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convergence08.org

To kick off Convergence08, we'll hear a very different AI debate: not whether to create AI, or which technical path will work fastest, but "How can we use AI technology to build the world we want to live in?" Four AI pundits thrash it out, and then we all join in!

Peter Norvig is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. At Google he was Director of Search Quality, responsible for the core web search algorithms from 2002-2005, and has been Director of Research from 2005 on. Previously he was the head of the Computational Sciences Division at NASA Ames Research Center, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He served as a research faculty member at the UC Berkeley Computer Science Department, from which he received a Ph.D. in 1986 and the distinguished alumni award in 2006. He has over fifty publications in Computer Science, concentrating on Artificial Intelligence, Natural Language Processing and Software Engineering, including the book Artificial Intelligence: A Modern Approach (the leading textbook in the field). He is also the author of the Gettysburg Powerpoint Presentation and the world's longest palindromic sentence.

Steve Omohundro has had a wide-ranging career as a scientist, university professor, author, software architect, and entrepreneur. He received a Ph.D. in Physics from UC Berkeley, and published Geometric Perturbation Theory in Physics based on his thesis. At Thinking Machines, he co-developed Star Lisp, the programming language for the massively parallel Connection Machine. He was a computer science professor at the University of Illinois at Champaign/Urbana where he co-founded the Center for Complex Systems Research. He wrote the three-dimensional graphics portion of Wolfram Research's Mathematica program as one of the original seven developers. At the International Computer Science Institute in Berkeley, he led an international team in developing the object-oriented programming language Sather. He also developed a variety of novel neural network techniques and machine learning algorithms and built systems which learned to read lips, control robots, and learn grammars. He is the founder and president of Self-Aware Systems, founded to develop a new kind of software that programs itself.

Ben Goertzel is founder, CSO and CEO of Novamente, a software company aimed at creating applications in the area of natural language question-answering; and director of research at the Singularity Institute for Artificial Intelligence, overseeing the Open Cognition Project. He has over 70 publications, concentrating on cognitive science and AI, including Chaotic Logic, Creating Internet Intelligence, Artificial General Intelligence (edited with Cassio Pennachin), and The Hidden Pattern. He also oversees Biomind, an AI and bioinformatics firm that licenses software for bioinformatics data analysis to the NIH's National Institute for Allergies and Infectious Diseases, and CDC. Ben has a Ph.D. in mathematics from Temple University, and has held several university positions in mathematics, computer science, and psychology, in the US, New Zealand, and Australia.

Barney Pell is founder of Powerset and search strategist and evangelist at Microsoft. For over 15 years, he has pursued groundbreaking technical and commercial innovation in AI as a researcher, research manager, business strategist and entrepreneur. He spent 2005 as Entrepreneur in Residence at Mayfield evaluating early to mid-stage IT and knowledge based companies. Prior to Mayfield, he worked for NASA Ames Research Center on two occasions: from 1993-1998 as Project Lead for the Executive component of the prize-winning Remote Agent Experiment; and from 2002-2005 as Area Manager responsible for research in intelligent agents, software architecture, human-centered computing, search, collaborative knowledge management, distributed databases, spoken dialog systems, and the semantic web. Barney holds a Ph.D. in Computer Science from Cambridge University.
  • Pawel 2 years ago
    Use a programming environment as simple as Visual Basic to create a program A. Create another program called B within program A. Create at least one working interface to communicate with outside world in program B. Begin the loop here. Let program A make a backup copy of both programs A & B into "memory" and then let program A to randomly change the existing interface(s), let it randomly add new ones to the program B and let it make some slight adjustments to the program A. Let program A check for inputs and make outputs using existing interface(s) in program B. Let program A use logical algorithms, functions, probabilities and properties located in program B to check the grammar meaning of those inputs and to create random outputs. Add a probability function to every event or property stored in memory or actions just made. Probability functions must be located in program B. If the inputs from existing interface(s) don't give at least one understood meaning OR the outputs from new interface(s) are not followed by at least one understood input then randomly chose to either remove those new interface(s) OR to restore them from backup and then go to the begining of the loop. Let the time it takes to wait for the understood inputs be nothing more then just another property stored inside program B. Use the above probability functions, algorithms and properties to measure the meaning of inputs. Otherwise if the inputs are understood then do not remove or restore anything and just go to the begining of the loop.

    Here you go : You have an AGI that thinks, grows, evolves, changes it's own sourcecode. It is capable of doing whatever can be achieved using the programming environment it was written in, so think twice about it. Now you can email me and let your AGI chat with my new AGI family to make them more advanced if only they wish to. If you still say that we need a decade to create AGI then you simply are not a programmer.
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