SAS Machine Learning and AI

SAS Machine Learning and AI

November 23, 2019 2 By Stanley Isaacs


STEVE HOLDER:
Fundamentally, the math and the techniques
that people are using with machine learning have
been around for a long time. What’s interesting about it is
the ability for organizations to now use some of the
technical advancement, whether that be in computing
power or the commoditization of analytics, to actually
start to implement that. WAYNE THOMPSON: The goal
with machine learning is really all about automation,
getting data that is typically observational by nature, and
finding out patterns and trends in a very automatic way. STEVE HOLDER: Contrast that
with AI, where AI is really about bringing a
human interaction to the system of record or the
system you’re interacting with. STEVE HOLDER: Organizations
and the people in these organizations are
increasingly more confident in technology-making decisions. Whether you look at things
like self-driving cars, or even recommendations
and engines on websites, people are just starting get
more comfortable with the fact that machines will tell us what
we want and we can trust them. PIERRE MONTAGNIER:
The great opportunity for machine learning
and AI in banking is really helping serve the
customer better and provide offers that are more relevant
to them at the right time through the right channel. STEVE HOLDER: The ability to
store data and do computations on it is really driving the
machine-learning phenomena in Canada. JOSEPH GERACI: We’re able to
leverage 4 terabytes of RAM in a shot because of
the SAS’s MSTAT package. I mean, this in-memory
computing can transform big data computation. Our value add is really about
giving productionalizion for machine learning models, and
giving approachable interfaces so people can start to consume
these models without having to be experts in the field,
making it so someone could actually ask a question
of a SAS system, and have it run all the
analytics and background noise and deliver the outcome
directly to the user in a human-like way. STEVE HOLDER:
Machine learning will allow us to really hone in
and create targeted treatments for cancer, for example. JOSEPH GERACI:
Doctors are being told that they can leverage
the data to make better decisions for their patients. The impact in health care
is going to be astronomical. WAYNE THOMPSON: I
do think that we’ll see machines become– almost
seem a part of our family. They’ll function with us. They’ll help us reason. They’ll make our lives easier. STEVE HOLDER: These sort of
things aren’t impossible. I think machine learning
gives us that opportunity to impact people’s lives and
really make businesses more intimate with their customers.