At its upstate New York facility, IBM researchers are tackling a number of issues that range from business analytics and IT services to health care.
YORKTOWN HEIGHTS, N.Y.-"Watson"
isn't brushing up on any trivia today.
Watson, now maybe the world's most well-known supercomputer (with its own
New York Times Magazine profile
to prove it), is half hidden behind a black
curtain and stationed in the mock "Jeopardy" studio that IBM
has built inside its massive T.J. Watson Research Facility here.
During a recent visit there, IBM
engineers could be seen tweaking Watson, which, though based on some of the
same technology as the company's other Blue Gene supercomputers, utilizes natural-language
capabilities. Although Big Blue is still testing Watson against "live" Jeopardy
contestants, the supercomputer is expected to appear on the real game show
sometime later this year.
While Watson, much like its chess-playing predecessor, Deep Blue, is an impressive
way for IBM to capture the public's
imagination, the supercomputer is only a small part of what goes on at the
Watson facilities, both here and in neighboring Hawthorne, N.Y.
What is really driving a small but growing part of IBM's
research these days is analytics
, which is essentially a discipline that
uses mathematics and data to arrive at the most optimal decision. For years,
IBM research and math departments have played a key role in the company's
research; now the
company tapped these scientists and researchers to be part of its massive
Global Services Division.
One day, in fact, Watson could find itself, rather than on TV, part of this very
same analytics push--specifically focusing on health care, where its language
software and massive computational ability could assist in the areas such as
molecular biology and genomic sequencing. As part of this direction, IBM
is looking to increase the number of people in its math department from about
110 to 200 or so, especially concentrating on those with expertise in very
specific fields of study, including operations research, machine learning and
"We are looking for special people. We don't want people in the ivory
tower," said Baruch Schieber, manager of Business Analytics and
Optimization at IBM Research. In other
words, he is looking for mathematicians interested in real-world work. "We
want people to get in here and understand how people manufacture and how
companies distribute their goods from the warehouse to the supermarket."
Large IT companies, from IBM and Oracle
and Dell, all have services divisions, which are becoming increasingly
competitive and lucrative. In a recent report, IDC
found that global IT-services spending is slated to grow from $573.4 billion
this year to $685 billion by 2014. When IBM
announced its financial 2010 second-quarter results
, the services division
reported a 2 percent increase in revenue, to $13.7 billion.
IBM's approach to IT services is somewhat
different from that of other companies. It is able to tap into its own massive research
division and incorporate in-house scientific research, such as analytics, into
a business division such as Global Services. For the past year, IBM
has highlighted this approach in its Smarter Planet initiative, but the concept
actually goes back to 2002, when IBM
. This began a nearly 10-year effort to bring
more research and analytics into the services division.
Schieber explained that, though IBM has
been talking up its particular approach to IT services for the past few years, applying
analytics to business problems actually goes back about 20 years, to when IBM
worked with American Airlines on a customized fleet-and-crew scheduling project.
IBM researchers work within two
different disciplines of analytics, which then come together. The first is
business analytics, which uses data to make predictions and forecasts; the
second is optimization, which combines predictions and business constraints to
produce an outcome and plan to meet differing objectives.
A recent example of this cooperative process is a project with the New York
State Department of Taxation to collect tax revenue owed to the state.
First IBM research looked at the situation, researched the historical data
and applied both types of analytical methods to the problem. The company then came
up with a combination of software-including data warehouse, database
management, and business intelligence-to determine which people would respond
to a simple letter from the tax division and which ones would require a