Steve Omohundro

From Wikipedia, the free encyclopedia
Jump to: navigation, search
Steve Omohundro (2010)

Stephen M. Omohundro (born 1959) is an American scientist known for his research on Hamiltonian physics, dynamical systems, programming languages, machine learning, machine vision, and the social implications of artificial intelligence. His current work uses rational economics to develop safe and beneficial intelligent technologies for better collaborative modeling, understanding, innovation, and decision making.

Education[edit]

Omohundro earned degrees in physics and mathematics from Stanford University and a Ph.D. in physics from the University of California, Berkeley.

Learning algorithms[edit]

Efficient geometric learning algorithms[edit]

Omohundro was one of the first to recognize the importance of machine learning for machine vision and started the "Vision and Learning Group" at the University of Illinois which produced 4 Masters and 2 Ph.D. theses. He developed a number of efficient geometric algorithms for speeding up neural network, machine learning, machine vision, and graphics tasks, several of which are widely used.[1][2] Omohundro created numerous algorithms based on k-d trees,[3] invented the powerful balltree and boxtree geometric data structures.,[4][5] and invented the powerful bumptree structure,[6] which dramatically speeds up Gaussian mixture based neural network algorithms and produced a factor of 50 speedup on a robotics task.

Manifold learning and lipreading[edit]

Omohundro invented the general and widely used manifold learning task and introduced several algorithms for accomplishing this task.[7] Omohundro, Chris Bregler and others extended these ideas and applied them to a wide range of visual learning and modelling tasks.[8][9][10][11][12][13][14]

Model merging and grammar learning[edit]

Omohundro invented the Best-first model merging approach to machine learning.[15] Omohundro and Andreas Stolcke applied this model to learning stochastic grammars. Their approach was very successful in learning Hidden Markov Models and Stochastic Context-free Grammars and is now widely used.[16][17][18]

Family Discovery Learning Algorithm[edit]

Steve Omohundro

Omohundro developed the Family Discovery Learning Algorithm, which discovers the dimension and structure of a parameterized family of stochastic models.[19]

Self-improving artificial lntelligence and AI safety[edit]

Omohundro started Self-Aware Systems[20] in Palo Alto, California to research the technology and social implications of self-improving artificial intelligence. He was an advisor to the Singularity Institute for Artificial Intelligence and the Lifeboat Foundation on artificial intelligence. He argues that rational systems exhibit problematic natural "drives" that will need to be countered in order to build intelligent systems safely. His papers, talks, and videos on AI safety have generated extensive interest.[21][22] He has given many talks on self-improving artificial intelligence, cooperative technology, AI safety, and connections with biological intelligence.

Programming languages[edit]

*Lisp parallel programming language[edit]

At Thinking Machines Corporation, Cliff Lasser and Steve Omohundro developed Star Lisp, the first programming language for the Connection Machine. Omohundro also helped create the data parallel style of parallel programming and developed many parallel algorithm libraries and applications for the Connection Machine.[citation needed]

Sather programming language[edit]

Omohundro joined the International Computer Science Institute (ICSI) in Berkeley, California, where he led the development of the open source programming language Sather, which introduced a number of advances in object-oriented language design.[23][24][25][26][27][28] Sather is featured in O'Reilly's History of Programming Languages poster.[29]

Physics and dynamical systems theory[edit]

Omohundro's book Geometric Perturbation Theory in Physics[30] describes natural Hamiltonian symplectic structures for a wide range of physical models that arise from perturbation theory analyses.

He showed that there exist smooth partial differential equations which stably perform universal computation by simulating arbitrary cellular automata.[31] The asymptotic behavior of these PDEs is therefore logically undecidable.

With John David Crawford he showed that the orbits of three-dimensional period doubling systems can form an infinite number of topologically distinct torus knots and described the structure of their stable and unstable manifolds.[32]

Other contributions[edit]

Mathematica and Apple tablet contest[edit]

From 1986 to 1988, he was an Assistant Professor of Computer science at the University of Illinois at Urbana-Champaign and cofounded the Center for Complex Systems Research with Stephen Wolfram and Norman Packard. While at the University of Illinois, he worked with Stephen Wolfram and others (D. Grayson, R. Maeder, H. Cejtin, D. Ballman and J. Keiper) to create the symbolic mathematics program Mathematica. He and Stephen Wolfram led a team of students that won an Apple Computer contest to design "The Computer of the Year 2000." Their design entry "Tablet" was a touchscreen tablet with GPS and other features that finally appeared when the Apple iPad was introduced 22 years later.[33][34]

Neural models of attention[edit]

Subutai Ahmad and Steve Omohundro developed biologically realistic neural models of selective attention.[35][36][37][38]

Bayesian image database search[edit]

Omohundro became a Research scientist at the NEC Research Institute, working on machine learning and computer vision, and was a co-inventor of U.S. Patent 5,696,964, "Multimedia Database Retrieval System Which Maintains a Posterior Probability Distribution that Each Item in the Database is a Target of a Search."[39][40][41][42][43]

Pirate puzzle[edit]

Omohundro developed an intriguing extension to the game theoretic pirate puzzle that was featured in Scientific American.[44]

Gesture-based user interfaces[edit]

Omohundro and 5 others invented U.S. Patent 7,775,439 B2 "Featured Wands for Camera Calibration and as a Gesture Based 3D Interface Device."[45]

Publications[edit]

  • Christoph Bregler, Stephen Omohundro, Michelle Covell, Malcolm Slaney, Subutai Ahmad, David Forsyth, Jerry Feldman, "Probabilistic Models of Verbal and Body Gestures" in Computer Vision in Man-Machine Interfaces, eds. R. Cipolla and A. Pentland, Cambridge University Press, 1998.
  • Christoph Bregler and Stephen M. Omohundro, "Learning Visual Motion Models for Lip Reading" in Motion-Based Recognition, eds. M. Sha and R. Jain, Kluwer Academic Press, 1997.
  • Stephen M. Omohundro, "Family Discovery", in Advances in Neural Information Processing Systems 8, eds. D. S. Touretzky, M. C. Mozer and M. E. Hasselmo, MIT Press, Cambridge, MA, 1996.
  • Christoph Bregler and Stephen M. Omohundro, "Surface Learning with Applications to Lipreading", in Cowan, J. D., Tesauro, G., and Alspector, J., (eds.) Advances in Neural Information Processing Systems 6, Morgan Kaufmann Publishers, San Francisco, CA, 1994
  • Stephen M. Omohundro, "The Sather Programming Language", Dr. Dobb's Journal, Volume 18, Issue 11, October 1993, p. 42.
  • Stephen M. Omohundro, "Geometric Learning Algorithms" Physica D, 42 (1990) 307-321
  • Stephen M. Omohundro, "Modelling Cellular Automata with Partial Differential Equations", Physica D, 10D (1984) 128-134
  • Stephen M. Omohundro, "Autonomous technology and the greater human good", Journal of Experimental & Theoretical Artificial Intelligence, Published online: 10 Apr 2014.

References[edit]

  1. ^ Stephen M. Omohundro, “Geometric Learning Algorithms” Physica D, 42 (1990) 307-321
  2. ^ Stephen M. Omohundro. Emergent Computation, edited by Stephanie Forrest, MIT Press (1991) 307-321
  3. ^ Stephen M. Omohundro, “Efficient Algorithms with Neural Network Behavior”, Complex Systems 1:2 (1987) 273-347.
  4. ^ Stephen M. Omohundro, “Five Balltree Construction Algorithms“, ICSI Technical Report TR-89-063 (December 1989).
  5. ^ Stephen M. Omohundro, “The Delaunay Triangulation and Function Learning“, ICSI Technical Report TR-90-001 (January 1990).
  6. ^ Stephen M. Omohundro, “Bumptrees for Efficient Function, Constraint, and Classification Learning” in Advances in Neural Information Processing Systems 3, eds. R. P. Lippmann, J. E. Moody, D. S. Touretzky, Morgan Kaufmann Publishers, San Francisco, CA, 1991, pp. 693-699.
  7. ^ Stephen M. Omohundro, “Fundamentals of Geometric Learning.” University of Illinois at Urbana-Champaign, Department of Computer Science Technical Report UILU-ENG-88-1713 (February 1988).
  8. ^ Chris Bregler, Stephen M. Omohundro, and Yochai Konig, “A Hybrid Approach to Bimodal Speech Recognition“, Proceedings of the 28th Annual Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, November 1994.
  9. ^ Christoph Bregler and Stephen M. Omohundro, “Surface Learning with Applications to Lipreading“, in Cowan, J. D., Tesauro, G., and Alspector, J., (eds.) Advances in Neural Information Processing Systems 6, Morgan Kaufmann Publishers, San Francisco, CA, 1994, pp. 43-50. ICSI Technical Report TR-94-001.
  10. ^ Christoph Bregler and Stephen M. Omohundro, “Nonlinear Image Interpolation using Manifold Learning“, in Advances in Neural Information Processing Systems 7, eds. Gerry Tesauro, David S. Touretzky, and Todd K. Leen, MIT Press, Cambridge, MA, 1995, pp. 973-980.
  11. ^ Peter Blicher and Stephen M. Omohundro, “Unique Recovery of Motion and Optic Flow via Lie Algebras”, Proceedings of the Ninth International Joint Conference on Artificial Intelligence (1985).
  12. ^ Christoph Bregler and Stephen M. Omohundro, “Nonlinear Manifold Learning for Visual Speech Recognition“, in the Proceedings of the Fifth International Conference on Computer Vision, ed. W. Eric L. Grimson, IEEE Computer Society Press, Los Alamitos, CA, June 1995, pp. 494-499.
  13. ^ Christoph Bregler and Stephen M. Omohundro, “Learning Visual Motion Models for Lip Reading” in Motion-Based Recognition, eds. M. Sha and R. Jain, Kluwer Academic Press, 1997.
  14. ^ Christoph Bregler, Stephen Omohundro, Michelle Covell, Malcolm Slaney, Subutai Ahmad, David Forsyth, Jerry Feldman, “Probabilistic Models of Verbal and Body Gestures” in Computer Vision in Man-Machine Interfaces, eds. R. Cipolla and A. Pentland, Cambridge University Press, 1998.
  15. ^ Stephen M. Omohundro, “Best-First Model Merging for Dynamic Learning and Recognition” in Moody, J. E., Hanson, S. J., and Lippmann, R. P., (eds.) Advances in Neural Information Processing Systems 4, pp. 958-965, San Mateo, CA: Morgan Kaufmann Publishers, (1992).
  16. ^ Andreas Stolcke and Stephen M. Omohundro, “Hidden Markov Model Induction by Bayesian Model Merging“, in Advances in Neural Information Processing Systems 5, ed. Steve J. Hanson and Jack D. Cowan, J. D. and C. Lee Giles, Morgan Kaufmann Publishers, Inc., San Mateo, California, 1993, pp. 11-18.
  17. ^ Andreas Stolcke and Stephen M. Omohundro, “Best-first Model Merging for Hidden Markov Model Induction“, ICSI Technical ReportTR-94-003, January 1994.
  18. ^ Andreas Stolcke and Stephen M. Omohundro, “Inducing Probabilistic Grammars by Bayesian Model Merging“, Proceedings of the International Colloquium on Grammatical Inference, Alicante, Spain, Lecture Notes in Artificial Intelligence 862, Springer-Verlag, Berlin, September 1994, pp. 106-118.
  19. ^ Stephen M. Omohundro, “Family Discovery“, in Advances in Neural Information Processing Systems 8, eds. D. S. Touretzky, M. C. Mozer and M. E. Hasselmo, MIT Press, Cambridge, MA, 1996.
  20. ^ Self-Aware Systems
  21. ^ Stephen M. Omohundro, “The Nature of Self-Improving Artificial Intelligence“ Singularity Summit 2007, San Francisco, CA
  22. ^ Stephen M. Omohundro, “The Basic AI Drives“, in the Proceedings of the First AGI Conference, Volume 171, Frontiers in Artificial Intelligence and Applications, edited by P. Wang, B. Goertzel, and S. Franklin, February 2008, IOS Press.
  23. ^ Stephen M. Omohundro, “Sather Provides Nonproprietary Access to Object-Oriented Programming“,Computers in Physics, Vol.6, No. 5, September, 1992, p. 444-449.
  24. ^ Heinz Schmidt and Stephen M. Omohundro, “CLOS, Eiffel, and Sather: A Comparison“, in Object-Oriented Programming: The CLOS Perspective, ed. Andreas Paepcke, MIT Press, Cambridge, Massachusetts, 1993, pp. 181-213.
  25. ^ Stephen M. Omohundro, “The Sather Programming Language“, Dr. Dobb’s Journal, Volume 18, Issue 11, October 1993, p. 42 and in Dr. Dobb’s Sourcebook for Alternative Programming Languages.
  26. ^ Clemens Szyperski, Stephen M. Omohundro, and Stephan Murer, “Engineering a Programming Language: The Type and Class System of Sather“, in Jurg Gutknecht, ed. Programming Languages and System Architectures, Lecture Notes in Computer Science Volume 782, Springer-Verlag, Berlin (1994) pp. 208-227.
  27. ^ David Stoutamire and Stephen M. Omohundro, “The Sather 1.1 Specification“, International Computer Science Institute Technical Report TR-95-057, October 1995.
  28. ^ Stephan Murer, Stephen M. Omohundro, David Stoutamire, and Clemens Szyperski, “Iteration Abstraction in Sather“, Transactions on Programming Languages and Systems, Volume 18, Number 1, January 1996, pp. 1-15.
  29. ^ O'Reilly's History of Programming Languages poster
  30. ^ Stephen M. Omohundro, Geometric Perturbation Theory in Physics, World Scientific Publishing Co. Pte. Ltd., Singapore (1986) 560 pages. ISBN 9971-5-0136-8
  31. ^ Stephen M. Omohundro, “Modelling Cellular Automata with Partial Differential Equations”, Physica D, 10D (1984) 128-134.
  32. ^ John David Crawford and Stephen M. Omohundro, “On the Global Structure of Period Doubling Flows”, Physica D, 12D (1984), pp. 161-180.
  33. ^ Bartlett Mel, Stephen Omohundro, Arch Robison, Steven Skiena, Kurt Thearling, Luke Young, and Stephen Wolfram, “Tablet: Personal Computer in the Year 2000?, Communications of the ACM, 31:6 (1988) 638-646.
  34. ^ Bartlett Mel, Stephen Omohundro, Arch Robison, Steven Skiena, Kurt Thearling, Luke Young, and Stephen Wolfram, “Academic Computing in the Year 2000?, Academic Computing, 2:7 (1988) 7-62.
  35. ^ Subutai Ahmad and Stephen M. Omohundro, “Equilateral Triangles: A Challenge for Connectionist Vision“, Proceedings of the 12th Annual meeting of the Cognitive Science Society, MIT, (1990).
  36. ^ Subutai Ahmad and Stephen M. Omohundro, “A Network for Extracting the Locations of Point Clusters Using Selective Attention“, ICSI Technical Report No. TR-90-011, (1990).
  37. ^ Subutai Ahmad and Stephen M. Omohundro, “Efficient Visual Search: A Connectionist Solution“, Proceedings of the 13th Annual meeting of the Cognitive Science Society, Chicago, (1991).
  38. ^ Bartlett Mel and Stephen M. Omohundro, “How Receptive Field Parameters Affect Neural Learning” in Advances in Neural Information Processing Systems 3, edited by Lippmann, Moody, and Touretzky, Morgan Kaufmann Publishers, Inc. (1991) 757-766.
  39. ^ U.S. Patent 5,696,964
  40. ^ I. J. Cox, M. L. Miller, S. M. Omohundro, and P. N. Yianilos, “Target Testing and the PicHunter Bayesian Multimedia Retrieval System“, in the Proceedings of the 3rd Forum on Research and Technology Advances in Digital Libraries, DL’96, 1996, pp. 66-75.
  41. ^ Ingemar J. Cox, Matt L. Miller, Stephen M. Omohundro, and Peter N. Yianilos, “PicHunter: Bayesian Relevance Feedback for Image Retrieval“, in the Proceedings of the 13th International Conference on Pattern Recognition, 1996, pp. 361-369.
  42. ^ U.S. Patent 5,696,964, “Multimedia Database Retrieval System Which Maintains a Posterior Probability Distribution That Each Item in the Database is a Target of a Search“, Ingemar J. Cox, Matthew L. Miller, Stephen M. Omohundro, and P. N. Yianilos, granted December 9, 1997, assigned to NEC Research Institute, Inc.
  43. ^ T. P. Minka, M. L. Miller, I. J. Cox, P. N. Yianilos, S. M. Omohundro, “Toward Optimal Search of Image Databases“, in Proceedings of the International Conference on Computer Vision and Pattern Recognition, 1998.
  44. ^ Ian Stewart, “A Puzzle for Pirates“, Mathematical Recreations,Scientific American, May 1999, pp. 98-99
  45. ^ Donald G. Kimber, Feng Guo, Eleanor G. Rieffel, Kazumasa Murai, Stephen Omohundro, U.S. Patent 7,775,439 B2, August 17, 2010, "Feature Wands for Camera Calibration and as a Gesture Based 3D Interface Device"

External links[edit]