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From YouTube: Building an Edge Intelligence Application at Verizon Media - Ganesh Harinath (Verizon Media)
Description
Building an Edge Intelligence Application at Verizon Media
Ganesh Harinath (Verizon Media)
OpenShift Commons Gathering on Data Science
January 28, 2021
https://commons.openshift.org/gatherings/OpenShift_Commons_Gathering_on_Data_Science.html
Find out more about OpenShift Commons, please visit: https://commons.openshift.org
A
A
Moving
forward
5-10
years,
robotic
arm
surgery
is
going
to
be
very,
very
normal,
and
what
that
means
is
a
doctor
from
new
york
can
perform
a
surgery
on
a
patient
in
los
angeles.
To
me,
this
is
fascinating
and,
interestingly,
when
you
take
a
closer
look
at
what's
required
for
all
these
things
to
happen,
robotics
is
important.
A
virtual
reality
is
very
important
and
artificial
intelligence
is
the
foundation
for
this
capability
and,
most
importantly,
we
being
part
of
telco
5g
would
enable
to
converge
these
technologies
to
make
this
capability
a
reality
in
years
to
come.
A
But
when
we
start
to
ground
ourselves
and
then
take
a
closer
look
at
where
we
are
today,
what
we
are
trying
to
do
with
ml
and
ai
a
lot
of
applications
that
really
required
massive
data
on
the
cloud
applying
ai
to
understand
various
aspects
of
the
network
was
one
of
the
area
that
was
very,
very
focused
on,
but
looking
forward.
Industrial
automation
is
a
space
where
we
are
starting
to
understand,
build
capabilities
and
solutions
to
the
right
on
the
left
autonomous
cars.
A
I'm
fascinated
there's
a
long
way
to
go,
but
the
autonomous
car
today
can
look
at
the
car
in
front,
but
what
needs
to
happen
is
to
be
able
to
really
connect
two
5g
capabilities
and
apply
ai
to
plan
the
entire
route
and
that's
in
play
as
well.
These
are
like
fascinating
changes
that
we
all
are
living
through
and,
interestingly,
the
shift
has
been
accelerated,
but
the
way
how
I
summarize
my
experience,
any
application
that
we
would
actually
touch
field
c
would
be
powered
by
ai.
A
Now,
to
summarize
how
the
application
shift
is
happening
when
you
take
a
closer
look
at
any
machine
learning
application,
I'm
sure
we
all
know
there
is
an
aspect
of
model
training
which
is
very
compute
intensive,
and
there
is
aspect
of
inferencing
and
in
today's
world
very
easily.
We
deploy
both
training
and
inferencing
on
the
cloud
and
have
this
mlai
experience
directly
from
the
cloud.
A
In
order
to
accommodate
this,
we
are
starting
to
see
a
paradigm
shape,
and
that
is
moving
the
inference
capability
very
intelligently
and
seamlessly
from
the
cloud
to
the
closest
location
where
the
need
is
so
some
of
the
application.
If
the
inferencing
is
of
the
order
of
10
to
25
milliseconds,
that's
just
an
estimate,
then
ideal.
You
deploy
these
inferencing
onto
the
cdn
edge
vbmg.
We
have
cdn
edge
in
160
location.
A
A
A
A
A
We
have
that
reliability
both
in
terms
of
high
volume
inferencing
and
also
ensure
that
it
is
seamless
and
it's
actually
working
in
a
factory
environment
and
5g
private
definitely
is
going
to
play
a
big
role
to
connect
all
these
different
sensors
cameras
and
so
on
and
route
signals
and
video
streams
to
a
platforms,
a
centralized
platform
which
can
ingest
and
apply
artificial
intelligence
and
start
to
surface
in
sites.
To
improve
efficiencies,
to
avoid
error
near
real
time
without
any
material
loss,
and
this
is
an
area
where
verizon
are
starting
to
heavily
invest.
A
A
Now,
knowing
verizon
has
tens
of
thousands
of
cell
towers
having
technologies
like
drone
and
computer
vision.
So
on
it's
it's
very
timely
that
we
we
start
to
build
applications
instead
of
people
climbing
on
the
side
tower
to
understand
issues
with
the
towers
and
connections
and
so
on,
apply
drones
to
understand
the
issues
around
those
cell
towers
one.
It
addresses
a
lot
of
safety
issues
too.
It
addresses
the
lot
of
sorry
there's
a
lot
of
cost
efficiencies
attributed
as
well
and,
most
importantly,
with
computer
vision.
A
You
really
see
a
lot
of
insights
where
you
can
take
corrective
actions
near
real
time
and
we're
continuing
to
invest,
and
this
is
kind
of
a
very
vertical
application.
Today
you
solve
it
for
cell
traveler
third
hours,
you
can
retrain
it
to
monitor
oil
pipelines,
buildings
and
bridges
and
then
so
on.
I
personally
am
very
very
fascinated
about
the
mission
that
we
embarked
on.
A
A
A
A
In
simple
terms,
I
call
the
pink
boxes
and
the
blue
boxes
were
deployed.
On
the
cloud
now
eloquently,
we
have
to
separate
these
pink
boxes,
to
the
closest
edge,
which
could
be
a
cdn
edge
or
a
2u
box,
which
would
empower
you
to
build
applications
like
a
drone,
vertical
inspection
applications
like
factory
automation
and
then
so
on.
So
we
are
very
heavily
invested
in
operationalizing
the
capability
of
platform,
which
helps
empowers
us
to
build
edge
applications
seamlessly.
A
So
what
you're
seeing
is
a
very
high
level
blueprint
of
the
platform
leo
where
the
pink
boxes
are
taken
care
as
part
of
the
model
inferencing
and
application
deployment,
and
this
application
deployment
has
to
be
end
to
end.
We
should
be
able
to
run
ui,
it
has
to
be
secured,
and
this
to
me
is
a
paradigm
shift.
A
We
all
talk
about
distributed
infrastructure.
Now
we
are
talking
about
a
distributed
application
where
the
same
drone
inspection,
the
same
factory.
Automation
has
to
be
deployed
in
multiple
locations
and
in
many
cases
it
has
to
be
integrated
on
the
cloud
to
make
it
work
very,
very
seamlessly,
and
it's
a
it's
a
it's
a
fascinating
time
where
the
demand
for
infrastructure
is
changing.
The
security
posture
is
changing.
A
A
So
what
that
translates
to
is,
it
can
be
deployed
on
any
edge
platform,
but,
as
I
was
mentioning,
it's
very
important
to
have
a
seamless
interconnect
to
the
cloud,
because
it's
just
only
portion
of
your
application
and
a
lot
of
the
training
needs
to
happen
on
the
cloud
and
there
could
be
compliance
policies
where
you
have
to
persuasive
on
the
cloud,
and
this
data
has
to
be
shipped
onto
the
cloud
for
various
reasons
and,
most
importantly,
a
fascinating
approach
of
building
models.
This
is
called
distributed.
A
Is
super
important,
be
able
to
ingest
data,
all
forms
of
kinds
of
data,
high
throughput
and
so
on,
and
it
should
empower
us
to
build
end-to-end
applications
with
ui,
very
secure
and
so
on
and,
most
importantly,
the
security
posture
has
changed
because
you
have
a
2u
box
sitting
somewhere
physical
security
becomes
important
application.
Security
becomes
important
to
you.
These
things
have
to
be
factored
in
this
which
is
beyond
leo,
but
we
need
to
have
a
strategy
to
address
all
aspects
of
security
and
leo
does
address
application
security.
A
It's
operationalized
and
we
have
been
very,
very
successfully
been
using
within
verizon
and,
interestingly,
though,
it's
very,
very
early
leo
has
become
the
north
star,
edge
architecture
or
verizon
media
group,
as
we
speak
now.
To
conclude,
we
are
starting
to
see
a
new
influx
of
application.
I
call
this
as
next
generation
application
and
these
applications
each
one
of
them
would
be
powered
by
ai,
there's,
no
doubt
they're
poised
to
enhance
human
experience
and
efficiencies
and
health
and
safety
and
so
on.
A
A
We
need
to
have
a
strategy
and
partnerships
in
place
where
we
have
control
on
the
edge
and
technologies
like
openshift,
definitely
will
put
us
in
a
very,
very
good
situation,
to
have
a
very
controlled
and
manageable
environment,
taking
into
account
it's
very,
very
distributed
too
and,
most
importantly,
how
are
we
going
to
build
test?
Deploy,
keep
the
environment
very
agile
that
way
it's
adaptive,
adaptive
too,
so
so,
taking
all
these
things
into
account,
we're
very
early
on.