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© 2010, Imagination Engines, Inc.
Boldly Innovating Innovation via Creative Machine
Intelligence(A Feigned Retreat from Complexity)
Stephen L. Thaler, Ph.D.President & CEO,
Imagination Engines, Inc.and
Founder,In Its Image, Inc.
Innovation Demands Boldness Scottsdale, AZ ● 30 September, 2010
__________________________________
A radically new form of totally self-organizing, autonomous,contemplative, and creative machine intelligence may possibly bethe poster child for all disruptive technologies since it may, bydefinition, generate all subsequent technologies. The lessonscumulatively learned from the advancement of what might arguablybe called the “ultimate idea” should be especially interesting to thisworkshop since the approaches used have boldly exploited thecurrent retreat from complexity, bypassed conventional reviewmethods, and harnessed the concept’s inherent disruptiveness,both technologically and philosophically, as an extremely effectivemarketing vehicle.
Simple & Elegant
A noise-driven dialog between at least two artificial neural networks generates new ideas.
Makes Itself Arbitrarily Complex
Self-organization inherent to artificial neural networks makes this so.
Scalable Machine Intelligence
& Consciousness
Neural brainstorming session is the basis of human cognition.
Is that all there is?
Requires utmost boldness to advance, realizing its philosophical implications.
Creativity Machine®
Paradigm
© 2010, Imagination Engines, Inc.
The Ultimate Idea…because it generates all others!
hopping synaptic perturbations
ideas
opinions
© 2010, Imagination Engines, Inc.
THE PERCEPTRONraw environmental input patterns
associated output patterns(i.e., opinions)
© 2010, Imagination Engines, Inc.
THE IMAGITRON
0
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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
P mem
, pro
babi
lity
of a
ctiv
atin
g a
mem
ory
mem
orie
smemories + confabulations
optimal memory generation rate
highest constraint satisfaction by confabulations
wi’ – wi i = 1
N
( )2
N
root-mean-square transient synaptic fluctuation
input
output
wi = ith weightN = no. of weights
© 2010, Imagination Engines, Inc.
PERCEPTRON
opinions
IMAGITRON
potential ideas
wei
ght f
luct
uatio
ns
auxiliary sensory inputs• Imagitron quickly absorbs “Zen” of
conceptual space, without human involvement.
• Perceptron quickly learns to form opinions about novel patterns emerging from imagitron, without human involvement.
• Perceptron manages weight fluctuations within imagitron until solution pattern is obtained.
• Can be used to “invent significance” to raw sensory input patterns (i.e., sense making).
• Compound DAGUIs emulate juxtapositional invention, logical deduction/induction, and create theories from analogy modules.
US Patent 5,659,666, “DAGUI” (Creativity Machine Paradigm)
DEVICE FOR THE AUTONOMOUS GENERATIONOF USEFUL INFORMATION (DAGUI)
© 2010, Imagination Engines, Inc.
SELF-TRAINING ARTIFICIAL NEURAL NETWORK OBJECT (STANNO)
• No explicit, human-conceived training algorithm.
• Trainer absorbed into trainee so as to create a monolithic neural net capable of autonomously learning.
• Class wrapper supplied to produce most efficient object-oriented neural net in world.
• 10 million attribute networks enabled for PCs and GPUs, completing training cycles on millisecond time scales.
• At core of extremely advanced automotive machine vision systems.
• Automates DAGUIs by allowing component nets to learn from successes and failures.
wei
ght u
pdat
es
TRAINER
weight update strategy
TRAINEE
error patterns
data patterns
US Patent 5,845,271, “Non-Algorithmically Implemented ANNs…”
© 2010, Imagination Engines, Inc.
DEVICE FOR THE AUTONOMOUS BOOTSTRAPPINGOF USEFUL INFORMATION (DABUI)
STANNO-BASED PERCEPTRON
opinions
STANNO-BASED IMAGITRON
potential ideas
wei
ght f
luct
uatio
ns /
lear
ning
auxiliary sensory inputs• Untrained STANNO-based imagitron
generates potential idea.
• Untrained STANNO-based perceptron generates some figure of merit to it.
• If figure of merit (opinion) is sufficient, reinforcement takes place in all networks.
• If figure of merit (opinion) is insufficient, training is weakened in imagitron, with reinforcement learning occurring in perceptron.
• Bootstrapping is continued until ideas have matured.
• Thereafter, derivative ideas may be generated on demand.
US Patent 7,454,388, “DABUI”
© 2010, Imagination Engines, Inc.
SUPERNETS
US Patent 7,454,388, “DABUI”
• Any number of sensors and actuators may be tied together via an adaptive/creative synthetic brain.
• Myriad STANNO modules may interconnect into “supernets” involving self-forming group membership filters (GMF) and Creativity Machines.
• Various neural correlates to the human brain automatically form.
• Synthetic intelligence shapes itself in response to environmental and corporeal demands.
• We are skipping simulation of human brain and striving for trans-human level intelligence.
© 2010, Imagination Engines, Inc.
CREATIVE ROBOT MASTERS SAND• Main problem is
accumulating mound of sand in front of robot.
• Robot develops its own “squat and leap” strategy via underlying DABUI system.
• Side-to-side motion disperses sand accumulation.
• Behavior developed in less than two minutes, tabula rasa.
© 2010, Imagination Engines, Inc.
CREATIVE ROBOT MASTERS SOIL• Main problem
again is accumulation of soil in front of robot.
• DABUI system develops its own strategy for crawling through potting soil, leveling material with front legs, while thrusting with rear legs.
• Behavior developed in less than a minute!
© 2010, Imagination Engines, Inc.
CREATIVE ROBOT LEARNS TO DREAD ROCKS• Main problem is
non-deterministic behavior of rock beneath robot.
• DABUI system develops a strategy of stabilization within the rock through in-place rocking, so that legs penetrate as deeply as possible.
• Garden rock definitely offers a higher crawling impedance than sand or soil.
© 2010, Imagination Engines, Inc.
CONTEMPLATIVE TERRAIN-SENSING ROBOTS
high impedancerock patch
target
• Vision pathways, navigation field generators, creative motor control, and path optimization modules knit themselves together into a single Supernet.
• Robot contemplates terrain, decides upon path of least resistance, and selects appropriate gaits along way to reach target, avoiding rocky patch.
© 2010, Imagination Engines, Inc.
low impedancesand patch
target
CONTEMPLATIVE TERRAIN-SENSING ROBOTS• When rocky
patch is replaced by sand, DABUI-based control system picks a more direct route toward the target on left.
• Project was reborn as autonomous rendezvous and docking for NASA.
• Later, off-world robots prototyped for NASA, utilizing tabula rasa behavioral development.
© 2010, Imagination Engines, Inc.
STIFF CHALLENGES / BOLD SOLUTIONS
• Retreat from Complexity– Emphasize simplicity and
elegance.• Disruptive Technology
– Identify proper point of entry into industry.
• Academic Adaptation– Treat university researchers as
esteemed knowledge workers.• Timid Incrementalism
– Seek out the more visionary “man in uniform.”
• Poverty of Imagination– Stimulate imagination via potential
applications and the viability of machine consciousness.
cortical imagitron
thalamic perceptron
© 2010, Imagination Engines, Inc.
• “let a thousand flowers bloom”– Allowed IEI in door.– There is vast duplication of
effort.• Grand Challenge / X-Prizes
– Small companies with limited budgets and vanguard technologies can’t afford to drop everything.
– Too many simplifications create overabundant competition.
– Become engineering and not scientific competitions.
• Greatest Curse– This is an unanticipated
technology that does everything.– We are drowning in the
possibilities.• There is hope in collaboration.
“grand challenges”too simplified.
STIFF CHALLENGES / BOLD SOLUTIONS
© 2010, Imagination Engines, Inc.
IEI DECADE (1997-2007) IN A NUTSHELL