beyond the turing test

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Beyond the Turing Test. Tom Ray ATR HIP Labs, Kyoto Zoology Department University of Oklahoma. The Turing Test. The Turing Test suggests that we can know that machines have become intelligent when we can not distinguish them from human, in free conversation over a teletype. The Turing Test. - PowerPoint PPT Presentation

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Beyond the Turing Test

Tom Ray

ATR HIP Labs, Kyoto

Zoology Department

University of Oklahoma

The Turing Test

The Turing Test suggests that we can know that machines have become intelligent when we can not distinguish them from human, in free conversation over a teletype

The Turing Test

The Turing Test suggests that we can know that machines have become intelligent when we can not distinguish them from human, in free conversation over a teletype

The Turing Test is one of he biggest red-herrings in science

Early Cinema

It reminds me of early cinema when we set a camera in front of a stage and filmed a play.

Because the cinema medium was new, we didn’t fully understand what it is and what we can do with it.

The Nature of the Medium

We didn’t understand the nature of the medium of cinema.

We are almost in the same position today with respect to the digital medium.

Spaces

Over and over again, in a variety of ways, we are shaping cyberspace in the form of the 3D material space that we inhabit.

But cyberspace is not a material space and it is not inherently 3D.

A place for the mind

I have heard it said that cyberspace is a place for the mind, yet we feel compelled to take our bodies with us.

3D virtual worlds and avatars are a manifestation of this.

Why do these worlds look and function as much as possible like the real thing?

Virtual Tower Records Store

I have seen virtual worlds where you walk down streets lined by buildings.

In one I saw a Tower Records store, whose front looked like the real thing.

You approached the door, opened it, entered, and saw rows of CDs on racks, and an escalator to take you to the next floor.

Virtual Tower Records Store

I have seen virtual worlds where you walk down streets lined by buildings.

In one I saw a Tower Records store, whose front looked like the real thing.

You approached the door, opened it, entered, and saw rows of CDs on racks, and an escalator to take you to the next floor.

Just Like The Real Thing!

Alpha World

I saw a demo of Alpha World, built by hundreds of thousands of mostly teenagers.

It was the day after Princess Diana died, and there were many memorials to her, bouquets of flowers by fountains, photos of Diana with messages.

Alpha World

I saw a demo of Alpha World, built by hundreds of thousands of mostly teenagers.

It was the day after Princess Diana died, and there were many memorials to her, bouquets of flowers by fountains, photos of Diana with messages.

It looked Just Like The Real memorials to Diana.

Why?

I wondered, why do these worlds look and function as much as possible like the real thing?

We can do anything

This is cyberspace, where we can do anything.

We can move from point A to point B instantly without passing through the space in between.

So why are we forcing ourselves to walk down streets and halls and to open doors?

A Different Physics

Cyberspace is not a 3D Euclidean space.It is not a material world.We are not constrained by the same laws of

physics, unless we impose them upon ourselves.

Liberate our Minds

We need to liberate our minds from what we are familiar with, before we can use the full potential of cyberspace.

Why should we compute collision avoidance for avatars in virtual worlds

when we have the alternative to find out how many avatars can dance on the head of a pin?

Artificial Intelligence

A machine might exhibit an intelligence exactly like and indistinguishable from humans (Turing AI)

Or a machine might exhibit a fundamentally different kind of intelligence,

like some science fiction alien intelligences.

Sample Size of One

Everything we know about life is based on one example of life: Life on Earth

Everything we know about intelligence is based on one example of intelligence: Human Intelligence

This limited experience burdens us with preconceptions, and limits our imaginations

Thought Experiment

We are all robotsOur bodies are made of metal and our

brains of silicon chipsWe have no experience or knowledge of

carbon based life,not even in our science fiction

This stuff?

Now one of us robots comes to our physics seminar with a flask of methane, ammonia, hydrogen, water, and some dissolved minerals.

The robot asks: “Do you suppose we could build a computer from this stuff?”

The Engineers Solution

The engineers among us might propose nano-molecular devices with fullerene switches, or even DNA-like computers.

But I am sure that they would never think of neurons.

Neurons are astronomically large structures compared to the molecules we are starting with

The Carbon MediumFaced with the raw medium of carbon

chemistry, and no knowledge of organic life,

we would never think of brains built of neurons,

supported by circulatory and digestive systems,

in bodies with limbs for mobility, bodies which can only exist in the context

of the ecological community that feeds them.

The Digital Medium

We are in a similar position today as we face the raw medium of digital computation and communications.

The preconceptions and limited imaginations deriving from our organic-only experience of life and intelligence,

make it difficult for us to understand the nature of this new medium, and the forms of life and intelligence that might inhabit it

Going Beyond?How can we go beyond our conceptual

limits,find the natural form of intelligent processes

in the digital medium,and work with the medium to bring it to its

full potential,rather than just imposing the world we

know upon it by forcing it to run a simulation of our physics, chemistry, and biology?

Evolution

In the carbon medium it was evolution that explored the possibilities inherent in the medium, and created the human mind.

Evolution listens to the medium that it is embedded in.

It has the advantage of being mindless,and therefore devoid of preconceptions,and not limited by imagination.

Digital Nature

I propose the creation of a digital nature.A system of wildlife reserves in cyberspacein the interstices between human

colonizations,feeding off of unused CPU-cyclesand permitted a share of our bandwidth

Spontaneous Digital Evolution

This would be a place where evolution can spontaneously generate complex information processes,

free from the demands of human engineers and market analysts telling it what the target applications are.

A place for a digital Cambrian explosion of diversity and complexity

Prospecting Digital NatureDigital naturalists can then explore this

cyber-nature in search of applications for the products of digital evolution,

in the same way that our ancestors found applications among the products of organic nature, such as: rice, wheat, corn, chickens, cows, pharmaceuticals, silk, mahogany.

But, of course, the applications that we might find in the living digital world would not be material, they would be information processes.

The Emergence of a “Natural”Artificial Intelligence

It is possible that out of this digital nature,there might emerge a digital intelligence,truly rooted in the nature of the medium,rather than brutishly copied and

downloaded from organic nature.It would be a fundamentally alien

intelligence,but one which would complement rather

than duplicate our talents and abilities

Evolution of Digital Organisms

Evolution in the Organic Medium

Evolution by natural selection on Earth has organized the form and process of matter and energy from the molecular level up through the ecosystem level

~ 12 Orders of Magnitude

The organization generated by evolution spans about twelve orders of magnitude of scale

from the molecular to the ecosystem level

Each Level of Scale

At each level of scale, there are richly organized structures and processes

Hierarchical

At each level of scale, the structures are built hierarchically from the structures of the level below

Built by Evolution

All of this rich hierarchically organized structure through twelve orders of magnitude of scale,

was built by the process of evolution by natural selection embedded in the medium of carbon chemistry.

Other Planets – Other Media

However, in theory, the process of evolution is neither limited to occurring on the Earth, nor in carbon chemistry.

Just as it may occur on other planets, it may also operate in other media, such as the medium of digital computation.

And just as evolution on other planets is not a model of life on Earth, nor is natural evolution in the digital medium.

A Different Physics

The digital medium is not a material medium.

It is a logical, informational medium.The digital medium does not exhibit the

laws of thermodynamics.Cyberspace is not a 3D Euclidean space.We are not constrained by the same laws of

physics, unless we impose them upon ourselves.

Evolution Sees the Medium

Evolutions sees the medium that it is embedded in.

In the organic medium, evolutions sees the laws of conventional chemistry and physics.

In the digital medium, evolution sees the logic of the machine code, the rules of the operating system, and the structure of memory,

as a surrogate physics and chemistry.

The Hardware is Invisible

Embedded within the digital medium, evolution can not see the hardware from which the computer is constructed.

Mechanical switches, vacuum tubes, transistors, integrated circuits,

all look the same to evolution if they implement the same logic.

Evolution only sees the logic.

Digital Time

A computer built from integrated circuits will be faster than one built from mechanical switches.

But the unit of time is the CPU clock cycle.From within the digital medium, evolution

can not tell if it is a second or a nanosecond

Topology of Cyberspace

Cyberspace is not a Euclidean space.There is no obvious distance metric.How can we analyze the topology?

Time is Distance?

The time that it takes to move data between two points might serve as a distance metric.

Within the (flat) RAM memory of a single computer, all pairs of points are equidistant.

Points in cache memory are closer together.Points on disk memory are farther apart.Distances between machines depend on

network topology and traffic conditions.

Conditions for Darwinian Evolution

Self-replicating entitiesTurn-over of generationsGenetic inheritanceGenetic variation

Ancestor

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

save registers to stack1010

move [bx] -> [ax]decrement cx

if cx == 0 jump 0100increment ax & bx

jump 01011011

restore registersreturn1110

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

Copy Procedure1100

Ancestor

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

save registers to stack1010

move [bx] -> [ax]decrement cx

if cx == 0 jump 0100increment ax & bx

jump 01011011

restore registersreturn1110

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

Copy Procedure1100

Ancestor

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

save registers to stack1010

move [bx] -> [ax]decrement cx

if cx == 0 jump 0100increment ax & bx

jump 01011011

restore registersreturn1110

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

Copy Procedure1100

Ancestor

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

save registers to stack1010

move [bx] -> [ax]decrement cx

if cx == 0 jump 0100increment ax & bx

jump 01011011

restore registersreturn1110

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

Copy Procedure1110

Parasite

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

1110

Ancestor

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

save registers to stack1010

move [bx] -> [ax]decrement cx

if cx == 0 jump 0100increment ax & bx

jump 01011011

restore registersreturn1110

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

Copy Procedure1100

Parasite

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

1110

Hyper-parasite

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

1010move [bx] -> [ax]

decrement cxif cx == 0 jumpb 1100

increment ax & bxjumpb 0101

1110

allocate daughter -> axcall 0011 (copy procedure)

cell divisionjumpb 0000

Reproduction Loop

Copy Procedure1100

Parasite

Self-exam1111

find 0000 (start) -> bxfind 0001 (end) -> axcalculate size -> cx

1101allocate daughter -> ax

call 0011 (copy procedure)cell divisionjump 0010

Reproduction Loop

1110

Social Hyper-parasite Self-exam110

find 001 (start) -> bxfind 000 (end) -> axcalculate size -> cx

1010move [bx] -> [ax]

decrement cxif cx == 0 jumpb 110increment ax & bx

jumpb 0101111

allocate daughter -> axcall 001 (copy procedure)

cell divisionjumpb 010

Reproduction Loop

Copy Procedure1100

1010move [bx] -> [ax]

decrement cxif cx == 0 jumpb 110increment ax & bx

jumpb 0101111

Self-exam110

find 001 (start) -> bxfind 000 (end) -> axcalculate size -> cx

1010move [bx] -> [ax]

decrement cxif cx == 0 jumpb 110increment ax & bx

jumpb 0101111

allocate daughter -> axcall 001 (copy procedure)

cell divisionjumpb 010

Reproduction Loop

Copy Procedure1100

1010move [bx] -> [ax]

decrement cxif cx == 0 jumpb 110increment ax & bx

jumpb 0101111

Self-exam110

find 001 (start) -> bxfind 000 (end) -> axcalculate size -> cx

allocate daughter -> axcall 0011 (copy procedure)

cell divisionjump 111

Reproduction Loop

Cheater

Emergence of Sex

When I turned off mutations to stop evolution,

the system continued to evolve.Spontaneously emergent sex continued to

create genetic changes.It was a kind of “sex with the dead”

resulting from parasitism gone wrong.

Evolution of DifferentiatedMulti-threaded Digital Organisms

Tom Ray and Joseph Hart

ATR, Kyoto, Japan

0123

billion years before present

com

plex

ity

ATR Japan

EPFL Switzerland

SFI USA

Chemnitz Germany

Cogs UK

VUB BelgiumAizu Japan

UDEL USA

Banff Canada

cell lineage of network ancestor

R S

reproductivetissue sensory tissue

Development of Ancestor

sel dif rep cop dev sen

senRsenAsenYsenScopSrepLrepS

copL senO

copC

561821 46 13 139

27

22521236122243

13

12 17

sel dif rep cop dev sen

senRsenAsenYsenScopSrepLrepS

copL senO

copC

561821 46 13 139

27

22521236122243

13

12 17

cell lineage of network ancestor

R S

reproductivetissue sensory tissue

ATR Japan

EPFL Switzerland

SFI USA

Chemnitz Germany

Cogs UK

VUB BelgiumAizu Japan

UDEL USA

Banff Canada

Tping Sensory Data

Int FecundityAvg;Int Speed;Int NumCells;Int AgeAvg;Int SoupSize;Int TransitTime;Int Fresh;Int Time;Int InstExec;Int InstExecConnect;Int OS;

struct TPingData{

};

Evolution of Multi-CelledDigital Organisms, Old

evolution

cell lineage of evolved network organism

reproductive tissue

Evolution of Multi-CelledDigital Organisms, New

evolution

cell lineage of new evolved network organism

R S

sensory tissuereproductive tissue

cell lineage of new evolved network organism

R S

sensory tissuereproductive tissue

sel dif rep copA copB dev sen

sel dif rep cop dev sen

duplication ofcop gene

differential expression of duplicated genes

Development of Ancestor

Evolution of New Sensory Tissues

evolution

Evolution of New Sensory Tissues

400100

The EndThis presentation:http://www.hip.atr.co.jp/~ray/pubs/pubs.html

Tierra Home Page: http://www.hip.atr.co.jp/~ray/tierra/tierra.html

Tom Ray: tray@ou.edu http://www.hip.atr.co.jp/~ray/

dev

copS

copL

sen

copS

repL

repS

sel17

0

25

49

58

96100

202

cell lineage of 8313aaa

structure of 8313aaa

genome (4352) un (3961)

genetic map of 8313aaa125/4352 = 2.9%

devcoprepsel mig div

copLcopSrepLrepS

genetic map of 8313aaa (4352)

13344232

13 29 22

12

3 1

36 160 13 422 2174

devcoprepsel mig div13344232 3 1

cop

dev

gene promotion in 8313aaa

Table 1: Genetic Change in each gene of seven genomes

sel dif rep repS repL cop copS copL copC dev sen senS senO senY senA senRrun age 21 18 56 13 43 46 22 12 12 14 144 41 17 12 52 22

1 11 0 0 27 0 35 11 5 25 8 7 31 22 147 17 13 92 6 0 0 25 0 33 28 0 100 8 0 49 22 *59 *58 *63 *553 8 10 6 23 0 30 20 14 17 33 0 33 46 18 42 15 594 9 14 0 61 8 77 13 0 50 0 0 13 17 29 33 2 95 6 29 6 27 15 30 50 9 158 17 0 29 34 29 33 23 326 6 10 0 13 0 16 4 0 8 8 0 78 22 -- -- -- --7 14 19 0 29 0 37 35 14 50 58 0 54 34 -- -- 25 --

Left columns are the run number, and age of the genome in days. Top row is the name of each of the six genes and ten sub-genes. Second row is the size of thegene in the ancestor. Remaining rows are the percentage change in the gene. * indicates that the gene is present in the genome, but is not expressed. – indicatesthat the gene has been lost from the genome.

Table 2: Sources of Genetic Change

Genetic Operation Number ofEvents

BytesAffected

mutation 263 263one-byte-insertion 9 9one-byte-deletion 15 15multi-byte-insertion 20 154multi-byte-deletion 11 64rearrangement 2 83end-loss 2 125

Heterogeneity of genetic change

The copL gene makes up 4% of the genomebut it retained 55% of the multi-byte-

insertions

R S

sel

dif

senS

dev

repS

repL

copS

dev

67

58

63

525048

44

40

35

25

15

10

0cell lineage of 0960aaa

1395aaj

sel dif rep copA copB dev sen

0960aaa

sel dif rep cop dev sen

duplication ofcop gene

sel dif rep copA copB dev sen

differential expression of duplicated genes

data (512)genome (320) un (128)

structure of 0960aaa

… what hep humorists here are already calling“Critical Mass” (get it? Not too many did in1945, the Cosmic Bomb was still trembling in itsearliness, not yet revealed to the People, so youheard the term only in the very superhepcat-to-hepcat exchanges).

- Thomas Pynchon, Gravity’s Rainbow

ATR Japan

EPFL Switzerland

SFI USA

Aizu Japan

Chemnitz Germany

Cogs UKUDEL USA

Banff Canada

VUB Belgium

Optimizations in Tierra

Most Successful Genotypes

Letter Time Genotype Max. Frequency

ABCDEFGHIJ

117166245313369542561683794866

39aab37aaf70aac36aaj38aan27aaj23abg29aae29aab24aar

0.250.300.200.250.210.210.340.240.230.33

Comparison of Optimizations in four Instruction Sets

Set Ancestor R0 R1 R2 R3 R4 R5 R6 R7 Avg. Opt. Max. OptI1I2I3I4

73949382

27545426

27573723

26543423

22553626

604935

565324

575443

554023

.35

.60

.48

.34

.30

.57

.37

.28

Size, Efficiency, & Complexity

Run Genotype Efficiency UnrollingR6R4R3R5R2R1R7R0RX

43crg35bfj26ayz24aah23awn23api23aod26abk82aaa

3.333.493.733.964.965.045.095.198.39

332211111

Copy loop of 80aaa10 instructions executed per loop

nop_1 ; copy loop templatenop_0 ; copy loop templatenop_1 ; copy loop templatenop_0 ; copy loop templatemov_iab ; copy from [bx] to [ax]dec_c ; decrement cxif_cz ; if cx != 0 skip next instructionjmp ; jump to template below (exit)nop_0 ; copy procedure exit complimentnop_1 ; copy procedure exit complimentnop_0 ; copy procedure exit complimentnop_0 ; copy procedure exit complimentinc_a ; increment ax (in daughter)inc_b ; increment bx (in mother)jmp ; jump to template below (copy loop)nop_0 ; copy loop complimentnop_1 ; copy loop complimentnop_0 ; copy loop complimentnop_1 ; copy loop compliment

Copy loop of 72etq6 instructions per copy, 18 per loopshl ; shift left cxmal ; allocate daughter cellnop_0 ; top of loopmov_iab ; copy instructiondec_c ; decrement cxdec_c ; decrement cxjmpb ; junkdec_c ; decrement cxinc_a ; increment axinc_b ; increment bxmov_iab ; copy instructiondec_c ; decrement cxinc_a ; increment axinc_b ; increment bxmov_iab ; copy instructiondec_c ; decrement cxor1 ; flip low order bit of cxif_cz ; if cx != 0 skip next instructionret ; exit loopinc_a ; increment axinc_b ; increment bxjmpb ; go to top of loopnop_1 ; bottom of loop

Zen of Evolution

Evolution may find the true nature of the digital medium by “becoming one” with it, the Zen of digital life

sel dif rep cop dev sen561821 46 13 139

27

cop

dev

cop

dev

dev

gene promotion in 0960aaa

x

162449586367701030

10351039

1045

1066

1075

10801084

repS

dif

repL

copS

dev

copS

copL

copC

repL

copS

dev

divide

reproductive cell lineage of 0960aaa

x

16

24

49

58

636770

1030

10351039

1045

1066

1075

10801084

repS

dif

repL

copS

devcopScopL

copC

repL

copS

dev

divide

reproductive cell lineage of 0960aaa

sensory cycle cell lineage in 0960aaa22

365

474

4259

157183

219

303329

448

510

sendev

sen

copdev

cop

sen

copdevcop

sen

copdevcop

sen

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