Dr. David Ferrucci discusses Watson Deep QA project at TiEcon Keynote
At TiEcon 2011 keynote session (www.tiecon.org), Dr. David
Ferrucci discussed the phenomenal challenges of building Watson, an
artificial intelligence computer system that competed with human
subjects in the quiz show Jeopardy and consistently outperformed
the human competitors. Compared to the Deep Blue, the
chess-playing computer, developed in 1997, the Watson Deep QA
project was infinitely more challenging. Chess is finite,
mathematically well defined with limited number of moves.
Computer can be really good at mathematically challenges and can
find information very quickly. Jeopardy however is a
significantly more complex challenge. Not only Watson had to
navigate through the complexity of human speech which is infinitely
more complex, contextual, idiomatic and full of puns and
expressions that alter the meaning of the words but additionally
Watson had to demonstrate the level of confidence it had in the
answer it came up with and it had to do all that in a matter of
seconds. Watson got better at the game and finally came up
with answers at the average speed of 3 seconds. Watson had
access to over 200 million pages of structured and unstructured
content consuming several terabytes of storage. While Watson
outperformed its human opponents most of the time, it had trouble
responding to several categories. Ferruci shared several
examples where Watson was completely off the mark and that gave
impressive evidence of how infinitely complex human speech is,
where meaning of the same words is often determined or altered
based on the order of the words, the sentence structure, placement
of commas and exclamation marks etc.
At TiEcon, this was a breakthrough keynote, considering that
most keynotes focus on the business aspect. Ferrucci's
presentation was technical and fascinating and kept the audience
riveted, soaking up the impressive information.
Ferrucci discussed the implications of this project in several
other domains, with the members of the press. It is possible
that Watson-based technology, or services built upon it, might
appear and might have implications in a wide range of
industries. Application in disease and healthcare diagnosis
for instance, can be an invaluable tool to aid the doctors rarely
have enough time with each patient to consider all possible
data. Also unlike many previous projects, Watson shows
considerable similarity of thinking with the human mind. For
instance, Watson is programmed for uncertainty. It is often
not completely confident and rather gives an answer with a certain
level of confidence making it easier to determine how much weight
to give to the answer given. Truly fascinating project.
Darshana Varia Nadkarni,
Ph.D.
Twitter @DarshanaN
web - darshanavnadkarni.wordpress.com
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