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- The Age of Complexity Science
- “I am convinced that the nations and people who master the new
sciences of complexity will become the economic, cultural and political super-powers of the next century”
Heinz Pagels, The Dreams of Reason
- “I think the next century will be the century of complexity.”
- “We stand on the verge of being able to change the human race”
Wired Magazine, January ‘98
- Evolution - From Chemistry to Biology
- 2 billion years after Earth was formed - life began
- With Time, the patterns became more complicated
- from Chemistry to Biology.
- A key element of an evolutionary process is a “written record” - otherwise it would be doomed to repeat.
- DNA - the digital computer designed by Evolution
to record its handiwork.
- Evolution - Time Speeding Up
Evolution took billions of years to design the first
primitive cells - and then events took only hundreds
of millions of years. DNA is 98.6% the same as the gorilla, and 97.8% the same as orangutans.
- Dinosaurs - 65 million years ago
- Primates - Tens of millions of years.
- Humanoids - 5 millions years ago
- Homo Sapiens - 0.5 million years ago
- Technology - Evolution by other means.
Homo Sapiens - distinguished by invention of technology, and
Technology is a continuation of Evolution
- beyond the making and use of tools
- record and progression in sophistication
- requires invention.
- Multiple subspecies of Homo Sapiens - the technologically more advanced groups became dominant. Evolution is Selection through Survival.
- Evolution is an inefficient programmer
- Most of the code “does not compute”
- Most of the DNA sequences do not produce proteins.
- 97% of the code is useless.
- Active part of the code is only about 23 megabytes
(less than Microsoft Word)
- Only object code, no source code
- No programming manual, no help files, no user manual.
- Introduce changes (updates) only at random
- Changes are evaluated over time by survival,
and ability to reproduce.
- Survival appears to be a crude technique
- focussing on a few features at a time
- Evolution cannot easily perform complete re-designs.
It is stuck - in time.
- The IQ of Evolution
- Evolution has produced millions of designs.
Deficiency - it is very slow!
- Most IQ tests are timed.
The IQ of Evolution is infinitesimally above zero
- only a bit smarter than random behaviors.
- The reason that our human-sponsored evolution is “smarter” is that we speed up time.
- The Question : Can Human intelligence create an intelligence more intelligent than itself?
- The Hardware & Software of Evolution
- Software recorded as digital data in the chemical structure of an ingenious molecule called deoxyribonucleic acid - DNA - the read-only memory (ROM) that controls the vast machinery of life. Remarkably complex and amazingly simple - Only four basic pairs provide the data storage for the complexity of all the millions of life-forms on earth, from primitive bacteria to human beings.
- The ribosomes - little recorder modules - read the code
and build proteins from only 20 amino acids.
Everything is programmed from this efficient code!
- This is “nano-engineering” -
the machinery of life takes place on the atomic level.
- The 3 Technology Laws
All three laws predict exponential advances.
- Moore’s Law : Processing power doubles every 18 months
- Gilders’s Law : Bandwidth doubles every 12 months
- Metcalfe’s Law : Effectiveness increases exponentially with the number of connections
- The Law of Accelerating Returns
As Order increases, so Time speeds up.
- Technology - Accelerated Evolution
Technology, like Evolution that spawned it, is inherently an accelerating process.
- The Hardware of Intelligence
- Human brain - massive parallelism is the strength.
Slow speed is the weakness.
- DNA-based evolution will eventually need to abandoned.
Too plodding. Good at tinkering and extending, but unable to scrap a design and start-over.
- The Law of Accelerating Returns says that Evolution will not be stuck - indeed it will find a way around limitations of neural circuits - humans have invented a technology that is a million times faster than carbon-based neurons. Ultimately, we’ll port everything to faster equivalents.
- The Software of Intelligence
What is needed to build intelligent machines
- Right set of formulas - recursive search,self-organizing neural nets, evolutionary improvement algorithms.
- Knowledge - something to start with - the rest can be learned by exposure.
- Computing Substrates in the 21st Century
- 3-D integrated circuits
- Molecular Computing
- Quantum Computing
- Achieving the Hardware Capacity of the Human Brain
- Human brain - 100 billion neurons - estimated 1,000 connections between each neuron and its neighbors, 100 trillion connections, each capable of simultaneous calculation. However - only 200 calculations per second. For problems requiring massive parallelism (like pattern recognition) this is great. But, for extensive sequential thinking, the is is mediocre.
- 100 trillion connections - each 200 calcs per sec - 20 million billion calcs/sec. So, when will we see equivalent speed ?
- The Human Genome Project
- International research program
with the goal of gathering a resource of genome maps and DNA sequence information that will provide detailed information about the structure, organization and characteristics of the DNA of humans and other animals.
The project began in the mid-80’s and is expected to be complete by around 2003 (18-20 years)
- Nano-engineering - K. Eric Drexler - founding father of “nano-technology”. Use individual atoms & molecules to build machines.
- Human or Machine?
Is a human with mechanical implants a machine?
Is a machine with human extensions a human?
Different Schools of Thought
- “Consciousness is different kind of stuff”
- “We can’t understand”
- “Thinking is as Thinking does”
- Deep Blue vs Kasparov
“As Deep Blue goes deeper and deeper,
it displays elements of strategic understanding.
Somewhere out there, mere tactics
are translating into strategy.
This is the closest thing I’ve seen
to computer intelligence.
It’s a weird form of intelligence.
But, you can feel it. You can smell it!”
Frederick Friedel, assistant to Gary Kasparov,
commenting on the computer that beat his boss.
- Three types of Intelligence
- The Recursive Formula
- Neural nets
- Evolutionary (Genetic) Algorithms
- Can Intelligent Systems become self-organizing?
The essential ingredients:
- Communication (network)
- Re-programmability (by others) over the network
- Ability to change “behavior”(self-re-programming)
Based on external or internal stimuli/algorithms
- The Internet has "emergent properties"
- Everyone uses the same protocol (TCP/IP)
- Stanardized packets, moving chaotically
- Users pay for their own links
- Each node contributes and benefits
- The Internet - Planetary Brain
- The Internet is evolving spontaneously, chaotically and autocatalytically
- Each new application creates an area of complexification, amplifying the total “intelligence” of the network.
- New solutions and applications appear more quickly, catalyzing the growth of the system.
- Critical Complexity
- When does "processing power" become "intelligence" ?
- When does connected intelligence become "self-organizing" ?
- Critical Complexity
Stuart Kauffman, Santa Fe Institute :
When a system of simple inter-acting components reaches a
certain level of complexity or "inter-connectedness"
it undergoes a dramatic transition, or phase change.
- The Edge of Chaos
Chris Langton, Santa Fe Institute :
A systems computational capability peaks in a narrow regime
between highly periodic and chaotic behavior.
- Symbionomic Evolution (Joel de Rosnay)
- Agents, Links, Reproduction, Reinforcement,Network,
Chaos, Amplification, Self-selection, Organization,
Emergence, Transmission, Symbiosis
- The phenomenon of lock-in through
“autocatalysis” and self-selection demonstrates
the general process of emergence of organized
complexity such as variations, mutations,
catalysis, amplification, selection, stabilization,
self-organization and co-evolution.
- Golden-rule for breaking deadlocks
in the management of complex systems :
Reversing or combining feedback loops makes
the system go from one of diminishing returns
to one of increasing returns.
- Artificial Life
"If molecules (intelligent nodes) spontaneously organize themselves into entities that eat, reproduce, evolve(re-program, assign new tasks,
change control strategies) those entities would be “alive”.
“Neobiology” : Born at Santa Fe (Chris Langton - 1987)
Synthesis of biology, chemistry, physics, robotics,
computer science, ecology and anthropology
- Analysis had 3 Revolutions :
All these were dominated by "analysis".
- Industrial - Coal to Cars
- Information - Writing to Processing
- Biological - Mastery of DNA
- The "co-evolutionary" process
- Synthesis - The revolution of Complexity Science
Where Anaalysis and Synthesis meet - is "Chaos" - complexity science.
- Complexity Science:
- The study of emergent behavior exhibited by
interacting systems operating at the threshold of
stability and chaos.
- Artificial Life:
- A synthetic approach to studying Life-as-it-could-be
and viewing Life-as-it-is within a larger context.
- Fractals Everywhere:
- General laws exist that apply to areas as
diverse as business, markets, large organizations,
competing animal populations, insect societies, cell
development, chemical reactions, virus reproduction
and the formation of planets.
Web Hotlinks to all topics (click on any item)