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Alexander Panov, astrophysicist, author of "Snooks-Panov curve" which describes the singularity, for Global Future 2045 Congress.
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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
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!