From: Spudboy100@aol.com
Date: Tue May 13 2003 - 23:25:46 MDT
<<Story location: http://www.wired.com/news/technology/0,1282,58714,00.html
02:00 AM May. 13, 2003 PT
Will we ever make machines that are as smart as ourselves?
"AI has been brain-dead since the 1970s," said AI guru Marvin Minsky in a
recent speech at Boston University. Minsky co-founded the <A HREF="http://www.ai.mit.edu/">MIT Artificial
Intelligence Laboratory</A> in 1959 with John McCarthy.
Such notions as "water is wet" and "fire is hot" have proved elusive quarry
for AI researchers. Minsky accused researchers of giving up on the immense
challenge of building a fully autonomous, thinking machine.
"The last 15 years have been a very exciting time for AI," said <A HREF="http://www.cs.berkeley.edu/%7Erussell">Stuart
Russell</A>, director of the Center for Intelligent Systems at the University of
California at Berkeley, and co-author of an AI textbook, Artificial
Intelligence: A Modern Approach.
Russell, who described Minsky's comments as "surprising and disappointing,"
said researchers who study learning, vision, robotics and reasoning have made
tremendous progress.
AI systems today detect credit-card fraud by learning from earlier
transactions. And computer engineers continue to refine speech recognition
systems for PCs and face recognition systems for security applications.
"We're building systems that detect very subtle patterns in huge amounts of
data," said Tom Mitchell, director of the <A HREF="http://www.cald.cs.cmu.edu/">Center for Automated Learning and
Discovery</A> at Carnegie Mellon University, and president of the <A HREF="http://www.aaai.org/">American
Association for Artificial Intelligence</A>. "The question is, what is the best
research strategy to get (us) from where we are today to an integrated,
autonomous intelligent agent?"
Unfortunately, the strategies most popular among AI researchers in the 1980s
have come to a dead end, Minsky said. So-called "expert systems," which
emulated human expertise within tightly defined subject areas like law and <A HREF="http://www.openclinical.org/aisp_apache.html">
medicine</A>, could match users' queries to relevant diagnoses, papers and
abstracts, yet they could not learn concepts that most children know by the
time they are 3 years old.
"For each different kind of problem," said Minsky, "the construction of
expert systems had to start all over again, because they didn't accumulate
common-sense knowledge."
Only one researcher has committed himself to the colossal task of building a
comprehensive common-sense reasoning system, according to Minsky. Douglas
Lenat, through his Cyc project, has directed the line-by-line entry of more
than 1 million rules into a commonsense knowledge base.>>
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