1968 release of Stanley Kubrick and Arthur C. Clarke's groundbreaking
film, "2001: A Space Odyssey" introduced millions of moviegoers
to the relatively new concept of Artificial Intelligence (A.I.).
The HAL 9000, the space ship's on-board computer, could think
for itself, speak for itself, even act in self-defense. With
its chillingly calm voice and red, all-seeing eye, HAL at
once embodied our deepest fears about and greatest hopes for
technology. Intelligent machines might help us reach the stars
- or else they might eclipse us, and render our humanity irrelevant.
way, the year 2001 has come and gone, and your desktop computer
- impressive tool that it is - is hardly cause for philosophical
meditation on what it means to be human. Where are the HAL
9000's and C3PO's science fiction promised us?
Intelligence, it turns out, is a lot harder to define than
researchers once thought, thereby making intelligent machines
a lot harder to build. But that doesn't mean scientists and
engineers have stopped trying. In "The Intimate Machine,"
Alan visits the MIT Media Lab where researchers are working
to make machines smarter, more empathetic and easier to work
with. Their creations might not lead us down the road to HAL,
but they do inch us closer every year to useful A.I. applications.
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9000's all-seeing eye from the film "2001: A
people had long imagined laborsaving robots and intelligent
machines, it was not until a pioneering group of mathematicians
and scientists met at Dartmouth College in 1956 that John
McCarthy coined the phrase "artificial intelligence." It was
at this conference that McCarthy and his colleagues Marvin
Minsky, Allen Newell and Herbert Simon - all now considered
founding fathers of A.I. - began their decades-long dominance
over the field. Though each scholar had trained in different
disciplines - from math to physiology to political science
- they did agree on one thing at that Dartmouth conference;
that machines could be programmed with, or at least to simulate,
Where are the HAL 9000's and C3PO's science fiction
in the midst of the Cold War, the U.S. government poured funding
into A.I. projects in the hopes that intelligent machines
would prove advantageous as inconspicuous spies, expendable
soldiers or some other as-yet undreamed of intelligent agent.
But electronic computers - the obvious platforms for such
devices - had only been in existence since the 1940s. As late
as the 1960s, they were still room-sized behemoths that just
did not possess the data storage capacity A.I. researchers
really needed. It was not until the computing revolution of
the 1970s and '80s that the hardware and software caught up
to the task of building anything remotely like HAL or R2D2.
A.I. researchers were noticing that abilities we take for
granted - like seeing, hearing and hand-eye coordination -
were more difficult to write code for than the first A.I.
programs. While early A.I. scientists had created successful
intellectual programs- excellent chess players and elegant
problem solvers- intelligent machines still eluded them.
"Big Blue" beat chess champ Gary Kasparov at his own
game. But that doesn't make Big Blue more "intelligent,"
according to Veloso.
Deep Blue played chess against Kasparov, the machine was not
looking at the board and was not lifting the pieces by itself,"
says Manuela Veloso, assistant professor of computer science
at Carnegie Mellon University. "The computer was extremely
good at thinking, but not at actually perceiving the board
and having an arm move the pieces. I feel that intelligence
includes these abilities."
this more inclusive definition of intelligence spread among
researchers, the field of A.I. expanded to encompass even
more disciplines. Psychology, cognitive science, neurology
and even evolutionary biology are now equally important as
mathematics and physics. A.I. researchers now take one of
two not necessarily opposing approaches. While some scientists
model robots' abilities - vision, for instance - on human
or animal vision, others work to achieve sight in robots without
regard to how well it mirrors natural processes. Although
there is plenty of crossover between these two camps, the
approaches tend to produce radically different results. Together,
the breakthroughs achieved on both ends of this A.I. spectrum
will help us build a better robot.
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