My computer is not intelligent at all. Although it can do many useful things which I cannot and I depend on it daily, it cannot do many of the things that are second nature to any two-year-old. Each new season brings us faster computers and we can extend the trend of exponentially increasing computer power to predict that at some point in the future, computers will exceed human brains in brute-force switching capacity. Experts estimate that today's computer falls short of the human brain by a factor of a million or so and that the threshold could be crossed in as little as 20 years!
Many of these same experts then predict that such machines will appear intelligent, but are generally sketchy on the details. How can we assume that a future computer will become smarter rather than continuing to be stupid, but stupid a million times faster? This article proposes to begin to fill in the knowledge gap with a few algorithms and a software architecture which could plausibly create the appearance of intelligence in future computers.
There is a spectrum of divergent opinions on the potential for thinking computers. On one hand, many people, including Hans Moravec in Mind Children (Harvard University Press, 1988; ISBN 0674576187) and Ray Kurzweil in The Age of Spiritual Machines (Penguin Books, 1999; ISBN 0140282025), assume that true thinking machines are inevitable because intelligence arises "spontaneously" when sufficient computational power is available. On the other hand some people (such as physicist Roger Penrose, author of The Emperor's New Mind) assert that true thinking machines are impossible because intelligence relies on some sort of "brain-stuff" which is inherent only in biological systems. To address both, I contend there are several observations we can make about intelligence and thinking and observe several specific constituent capabilities. Although my computer does not do any of them today, there is no inherent reason it could not be programmed to perform them when sufficient capacity becomes available.
2008 International Mathematica Conference Dr. Dobb's interviews Wolfram Research's Theo Gray, co-founder and Director of User Interfaces, and Roger Germundsson, Director of Research and Development, about the upcoming 2008 International
Mathematica Conference.
How Do You Do Nightly Builds and Tests when there is No Overnight? Software Production in a Geographically Distributed Environment
Attend this Webcast and find out how to overcome common build-test-deploy challenges that affect all members of a distributed team, including:
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<li> Communication difficulties, because of time-zone and cultural differences</li>
<li> Workflow challenges, like lack of documented procedures and build and test handoff problems</li>
<li> Slow build and test cycles, broken builds, and other factors that hamper distributed team productivity</li>
</ul>
Thursday, September 25, 2005 " 11am PT / 2pm ET
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In this volume of Best of BYTE, we explore the emergence of some heuristic algorithms. Although we have only scratched the surface of this intriguing subject, we hope we've suggested the potential of the synthesis of heuristics and algorithms.
Understand C/C++ code in less time. A new team member ? Inherited legacy code ? Get up to speed faster with Crystal Flow for C/C++. Code-formatting improves readability. Flowcharts are integrated with code browser. Export flowcharts to Visio.
