Robotics Reference
In-Depth Information
human endeavours are far more difficult to emulate than chess
playing. This is true. In many areas, the ability to write a topic
on computers, for example, computers are still pathetic. But as
computers continue to gain in capacity at an exponential rate, we
will have the same experience in these other areas that Kasparov
had in chess. Over the next several decades, machine competence
will rival, and ultimately surpass, any particular human skill one
cares to cite, including our marvellous ability to place our ideas in
a broad diversity of contexts. [13]
My one point of disagreement with all of this is Kurzweil's statement that
many other human endeavours are far more difficult to emulate than
World Champion level Chess playing, for example the ability to write a
topic on computers. Surely, for a human, writing a topic on computers
is much easier than winning the World Chess Championship. There are
literally thousands of authors of computer topics while the number of
World Chess Champions, up to and including Kasparov, was only 13
since the title was created and first contested in 1886. The fact that we
do not yet
know
how to program computers to write (acceptable) topics
about computers is no proof that the goal is more difficult to achieve
than that of defeating Kasparov. It's just that we have not yet
worked out
howtodoit!
Hugo de Garis
Hugo de Garis, born in Belgium, is an Associate Professor of Computer
Sceince at Utah State University where he heads the Brain Builder Group.
He teaches the world's first university course on Brain Building, to grad-
uate students, and is the scientific advisory director of the Brain Building
Division of Sentient Applications, Inc., based in Salt Lake City, which
aims to be the world's first artificial brain building company. His early
studies were on theoretical physics, but he abandoned this field of re-
search in favour of artificial life and Artificial Intelligence.
De Garis' work on AI has attracted many critics, most of whom object
to his view of eventual AI dominance over humans. He invented a new
field within AI known as evolvable hardware, in which neural network
circuits are evolved directly in hardware, at hardware speeds, to build arti-
ficial brains. His reasearch goal is to assemble thousands of these “brains”
into a larger artificial intelligence architecture to make a functioning Ar-
tificial Intelligence. He predicts that one day these machines, which he
