СИНГУЛЯРНОСТЬ ЭВОЛЮЦИИ И

БУДУЩЕЕ ФУНДАМЕНТАЛЬНОЙ НАУКИ

А.Д. Панов, МГУ, Москва, Россия

THE SINGULARITY OF EVOLUTION AND

THE FUTURE OF THE FUNDAMENTAL SCIENCE

A.D. Panov, MSU, Moscow, Russia

The evolution is an accelerating process.

The singularity of evolution is a point of time where the predicted rate

of evolution formally tends to infinityand simple extrapolations behind this

point are impossible

Various ways to the singularity of evolution.1. The demographic singularity.

H. von Foerster, P. Mora, L. Amiot.

Doomsday: Friday, 13 November, A.D. 2026

Science, 1960, V.132, p.1291

t* = 2026

I. S. Shklovsky.

The Universe, Life, Intelligence.

1965.

t* = 2030

The hyperbolic law of the growth

of the Earth population

t* - the point of singularity

I.S. Shklovsky,

1965

Various ways to the singularity of evolution.2. The technological singularity.

http://en.wikipedia.org/wiki/File:PPTExponentialGrowthof_Computing.jpg

Irving John Good, 1965 -

intelligence explosion

Vernor Vinge, 1988 -

technological singularity,

2005-2030

Hans Moravec, 1988 -

technological singularity,

2030-2040

Raymond Kurzweil, 1990th -

technological singularity,

2045

Smarter-than-human intelligence

prediction of future is

impossible

Various ways to the singularity of evolution.3. General singularity of evolution.

Graem Snooks, 1996: The evolution of the biosphere and then the evolution of the humankind is a joint accelerating process

expressed in terms of 'waves of life' with the acceleration factor ~3.0

Brain andhumankindevolution

Ray Kurzweil, 2001The Law of Accelerating Returns.

'Paradigm shifts‘ unitethe biological and thesocial evolution intoone chain.

General singularity of evolution.

General singularity of evolution.

8 phase transitions inhumankind history fromI.M. Diakonov, 1994.

Historical singularity -was predicted but the position in time was notcalculated

General singularity of evolution.S.P. Kapitsa, 1996 Mustier Acheul Chell Palaeolithic revolution Anthropogene

A.D. Panov, 2005 All biological points

t* = 2004 y. - all pointst* = 2015 y. - A.D. points

Properties ofphase transitions: - overcome of evolution crises (endo-exogenic,

thechno-humanitarian) - using of superfluous variety factors - Sedov's law of hierarchical compensations

General singularity of evolution.

The singularity is not a point -

it is a period of time,

approximately from 2000 to 2050.

The law of all planetary evolution from

the origin of life must be changed

during the period of singularity -

the 'weight' of the present time is

comparable with the 'weight' of origin

of life.

Any exact predictions over the

singularity based only on the

scale-invariant law of evolution

before the singularity is impossible.t* ~ 2000-2050

Post-singular evolution

+ What may be a base for

predictions?

+ The singularity is a region of

concentration of crises.

+ If the humankind survives after

the singularity, all crises must

be compensated.

+ Numerous of 'compensators'

must be supported

permanently after the

singularity point SUCH A LIFE IS NOT EASY!

Examples of post-singulartroubles:Depletion of mineral resources closed-circuit production

Depletion of fossil fuels renewable energy sources,

thermonuclear energy

Environmental protection general humanization,

possible prohibition of

experiments on any animals,

Other prohibitions (web etc.)

The rate of exploration of outer

space in XXI has slowed down

dramatically compared to the

XX century humankind will be restricted

by mainly planetary evolution

during a number of decades

or even more

.

Information crisis (S. Lem) and the future of science.(Is the future civilization 'a civilization of science'?)

+ Progressiveness is limited in time

for any evolution factor. The law

of leadership change.

+ The science is a typical progressive

factor of the evolution:

- Science method is related to industrial

revolution of XV-XVI century (resolution

of agrarian crisis of Middle Ages)

- The ancient mathematics and astronomy –

the factor of surplus variety

- The science became a leader in formation of

the vector of evolution of the civilization

+ Conclusion: the science could not be

eternal leader of the evolution (???)

+ Sedov’s law a change the place of

science in the social history in the future.

We should expect signs of a

crisis in the science.

Stanislav Lem (1963)+ Each solved problem bears a number

of new unsolved scientific problems + Number of problems grow exponentially,

but the number of scientists is restricted + There is a lack of scientists to study

all actual problems + 'Disrupt' of the front of science -

Information crisis(predicted to the beginning of XXI c in 1963)

A sort of a lack of resources!

Resource restriction and possible collapse

of funding of fundamental science (micro world and cosmos)

During accumulation of the science knowledge about the Nature,

new fundamental knowledge become more and more expensive.

More and more perfect methods and innovations cannot solve the

problem of the cost rising of the fundamental science.

Examples:

Larger and larger accelerators of particles (like LHC)

Larger and larger telescopes (cosmic and ground)

However the resources (number of scientists, money)

are restricted from the top.

Stabilization of the funding of science implicates reduction

of the amount of discoveriesdue to increase of mean cost

of one discovery

Reduction of the amount ofdiscoveries implicatesdecrease of interest of

the society to the fundamentalscience

Decrease of interest of thesociety to the fundamental

science implicates decreaseof funding of science

Decrease of fundingimplicates further reductionof the amount of discoveries

Positive feedbackloop

Collapse offunding

Positive feedback loop could produce collapse of funding

Crisis of loss of interest to the science

Mathematical model of the dynamics of

science. Step 5 years recurrent model.

Predictions of the model

(January 2006)

The absolute funding of science increases

but the upper level is restricted.

The number of discoveries increases

due to funding increasing, but

then begin to decrease due to

increasing of the cost of one

discovery.

There is interval of time where the

funding increases but the number of

discoveries decreases.

The final collapse of funding (near t ~ 500)

is a result of positive feedback loop

Number of

papers per year

1817-2010

http://www.wired.com/wiredscience/2011/03/best-science-maps?pid=1052 - from M'hamed el Aisati

1817 2010

Information

revolution,

1950

http://www.nsf.gov/statistics/nsf11313/

USA science funding

After 2006

the number of

papers decreases

for the first time in

all science history.

But funding of

science increases

The dynamics of electronic papers

(arXiv, http://arxiv.org/ )

Increasing of funding of science

A 'paradoxical' result: increasing of

funding implicates more early collapse

of funding of science with almost the same

total sum of results as for lower funding.

A practical example:

Freezing of funding of SSC collider

in USA and particle physics on

circle colliders

Increasing of funding of science 'brings the future closer' and makes it more safe.

Could Artificial Intelligence (AI) compensate the crisis of science?

= Information crisis (Stanislav Lem)

= Crisis of loss of interest to the science

= Resource crisis of science

Could AI-robots compensate a lack of number

of alive scientists?

Could AI 'grow knowledge' instead of study of nature

with real experiments?

...........

The Moor's law and AI capabilities

A prediction that AI will

'exceed human mind in

all parameters' is based

mainly on Moor's law.

1. A question:

Is the estimation of brain’s

rate correct? An amoeba

has comlicated behavior,

but it has not neurons at all.

The amoeba’s thinking is

molecular, whit is the rate?

2. Actually the Moor's law

provide only necessary

but not sufficient condition

for AI to exceed human

mind in all parameters.

За прошедшие 15 лет «разум» наших

электронных вычислительных машин

улучшился в миллион раз... В течение

нескольких следующих десятилетий

следует ожидать увеличения

характеристик «разума» машин еще

по крайней мере в несколько

десятков тысяч раз. «Разум» таких

машин по основным параметрам

будет заведомо превосходить разум

человека.

The «mind» of our computers was

improved million times during the last

15 years... A new improvement of

computer's «mind» no less than a

number of thousand times more

should be expected within the nearest

decades. The «mind» of such computers

will definitely overcome the human

mind in basic parameters.

I.S. Shklovsky, 1975И.С. Шкловский, 1975

37 years have passed! An improvement about million times since 1975 took place.

Where are the expected computers to overcome human mind?

The necessary and sufficient condition for computers to overcome human mind in all respects

is sufficiently fast and powerful hardware (Moor’s law)together with software that can reproduce human’s mode of reasoning.

But software is much more conservative than hardware.

What is a source of mistake in predictions?

maxima — one of the better systems of analytical computing now.

A classical AI system (heuristic programming).

Was written in 1972, 40 years ago.

Computer power was improved more than one million times.

Many other contemporary systems of analytical computing

have same core.

Microsoft Word — windows version was written in 1989, 23 years ago.

Computer power was improved about 105 times.

No changes in main functions of the Word system up to now.

The main system of documents preparation in the world now.

Computer translators from foreign languages — now are almost so feeble as

at the beginning of 1990th were Computer power was improved about 105 times after 22 years.

Main AI technologies:•Neural network•Heuristic programming•Expert systems•Evolutionary programming

All are known sincelate 1950-th - early 1960-th(more than 50 years no essential news)

It is unknown what is the human’s understanding.Nobody know exactly what problem should be solved to reproduce human’s understanding.A problem could not be solved if it was not formulated.

There is hard stagnation in the field of AI programming ideas.

•A computer operates with information.•A man operates with meanings.•It is supposed by default that human meanings

may be represented in information terms.•But nobody proved that human meanings actually

may be represented in information terms.

One possible counter-example:

If meanings are represented in brain by quantum states (not classical bit-like states) than meanings are not represented in

information terms, since such states have not properies of information:- information is something that can be copied (duplicated)

- quantum states is something that cannot be copied due tono-cloning theorem of quantum theory.

Quantum state is not information.

Real situation might be (and possibly is) even much more complicated

What is a source of troubles?

Rodger Penrose’s no-go theorem for AI

Theorem:Any finite computer system constructed with usage of any known physical principles cannot reproduce some special mathematical capabilities of a human mind.

Corollary 1: Operation of human mind is based on unknown physical principles

Corollary 2:To reproduce or overcome human mind with computer one should discover somenew physical principle(s) and construct a ‘computer’ system based on it.

Penrose’s hypothesis: new unknownprinciples related to quantum gravity.

The rough idea of proof:The theorem is similar to the Noether’s incompleteness theorem.A finite computer system is described like a finite system of ‘axioms’. Then there exist Noether’s propositions that may not be deduced in the system but can be understood by a human mind.

Nobody could predict when and whether the new required principles will be discovered. Therefore nobody could predict when a computer could overcome human mind.

The collapse of fundamental science funding might prevent the discovery of this new principles at all.

Contemporary direction of evolution of AI is not at all one to overcome human mind in all respects.

Rather, the actual direction is to integrate the humankind into one unit information system.

AI is only an instrument in man’s hands in this context.

The acivements in this direction are actually huge:- online-communications and virtual societies- fast search and indexing of information in the web- direct network democracy become compete with

usual representative democracy

“Towers and the Moon” metaphor

My private opinion: AI alone may not overcome possible crisis of science.

It may be used only as a kind of an instrument.However, I can’t propose any absolutely firm way

to overcome this crisis…

But there are a number of other possibilities to discuss in this respect.

Thank youfor attention!