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From YouTube: Fast Track AI With Hybrid Cloud
Description
Presented at AI Summit NYC 2020.
Business leaders desire data-driven insights to help improve customer experience.
Data engineers, data scientists, and software developers desire a self-service, cloud-like experience to access tools/frameworks, data, and compute resources anywhere to rapidly build, scale, and share results of their projects to accelerate delivery of AI-powered intelligent applications into production.
This keynote will provide a brief overview of the AI/ML use cases, required capabilities, and execution challenges. Next, we will discuss the value of open hybrid cloud powered by Kubernetes to help fast track AI/ML projects from pilot to production, and accelerate delivery of intelligent applications to the enterprise. Finally, the session will share real-world success stories from various industries globally.
Presented by Abhinav Joshi of Red Hat
A
Hi,
everyone
hope
you're
doing
good.
My
name
is
abhinav
joshi.
I
am
the
director
for
ai
strategy
and
go
to
market
at
red
hat.
Today,
I'm
going
to
be
talking
about
how
organizations
are
fast
tracking
and
operationalizing
the
ai
projects,
with
a
hybrid
cloud
platform
based
on
my
experience
in
the
industry.
These
are
the
top
benefits.
Organizations
are
achieving,
with
aiml
improve
digital
customer
experience,
gaining
competitive
advantage
by
offering
differentiated
digital
services,
increasing
revenue
and
reducing
operational
costs
and,
finally,
being
able
to
automate
the
manual
and
time
consuming
business
operations.
A
Here
are
the
examples
of
business
outcomes
achieved
by
organizations
across
various
industries
because
of
the
power
of
aiml
healthcare
organizations,
looking
for
faster
diagnostics
and
improving
clinical
efficiency,
financial
service
organizations
interested
in
use
cases
like
fraud,
detection
risk
analytics
and
improving
digital
security
insurance
companies,
interest
interested
in
automating
the
claims,
processing
and
offering
usage-based
discounts.
Then.
Finally,
automotive
companies
wanting
to
speed
up
the
autonomous
driving
initiatives
being
able
to
achieve
predictive
maintenance
and
optimizing
manufacturing
operations.
A
A
However,
there
are
execution
challenges
that
are
resulting
in
stall
projects.
The
big
one
that
we
like
here
all
the
time
from
different
organizations,
is
the
lack
of
a
data,
lack
of
quality
data
and
talent
shortage.
Both
of
them
continue
to
be
a
challenge,
and
then,
in
addition
to
that
being
able
to
operationalize
ai
is
a
big
challenge.
A
The
hybrid
cloud
platform
should
be
integrated
with
hardware
accelerators,
such
as
the
gpus
to
help
speed
up
the
machine,
learning
model,
development
and
inferencing
tasks.
Finally,
the
hybrid
cloud
platform
should
offer
consistent
experience
across
on-premises
public
cloud
and
edge
locations
and
be
able
to
efficiently
be,
like
all
the
architecture,
be
efficiently
managed
by
id
operations.
A
So
the
value
that
this,
the
hybrid
cloud
platform
has
been
providing
to
speed
up
the
software
application
development
can
now
be
applied
to
the
data
science
workflows
as
well.
It's
it
simplifies
the
deployment,
scaling
and
life
cycle
management
of
containerized
aiml
tools
by
automating
the
day,
one
to
two
operations,
tasks
associated
with
these
tools,
ensuring
the
high
availability
and
the
faster
time
to
value
integration
with
the
hardware
accelerators,
such
as
the
nvidia
gpus,
ensures
that
the
modeling
and
inferencing
tasks
can
like
happen
seamlessly
and
be
able
to
consume.
A
The
gpu
resources
as
needed,
it
can
also
be
consumed.
Is
either
as
a
self-managed
or
a
cloud-hosted
option,
thereby
providing
a
consistent
way
to
perform
day
one
to
do
operations
across
data
center
edge
or
public
clouds,
ensuring
the
portability
of
the
machine,
learning,
deep
learning
and
and
the
application
development
workflows?
A
A
This
helps
ensure
that
the
machine
learning,
deep
learning
models
can
be
easily
deployed
in
the
application
development
process
and
the
rollout
of
the
machine
learning
intelligent
applications
that
are
powered
by
aiml
can
also
happen
in
a
smooth
way
it
if
it
is
a
fully
integrated,
hybrid
cloud
platform
that
includes
key
capabilities
like
monitoring,
automation,
devops
tool,
chain
and
so
on,
built
on
100,
open
source
project
to
help
drive
the
innovation
forward.
On
that
point,
this
helps
drive
the
innovation
without
any
vendor
lock-in.
A
These
are
some
of
the
examples
of
organizations
across
different
industry
verticals
that
have
successfully
operationalized
the
aiml
projects,
with
red
hat
openshift
powered
hybrid
cloud
platform.
To
achieve
the
key
business
goals
and
objectives
now,
let's
dive
into
some
of
these
to
understand
their
specific
goals,
challenges,
solution
and
the
benefits
achieved.
A
A
Banks
like
like
rbc,
handle
massive,
like
lots
of
data
and
and
easily
10
billion
new
client
interactions
a
month
being
able
to
analyze.
The
increasing
amount
of
data
was
not
a
small
task
in
2016,
so
rbc
launched
his
own
ai
research
center
called
borealis
ai,
and
this
was
done
to
address
some
of
the
challenges
and
begin
taking
advantage
of
aiml
for
both
the
internal
research,
as
well
as
to
build
out
the
new
customer
service
offerings
across
personal
and
commercial
banking
to
wealth
management
and
capital
markets.
A
A
It
helps
that
it
takes
days
now
and
not
months
to
build
test
and
run
the
new
models
and
the
data
scientists
have
to
and
the
developers
have
to
no
longer
wait
on
the
infrastructure
and
the
tools
to
be
configured.
This
cloud
platform
is
powerful
too.
As
one
example,
the
bank
was
able
to
analyze
data
from
13
million
clients
in
in
just
a
matter
of
20
minutes
for
a
project.
A
Now
going
forward,
rpc
is
also
looking
to
leverage
the
ai
in
customer
facing
apps
as
well.
It
already
has
a
customer
virtual
assistant
called
know
me
that
is
helping
customers
like
achieve
better
decision
by
being
able
to
enhance
the
app
with
the
new
ai
powered
capabilities
like
rbc,
will
be
able
to
provide
a
more
tailored
approach
and
an
experience
and
make
better
recommendations
to
customers.
A
A
The
red
hat
hybrid
cloud
platform
is
actually
helping
them
save
lives
at
the
hundreds
of
hospitals
and
and
associated
healthcare
facilities,
previously
being
able
to
detect
sepsis
at
hca's.
Hospitals
was
was
done
manually
by
the
nursing
staff
that
required
a
lot
of
time,
and
also
it
meant
that
the
patients
were
only
getting
diagnosed
say
evaluated
once
every
12
hours,
but
the
modality
rate
for
the
missed
or
delayed
diagnosis
is
significant.
A
A
A
A
A
So
the
result
is
a
five
hour
head
start
in
the
diagnosis
and
treatment
of
sepsis
for
clinicians.
That
means
saving
lives
now,
based
on
all
the
work
that
was
done
say
to
build
out
this
a
solution
for
sepsis
it's
earlier
in
the
year,
hca
healthcare
was
able
to
build
an
application,
that's
actually
helping
them
fast
track.
The
treatment
and
the
fight
against
kovite
19.
A
A
A
A
Bmw
group
faced
several
challenges
when
red
hat
first
engaged
with
them
in
2016.,
first
and
foremost
on
their
mind,
was
redesigning
the
connected
drive
platform
to
support
the
rapid
growth
and
offer
the
customers
new
services.
They
sell
roughly
2.5
million
cars
per
year
and
all
of
them
are
now
connected
devices.
A
Bmw
group
is
not
only
about
a
single
project
and
its
goal.
It's
about
the
digital
transformation
of
the
company
and
the
industry,
including
a
redesign
of
its
connected
car
system
to
support
the
anticipated
growth
in
the
connected
vehicles.
That's
how
red
hat
hybrid
cloud
platform
entered
the
picture
in
2016.