IEEE Spectrum June, 2013 - 77

making iT

now that watson, ibm's "JeoparDy!"-winning cognitive
computing system, has left the game show circuit behind, it's finding ample use for its talents
in health care, finance, and other industries.
Watson has quite a knack for combing through
computIng
vast troves of data to find a fact or recommend
a course of action based on knowledge and past
experience. * And back at IBM's Thomas J. Watson Research
Center, in Yorktown Heights, N.Y., a research group led by electrical
engineer and computer scientist Lav Varshney is pushing Watson
to the next level. Varshney and his team don't want a system that
digs up a preexisting answer; they want to build a creative system, one that can come up with something new. And they want
that something to be tasty.
Working with chefs at the Institute of Culinary Education in
New York City, the IBM team is building a cognitive computing
system that, given plenty of data about what foods most people
already like, will be able to come up with inventive, delicious flavor combinations-far beyond the familiar pairings of tomato and
basil, chocolate and strawberry, chicken and rosemary.
Recipe-generating programs already exist, but they are generally simple and case based, substituting new ingredients based
on flavors that have worked well in other dishes. The IBM project is trying for something much harder: a system that comes up
with radically new dishes based on combinations of ingredients
and flavors that people would probably find appealing but may
never have been put together in a dish before.
Here's how it works. To begin, Varshney [left, in photo] and his
team set up a large database of recipes from cookbooks, online recipe
banks, and even the U.S. Navy (which, though not renowned for
gourmet fare, makes some of its recipes publicly available). This collection is what's known as an inspiration database, a pool of existing
creative endeavors-recipes, in this case-that the system can draw
from. "Then you can do a lot of transformations on those recipes,"
Varshney says. "You can take two different recipes and mix them
together; you can substitute ingredients; you can change the cooking
processes." The system takes those alterations as inputs, and then it
knits together new recipes until it has-depending on available computing power-"a million or a billion or however many you want."
But of those myriad recipes, many would likely prove unappetizing, and few would be both delectable and novel. So the system's
next and biggest challenge is to sort the wheat from the chaff-
or perhaps the anise-infused wheat-berry salad from the
nopal-cactus-and-halibut kebabs.

To do this, it first evaluates the tasteimparting molecules in each new combination of ingredients. Such flavor compounds
might include, say, the fruity allyl propionate or coumarin, a chemical in green vegetables that has been described as "the taste
of green." The program then approximates
what the newly meshed flavors taste like by
comparing their component chemical structures with similar mixtures already in the
database. To determine whether a new taste
is appealing, the program is armed with a
large body of research that has measured
how much people like the flavors imparted
by different combinations of compounds.
If people tend to enjoy flavor combinations
that are chemically similar to the new one,
the computer can deduce that they'll probably take pleasure in it, too.
To determine which flavor blends are truly novel, the system
simply checks them against existing ones. Some mixtures will
be entirely new, not found anywhere in the system's database
of recipes; others could be new within the context of a particular
cuisine. For instance, they might introduce flavor pairings found
in Indonesian food to an American-style dish.
Once the system has homed in on a promising recipe, Florian
Pinel [right, in photo], a member of Varshney's team who is both
a software engineer and a professionally trained chef, will sometimes whip up a batch. "Last year we had a few things that were
pretty good, like a turmeric-and-ginger grilled eggplant sandwich
with a berry sauce," Varshney recalls.
The system is still experimental, but Varshney is already envisioning
real-world uses. Could it help improve school lunch menus? Definitely,
he says. Could it create a range of recipes low in salt and fat for people
with cardiovascular disease? No problem. What about dinners for a
lactose-intolerant diabetic looking to incorporate specific seasonal
produce into her diet? Eventually, Varshney believes. "Here you
can create whatever you want under the constraints you set, rather
than just having to work with what's already there," he declares.
But the biggest limitation of IBM's approach may be that it
oversimplifies the pleasures of eating. Our opinion of a meal is
shaped by our feelings and memories, the people surrounding
us, and the textures and presentation of the food in front of us-
all things that are hard to capture in an algorithm.
Nevertheless, it's clear that Varshney's system is on track to
create an inexhaustible recipe book of mouth-watering, neverbefore-tasted dishes. This artificial intelligence could very well
prove that computers can outcompete humans at yet another
cognitive craft we thought we alone had mastered. n
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Table of Contents for the Digital Edition of IEEE Spectrum June, 2013