“When we integrate the data folks
with the domain teams, they start
thinking about the art of the possible,”
he says. “So I need to understand my
network, how my traffic patterns are.
And the data scientist is saying, ‘I can
give you that, but actually I can predict
the traffic pattern for you a week in
advance and I can introduce seasonal-
ity so that when you’re looking at the
traffic pattern you’re not looking at that
based on historical data. You’re actu-
ally predicting the future.’”
“So that’s where the value of the
domain expertise and data and AI—
George Iskenderian,
Director, Big Data & AI
Bell Inc (Canada)“ The paradigm
is shifting from
detecting issues
to looking at the
bigger picture and
understanding
why anomalies are
happening”expertise come together. When we
say we build with use cases in mind,
we do have a strategic view as well.
Certain things we do such as anticipat-
ing problems or needs might not be
very high priority today but they will be
in a year or two.”AI VS ML: WHAT’S THE DIFFERENCE?
AI and ML are often conflated in
technology circles, with many people
describing machine learning func-
tions as AI, and others pointedly112
FEBRUARY 2021BELL INC (CANADA)