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The Big Bang of Machine Intelligence!
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Brightest Technical Moments:
Diamonds - While employed as a materials scientist for aerospace giant McDonnell Douglas in 1986, Thaler invented the fastest diamond deposition technique in the world. Using high-energy lasers borrowed from the 'Star Wars' initiative, Thaler was able to grow single crystals of diamond as well as convert the native carbon within tungsten carbide and high-speed steel tools to the diamond phase. Of course, at the root of his success was the use of artificial neural networks to determine the sweet spots for diamond growth within a high-dimensional process space.
Brain Trauma and Death - In 1992, Thaler shocked the world with bizarre experiments in which the neurons within artificial neural networks were randomly destroyed. Guess what? The nets first relived all of their experiences (i.e., life review) and then, within advanced stages of destruction, generated novel experience. From this research emerged both a compelling mathematical model of near-death experience (NDE) and the basis of truly creative and contemplative artificial intelligence.
Cognition, Consciousness, and Creativity - After witnessing some really great ideas emerge from the near-death experience of artificial neural networks, Thaler decided to add additional nets to automatically observe and filter for any emerging brainstorms. From this network architecture was born the Creativity Machine (US Patent 5,659,666). Thaler has proposed such neural cascade as a canonical model of consciousness in which the former net manifests what can only be called a stream of consciousness while the second net develops an attitude about the cognitive turnover within the first net (i.e., the subjective feel of consciousness). In this theory, all aspects of both human and animal cognition are modeled in terms of confabulation generation. Thaler is therefore both the founder and architect of confabulation theory and the patent holder for all neural systems that contemplate, invent, and discover via such confabulations.
Mental Illness and Creativity - While the connection between psychopathologies and creative genius has long been suspected, Thaler has recruited the Creativity Machine Paradigm to demonstrate how cognitive pathologies develop as this contemplative neural system pushes itself toward higher levels of creative achievement. With the ability to compute both ideational novelty and cognitive pathology within these neurodynamic models, he has discovered an inevitable tradeoff between madness and inventive genius. In a nutshell, creativity occurs over multiple swings through neuronal chaos and tranquility, as ideas subliminally incubate. Typically, the more intense these swings, the more original is the creative output that is accompanied by periodic hallucinations, false perceptions, attention deficits, and an inability to differentiate fantasy from reality, all characteristic of what is considered mental illness.
The Tempo of Ideation - While several institutions attempt to build neural network-based brain simulations, none have considered how freshly forming ideas within one part of the brain are located and evaluated by other portions thereof. The methodology, Thaler claims, involves the rhythm (i.e., the frequency and clustering) with which stream of consciousness is occurring within certain pieces of the neural real estate. In fact, he has derived a master equation that quantitatively predicts the rhythm of idea generation both in Creativity Machines and the human brain, as a function of novelty of the notions being generated.
Currently, this scientist/inventor is engaged in building multi-billion neuron brain simulations that think and die just like the real thing.
Current Position: President & CEO, Imagination Engines, Inc.
Undergraduate Education: B.A. Westminster College, Summa Cum Laude, Majored in Chemistry, Physics, Mathematics, and Russian.
Graduate Education: Masters work at UCLA in chemistry, Ph.D. in physics, University of Missouri-Columbia.
Work Experience: 1973-1974, Production Chemist for Mallinckrodt Nuclear, 1981-95, Principal Technical Specialist, McDonnell Douglas, 1995-Present, President and CEO, Imagination Engines, Inc. Thaler also serves as Principal Scientist for Sytex, Inc.
Thaler has worked diverse technology areas that have included (1) nuclear radiation vulnerability and hardening, (2) high-energy laser interactions with solids, (3) electromagnetic signatures, (4) laser-driven growth of diamond and other ultra-hard materials, (4) laser ultrasonics in the non-destructive evaluation of aircraft structures, (5) the use of artificial intelligence techniques for structural monitoring, and currently (7) applied and theoretical artificial neural network technology.
Key Patents: Unclassified patents by Thaler are divided between laser-driven coating technologies and foundational neural patents that include the Creativity Machine® (U.S. 5,659,666) and Non-Algorithmically Implemented Neural` Networks.
Clientele: The past and current customer base of Thaler's technologies include
Major Applications of Thaler's Artificial Intelligence Technology:Of course, if Thaler is correct about his technology (i.e., US Patent 5,659,666) providing a working model of creative human cognition, then we can expect the application of these novel AI techniques to every aspect of human endeavor. Appropriately, all that Thaler's neural network technology can do is synonomous with all that we as humans do. Pursuing this kind of blue sky thinking, we can expect these virtual machines to engage not only in technical endeavors, but in the generation of new art and music. Further, because the imagination engine operates in the same way as human internal imagery, we can also expect this technology to lay the foundation for a radical paradigm shift in the entertainment industry. We also anticipate that the Creativity Machine® will become the major paradigm in robotic/android control schemes.
Presently realized applications of Thaler's neural network technology include:
"Daisy, Daisy" Do computers have near-death experience, Scientific American, May 1993.
Dying by design, IEEE Expert, Dec.1993.
The ghost in the machine, The Economist, 8 May 1993.
As They Lay Dying ... Near the end, artificial neural networks become creative, Scientific American, May, 1995.
Neural Networks That Create and Discover, PC AI, May/June 1996.
Creativity machine granted a patent, MSN UK News, August 1997.
The Creativity Machine, New Scientist, 20 January 1996.
Self-Training artificial Neural Networks, PC AI, Nov/Dec 1996
Computers that create: No hallucination, Aerospace America, January 1997
Attack of the Genius Robot Cockroach Swarm, DefenseTech.org, September, 2006.
Robot Restraint, Aviation Week, p11, May, 2008
Stephen Thaler's Imagination Machines, The Futurist, July-August 2009 Vol. 43.
Dr. Stephen Thaler: The Kush Interview, April 7, 2012
I am Become Death, Creator of Worlds, Eric Leech, Urbasm, May 20, 2013.
Should We Fear Artificial intelligence?, Eric Leech, Urbasm, March 31, 2016.
Artificial Intelligence - Visions (Art) of a Dying Synthetic Brain, Eric Leech, Urbasm, May 25, 2016.
Effects of Neutron Irradiation on the Raman Spectrum of Silicon, M. Chandrasekhar, H.R. Chandrasekhar, J.M. Meese and S.L. Thaler, Inst. Phys. Conf. Ser. 59, 205 (1981).
Annealing Mechanisms in Neutron Irradiated Silicon, S.L. Thaler, H.R. Chandrasekhar, M. Chandrasekhar and J.M. Meese, Physica 119B, 325 (1983)..
A Detailed Study of NTD Silicon Utilizing Raman Scattering, H.R. Chandrasekhar, M. Chandrasekhar, J.M. Meese and S.L. Thaler. Neutron Transmutation Doping of Semiconductor Materials. Ed. R.D. Larrabee (Plenum, New York, 1984) p. 287.
Neural net predicted Raman spectra of the graphite to diamond transition, Third International Symposium on Diamond Materials, Honolulu, HI, J. P. Dismukes, K. V. Ravi, K. E. Spear, B. Lux and N. Setaka (eds.), The Electrochemical Society, Inc.; Pennington, N.J., 1993, p. 773.
"Virtual Input Phenomena" Within the Death of a Simple Pattern Associator, Neural Networks, 8(1), 55-65 (1995).
Death of a gedanken creature, Journal of Near-Death Studies, 13(3), Spring 1995.
Neural Nets That Create and Discover, PC AI , May/June, 16-21, 1996.
Is Neuronal Chaos the Source of Stream of Consciousness? In Proceedings of the World Congress on Neural Networks, (WCNN'96), Lawrence Erlbaum, Mawah, NJ.
A Proposed Symbolism for Network-Implemented Discovery Processes, In Proceedings of the World Congress on Neural Networks, (WCNN'96), Lawrence Erlbaum, Mawah, NJ.
Autonomous Materials Discovery Via Spreadsheet-Implemented Neural Network Cascades, Journal of the Minerals, Metals, and Materials Society, JOM-e, 49(4) (1997).
Creativity via network cavitation - an architecture, implementation, and results, Adaptive Distributive Parallel Computing Symposium, Dayton, Ohio, 8-9 August, 1996.
Principles and application of the self-training artificial neural network, Adaptive Distributive Parallel Computing Symposium, Dayton, Ohio, 8-9 August, 1996.
"Databots", Adaptive Distributive Parallel Computing Symposium, Dayton, Ohio, 8-9 August, 1996.
Self-Training artificial Neural Networks, PC AI, Nov/Dec 1996.
The death dream and near-death darwinism, Journal of Near-Death Studies, 15(1), Fall 1996.
The fragmentation of the universe and the devolution of consciousness, U.S. Library of Congress, Registration Number TXu000775586 / January, 1997.
A quantitative model of seminal cognition: the creativity machine paradigm, Proceedings of the Mind II Conference, Dublin, Ireland, 1997.
Predicting ultra-hard binary compounds via cascaded auto- and hetero-associative neural newtorks, Journal of Alloys and Compounds, 279(1998), 47-59.
With Conrad, D.M, Real-Time Fault Detection Using Auto-associative Filtering, AIRTC, Oct. '98.
The emerging intelligence and its critical look at us, Journal of Near-Death Studies, 17(1), Fall 1998.
The Warhead Design Creativity Machine, Weapon Systems Technology Information Analysis Center, Volume 3, Number 1, December 2001.
LITMUS - Live Intrusion Tracking via Multiple Unsupervised STANNOs, PC AI, Jan/Feb 2002.
Neural Networks 101 - Servo Magazine, April, 2005.
With Furrer, D., Neural Network Modeling, Advanced Materials & Processes, Nov. 2005.
With Patrick, M. Clinton and Chavis, Katherine S., "Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations," 2007 IEEE Aerospace Conference Proceedings, IEEEAC paper #1409, March 2007.
Thalamocortical Algorithms in Space! The Building of Conscious Machines and the Lessons Thereof, In the Proceedings of World Future 2010: Sustainable Futures, Strategies, and Technologies, July 8-10, 2010, Boston, MA.
The Creativity Machine Paradigm: Withstanding the Argument from Consciousness, APA Newsletters, Volume 11, Number 2, Spring 2012.
With Ryan, S., Artificial Neural Networks for Characterizing Armor Performance, The 12th Hypervelocity Impact Symposium, Elsevier, 2012.
With Ryan, S., Artificial Neural Networks for Characterising Whipple Shield Performance, International Journal of Impact Engineering, Elsevier, 2012.
The Creativity Machine Paradigm, Encyclopedia of Creativity, Invention, Innovation, and Entrepreneurship, (ed.) E.G. Carayannis, Springer Science+Business Media, LLC, 2013.
Lessons from connectionism in differentiating knowledge, "e-mentor" 2014, nr 3 (55), s. 81-86.
Synaptic Perturbation and Consciousness, International Journal of Machine Consciousness, Vol. 06, No. 02, pp. 75-107, 2014.
With Ryan, S. and Kandanaarachchi, S., Machine Learning Methods for Predicting the Outcome of Hypervelocity Impact Events, Expert Systems with Applications, 45: 23-39, Elsevier, 2016.
With Hoyt, R., Linnville, S., and Moore, J., Digital Family History Data Mining with Neural Networks: A Pilot Study, Perspectives in Health Information Management / AHIMA, American Health Information Management Association, Winter(2016).
Cycles of Insanity and Creativity within Contemplative Neural Systems, Medical Hypotheses, 94:138-147, Elsevier, 2016.
Pattern Turnover within Synaptically Perturbed Neural Systems, Procedia Computer Science, 88, Elsevier, 2016.
A neurodynamic model linking creativity and insanity, Atlas of Science, 2017
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