suggesting that AI – in its truest
sense – is not really available yet.
Iskenderian is happy to explain his
view. “I’ll give it an analogy: if artifi-
cial intelligence is mathematic, then
machine learning would be algebra.
So machine learning is a discipline
within the bigger umbrella of artificial
intelligence. And then deep learning
would be linear algebra.
“We realize that AI and ML are of par-
amount importance and it’s going to
play a significant role going forwards.
And we have various initiatives to makesure that we focus specifically on AI/
ML expertise development, but also
how we create value using AI/ML, so
it’s very important to the organization.
We talked about network operations
and performance, failure detection: all
those concepts can be solved with
AI/ML.
“I’ll give you an example: spam fil-
tering. When millions and millions of
emails are going through some serv-
ers, it would be cost prohibitive for any
decision logic to look at that and say
‘this is spam, this is not spam’. Machine116
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