal systems, arguing whether this limitation constrained the abilities of computers to duplicate [intelligence and creativity].


'in other words then, if a machine is expected to be infallible, it cannot also be intelligent.' (Turing, 1947)

To Turing this demonstrated... the need to develop fallible machines able to learn from their own mistakes.

'The argument from Godel's and other theorems rests...on the condition that the machine ...not make mistakes...But this is not a requirement for intelligence.'

Incorporate a random element [such as guesses] to create...a 'learning machine'.

Guesses might be extended not only to external questions, but to modifications in the computer's own instructions.

Turing designed a random-number generator that instead of producing pseudorandom numbers by a numerical process, included a source of truly random electronic noise.

Turing's 'unorganized Machine': largely randomly constructed of large number of similar units capable, in a simple model, of two possible states connected by two inputs and one output each.

This '...simplest model of a nervous system' could be made self-modifying and, with proper upbringing,...become more complicated than anything that could be otherwise engineered.

The human brain must start out as such an unorganized machine, since only in this way could something so complicated be reproduced.

Turing saw evolutionary computation as the best approach to truly intelligent machines.

'Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's" [See role of REM in physical development of maturing brain.]

All intelligence is collective.

The truth that escaped Leibniz, but captured Turing, is that...intelligence arises not from the unfolding of a predetermined master plan, but by the accumulation of random bits of wisdom through the power of small mistakes.

Back to the problem of reconciling the mechanism of intelligence with the unpredictability of mind.

...powers of mind derive not only from...very large numbers (by combinatorial processes alone), but from the realm of the very small (by the element of chance adhering to any observable event.)

Chapter 5: The Proving Ground

Sudden leaps in biological or technological evolution occur when an existing structure or behavior is appropriated by a new function...

Feathers must have had some other purpose before they were used to fly.

Charles Baggage envisioned using the existing network of church steeples that rose above the chaos of London as the foundation for a packet-switched communications net.

On computers vs people as calculators:

'The only difference is that the IBM machines didn't get tired and could work three shifts'. (Richard Feynman)

John Von Neumannn worked on a theory of automata general enough to apply both to the construction of digital computers and to the operation of the brain.

[Our brain as parallel processor]: 'The brain can be conceived as a network with braIn cells in its nodes. ...every...cell can receive impulses from more than one other cell and can transmit impulses to several cells.'

[Which impulses are received or transmitted depend on the state of the cell, which in turn depends on [its history].

The actual state of the cells...would characterize the state of the brain. [ which is synonymous with a state of mind?]

A Turing machine assembles a complex computation from a sequence of atomistic steps. ...the brain represents a computational process by a network of intercommunicating components...and is not necessarily restricted to one computational step at a time.

Chapter 6: Rats in a Cathedral

Ancient instincts drew us toward capturing small animals and dismantling machines.

Something about abandoned machines-the suspension of life without immediate decay- evokes a mix of fear and hope.

There are no qualitative differences in unifying principles underlying intelligent behavior among living beings and machines. (Wiener, Rosenblueth, Bigelow,1947)

...only information concerning the outcome of the previous act...had to [be] returned [for the 'intelligence process' to continue].

Von Neumann's deathbed notes for Yale's Silliman Lectures published posthumously as The Computer and the Brain (1958)

He was preoccupied with explaining the differences.

He had become less interest in whether machines could learn than in whether they could learn to reproduce.

Neumann knew something as complicated as a brain could never be designed; it would have to be evolved.

Today networks of computers execute instructions thousands or even millions of times faster than biological neurons, but this power pales in comparison to the combinatorial abilities of... billions of neurons...

[Today] computers remain rats running two-dimensional mazes at basement level below the foundations of mind.

How ambiguities might bind the ingredients of logic and arithmetic into the cathedral perceived as mind. Hear Von Neumann's Why the Mind is in the Head (1948).

'...all that you need to plan...in detail is the primary automaton, and what you must furnish to it is...neurons which swim around in the cortex....If you do not separate them...then the thing can be watched by the primary automaton and be continuously.

'reorganized...if the primary automaton functions in parallel, if it has various parts which may have to act simultaneously and independently on separate features, you may even get symptoms of conflict...

'...and, if you concentrate on marginal effects, you may observe the ensuing ambiguities...

Chapter 7: Symbiogenesis

The forging of coalitions leading to higher levels of complexity


Alliances produced life:

'...genes were originally independent, virus-like organisms which by symbiotic association formed more complex units' (Niels Aall Barricelli)

Reproduction plus evolution, however, does not necessarily equal life.

Efficient search is what intelligence is all about.

The ability to solve problems is a primary element of intelligence.

A clear-cut definition of 'living' remains elusive to this day.

[The metaphorical imagination at work again:]

Barricelli describes a situation in which it's 'as if genetic material got into the habit of creating a body or a somatic structure only when a situation arises which requires the performance of a specific task (for instance a fight with another organ

'... and assuming that the body would be disintegrated as soon as its objective had been fulfilled.'

[Dyson goes on with the metaphors, on p. 121-23]

But aren't these analogies deeply flawed? No, software is analogous not to self-reproducing organisms, but to self-replicating DNA.

That most software is parasitic (or symbiotic) in its dependence on a host metabolism, rather than freely self-replicating, strengthens rather than weakens the analogies with life.

[The metaphorical imagination run wild.]

Thomas Ray, 1993. A biologist who, after a decade in a South American rainforest, decided to experiment with evolution in a faster form [by means of computation.]

Creating a Tierran reserve...envisioned as a cooperative laboratory for evolving commercially harvestable software of a variety and complexity beyond what we could ever hope to engineer.

The Tierran organisms can survive only within the universe of virtual machines in which they evolved. Outside this special environment they are only data.


Thanks to Godel, Turing and colleagues, the proof was there from the beginning that a digital universe would be an open universe in which mathematical structures of unbounded complexity, intellect...might freely grow.

There is no limit, in mathematics or in physics, to how far and how fast Barricelli's numerical symbioorganisms will be able to evolve.

'This process will be more expeditious than evolution,' Alan Turing predicted in 1950. 'The survival of the fittest is a slow method for measuring advantages. The experimenter, by the exercise of intelligence, should be able to speed it up.'

Chapter 8: On Distributed Communication


Begins with ancient Greek signal lights.....

Robert Hooke (1635-1703): How the minds keeps track...is like a coiled spring.

The mystery was not that we are able to perceive, remember, ...generate new concepts...but how the mind keeps track to temporal sequence while preserving random access to its store of memories and ideas.

Hooke estimated the storage capacity of the human brain [!].

In 1673 he produced an arithmetical engines whose design he kept secret. Also developed a system of information transmission, with control codes- his version of signal lights.

[In the modern era] the obstacles shifted from establishing the physical connections constituting each leg of a telegraph circuit to switching, regenerating, and encoding and decoding the messages at either end.

'Computing machines, said John Von Neumann in 1949, 'can be thought of as machines which are fed, and emit, some medium like punched tape.'

The more connectivity in a network, the more resistant to damage (because there are more alternative routes).

However, the more alternatives, the greater intelligence and memory needed to route messages efficiently through the net.

A central switching authority establishes an unbroken connection for every communication, mediating possible [simultaneous] conflicts

Theseus: Paul Baran's mechanical mouse has...not only to remember, but to forget.

[Baran's interesting 1964 comment on security and release of military communications system design into public domain]

'...we chose not to classify this work, and not to patent the work.

'...if one cannot safely describe a proposed system in the unclassified literature, then, by definition, it is not sufficiently secure to be used with confidence.'

Chapter 9: Theory of Games and Economic Behavior

Von Neumann's game theory and the rise of self-organizing systems.

His early economic papers: Equilibrium shown to depend on growth.

Assume coalitions among players, and how non-zero sum games can be reduced to zero-sum games (where one player's loss equals other players' gain) by including a fictitious, impartial player (sometimes called Nature) in the game.

John Nash (1994), Nobel Prize for Economics: "The human brain is a highly parallel setup. It has to be."

Nash predicted that optimal performance of digital computers would be achieved by coalitions of processors operating under decentralized parallel control.

Despite the advances of neurobiology and cognitive science over the past forty years, this fundamental picture of the brain as a mechanism for evolving meaning from statistics has not changed.

Information in the brain is pulse-frequency coded [?], rather than digitally coded as in a computer.

The resulting tolerance for error is essential for reliable computation by a web of electrically noisy and chemically sensitive neurons bathed in a saline fluid or, perhaps, a web of microprocessors bathed in the distractions of the real world.

Whether a particular signal is accounted for as excitation or inhibition depends on the individual nature of the synapses that mediate its journey through the net.

A two-valued logic is inherent in the details of the neural architecture

McCulloch-Pitts: Any computation performed by a neural network is formally equivalent to some Turing-machine computation that can be performed one step at a time.

Von Neuman: To understand high-complication automata and, in particular, the central nervous system... this process logic will have to undergo a pseudomorphosis to neurology to a much greater extent than the reverse.

Individual units of information in neural net must be assigned a value: apply here the utility function of game theory or mathematical economics.

Higher-level representations... constructed in a neural network are not...step by step processes ...but [constructed] from the relations between dynamic local maxima and minima generated by a real-time, incomprehensibly complex version of one of von Neumann's games.

In a neural network the flow of information behaves like the flow of currency in an economy... Each bit represents the difference between two alternatives, not any one thing at one time.

The metaphor has been used both ways. 'The currency of our systems is not symbols, but excitation and inhibition.' (Rumelhart and McClelland)

[George Dyson's summary of the economic/computation/mind metaphor beginning on page 160 of paperback edition:]








[Economics evolves intelligence.]

The cellular-programing revolution began in the Cambrian era; the computer software revolution began in the era of von Neumann; the monetary revolution began in the time of Hobbes.

Money, like information but unlike material objects, can, by assuming different forms, be made to exist in more than one place at a single time.

That brains in nature operate more as economies than as digital computers should come as no surprise.

Indeed, economic principles are the only known way to evolve intelligent systems from primitive components that are not intelligent themselves.

[On page 169, a metaphoric frenzy equating the flow of currency with the flow of neurotransmitters.]

Components of a neural network must, like components of financial system, have some temporal delay, however small, to allow the network to compute.

The Goal of Life and Intelligence, if there is one...

is awkward to define. It is....order...

which is available in limited quantities, at a certain price.

Organization can be increased or created only by absorbing existing sources of order, or shedding disorder.

In human society, money serves to measure and mediate local markets for decreasing entropy [decreasing disorder.]

Economy of things...by which the meaning of things can be evaluated and from which meaningful information structures can be built.

von Neumann died while working toward a theory of the economy of mind. Physics is the rules. Economy is the means by which organisms and organizations develop strategies that increase their chances for reward.

The formation of coalitions holds the key.

Species are an enduring coalition over space and time.

Our own species is doing its best to adjust to a three-way coalition of...

self-reproducing human beings, self-reproducing numbers, and self-reproducing machines.

Chapter 10: There's Plenty of Room at the Top

A self-organizing system changes from "part separate" to "parts joined". (W. Ross Ashby, 1961)

Meaning has to be supplied from the outside. Any individual system can only be self-organizing with reference to some other system.

This frame of reference can be as complicated as the visible universe or as simple as a single channel of Morse code.

Ashley reported on a series of computer simulations measuring the stability of complex dynamic systems.

They are stable up to a critical level of connectance, and then, as connectance increases, ...go suddenly unstable.

The genesis of life or intelligence within or among computers:

A computers hooked up to a random network. The computer would be [analogous to] the conscious mind. The network [analogous to[ the unconscious.

...the central paradox of artificial intelligence... [is that]...systems simple enough to be understandable are not complicated enough to behave intelligently...

Oliver Selfridge's Pandemonium, 'the uproar of all demons'.

Its aim was to understand Morse code sent by human operators- a...problem in pattern recognition that had confounded all machines to date.

Designed to learn from its mistakes.

...data demons store and pass on data to computational demons who pass results to cognitive demons to weigh the evidence and computes a shriek..

.and from all the shrieks the highest level demon of all, the decision demon, merely selects the loudest.

The tendency to form coalitions makes it impossible to keep the levels of decision making from shifting from one moment to the next. (Barricelli's numerical symbioorganisms and von Neumann's game theory.)

In this ambiguity lies the persistence of the 19th century's argument from design- a ...dispute over whether the power of selection and the intelligence it represents belongs to an all-knowing God or to impartial nature alone...

Intelligence, by any measure, is based on the ability to be selective...

to recognize signal amidst noise, discriminate right from wrong, select the strategy leading to reward...

It is possible to construct self-preserving systems that grow, evolve, and learn, but do not reproduce, compete, or face death in any given amount of time....

A blind watchmaker who can build an eye can evidently assemble structures that no longer stumble around.

Misunderstandings may arise before two alien forms of intelligence become aware of one another. (Barricelli, 1963)

'Nothing, we say to ourselves, can have intelligence unless we understand all about it- as though intelligence in all except ourselves meant the power of being understood rather than of understanding.' (Barricelli)

Contraband passes across the boundaries between life and nonlife as freely as between intelligence and nonintelligence.

The traffic goes both ways, attributing life and intelligence to processes below our own level as well as to those above.

Everywhere we look things are turning out to be more intelligent and more alive than they once seemed.

[Design, again]

Samuel Butler's watch was designed from within; Darwin's watch was designed by the accumulation of sheer coincidence over time.

[Organisms benefit from complexity at certain crucial thresholds.]

' ... complication, as well as organization, below a certain minimum level is degenerative, and beyond that level can become self-supporting and even increasing....' (von Neumann, 1948)

What leads organism to evolve to higher types?

Darwinian evolution plus symbiogenesis

Culture is a form of inheritance that doesn't require killing.

[Persistent Patterns]

Cells are persistent patterns composed of molecules that come and go....species are persistent patterns of individuals who come and go....

[More analogizing]

Comparing human beings to the ants, Thomas observed that 'we are linked in circuits for the storage, processing, and retrieval of information, since this appears to be the most basic and universal of all human enterprises. It may be our biological fu

Thomas' concern over the power of artificial intelligence to run the place for human betterment, his concern over the unsettling prospect of the tyranny of the nervous system over an individual organism's component cells.

Chapter 11: Last and First Men

Olaf Stapleton and Lewis Fry Richardson were in the same Friend's Ambulance Unit in World War I

Richardson was a meteorologist who figured out that 64,000 human computers could calculate a global model of the atmosphere faster than the weather could keep up.

Simple, local rules produce complicated, global results.

His methods similar to those of a massively parallel computation, distributed among multiple processors, simulate complex physical systems.

Stapleton's science fiction: how do two intelligence species recognize [and, I would add, acknowledge] one another.

Self-reproducing clay crystals may have served as a template for the beginnings of organic life, just as organic life is now serving as a substrate for ...self-reproducing forms of silicon and their associated code.

We shall not see biochemistry replaced by electronics; we shall see a merger that incorporates them both.

[See top of page 203 for George Dyson's imaginative reaching for all-encompassing vision of evolution from clay to silica intelligence via biology.]

The emergence of individuality... all depends on bandwidth.

If bandwidth begins to match the internal processing power of the individual nodes in a communications network, individuality begins to merge.

Since human beings (usually) think at a higher speed than that at which they communicate, this situation does not occur in human society, though hints of it may be found in certain ritual activities in which thoughts are synchronized through music...

We can only speculate on how mind might emerge...[when network bandwidth begins to match speed of internal processing.]

Until we understand our own consciousness, there is no way to agree on what, if anything, constitutes consciousness among machines.

Three results are possible, given any supposedly conscious machines. Either the machine says, 'Yes, I am conscious,', or it says, 'No...., or it says nothing at all.

Chapter 12: Fiddling While Rome Burns

Mind has prevailed until recently as a quality distributed among all things, captured one lifetime at a time and then returned...Only our designated prophets bring back something from the edge.









Sir George Dyson, the author's grandfather, on the arts... from Fiddling While Rome Burns, Oxford University Press, 1954)



We stand transfixed, like monkeys given a mirror, by the novelty of our own image reflected in the surface of the web.

...the mystery of much runs even deeper than the mystery of mind.

Hillis' fable, The Songs of Eden, elucidates the symbiosis between sequence (songs) and structure (apes) that [may have] led to the evolution of mind.

'Why do we have these powers of intuition and expression in sound which so completely transcend the normal use of our senses, and which appear to have neither a boundary or a meaning that can be rationally defined?

The only theory of art which makes sense is that which acknowledges the specific creation of a new world...not be be explained in terms of any other worlds...except that of the art in question...

The saint both pursues and creates religion.

The scientist both seeks and makes truth.

The artist evolves his own sense of order and expresses it by his craft.

These are all new worlds, living their own lives according to their own laws.

We cannot explain a world created by our imagination.

It may have no material counterpart in life at all. (Sir George Dyson)

We have mapped, tamed, and dismembered the physical wilderness of our earth. But, at the same time, we have created a digital wilderness whose evolution may embody a collective wisdom greater than our own.

Our destiny and our sanity as human beings depend on our ability to serve a nature whose intelligence we can glimpse all around us, but never quite comprehend.

Not in wilderness, but 'in Wildness is the preservation of the world.' (Henry David Thoreau, "Walking", Atlantic Monthly, June,1862)


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