►
Description
The Enterprise Neurosystem Initiative at America Movil
Karlo Piceno (América Móvil)
Raul Reyes (América Móvil)
William Wright (Red Hat)
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
B
B
C
Hello,
my
name
is:
I
am
in
charge
of
fighting
infrastructure
and
cloud
services
optimizations.
I
have
been
in
america
mobile
for
five
years
now
and
my
main
focus
has
been
to
enable
and
empower
the
different
and
distributed
teams
in
latin
america.
So
so
we
can
be
always
evolving
and
always
getting
more
of
the
innovation
in
the
operation.
A
A
So
here
we
go
one
of
the
core
things
we've
thought
about
over
the
years
is
just
that
human
and
I.t
architecture
share
a
number
of
strong
similarities,
and
we
just
noticed
this
more
and
more,
especially
with
the
advent
of
artificial
intelligence
and
which
really
is
kind
of
the
completion
of
this
parallel
model.
You
know
when
you
think
about
it
and
you've
got
all
these
mobile
devices.
They
could
be
considered
almost
nerve
endings,
they
have
the
capability
of
hearing
and
you
know
sound
and
visual
identification
and
then
data
centers,
really
equal.
A
The
brain's
functions
in
a
lot
of
ways
like
the
cerebellum
and
memory
and
processing,
cpus
and
so
what's
interesting.
Is
there
really
is
a
kind
of
a
parallel
model?
You
know
we
as
a
you
know:
species
have
created
something
that's
very
similar.
You
know
in
many
respects,
and
so
in
terms
of
the
human
body.
The
more
core
operations
are
fully
autonomous
like
the
heartbeat
chemical
levels,
the
way
we
assimilate
energy
and
it
still
partitions,
conscious
thought
processes
as
part
of
that
too.
A
And
that's
where
we
have
ended
up
today,
which
is
a
new
ai
and
machine
learning,
telco
community
right
now,
which
is
called
the
enterprise
neurosystem,
and
this
is
about
ai
infrastructure,
basically
connected
to
every
single
business
function
across
the
enterprise
and
we're
definitely
starting
with
telco
from
that
perspective.
But
it
will
be
applicable
to
all
verticals
because
there
are
every
corporation
in
the
fortune.
A
So
it
basically
unifies
and
optimizes
an
entire
multinational
corporation
at
that
scale,
with
a
single
ai
and
ml
framework,
and
it
enables
like
I
said
before,
the
overarching
cross-correlation
of
all
these
different
data
points,
but
then,
what's
interesting
is
over
time
edge
and
core
ai.
All
those
instances
become
part
of
one
system
and
it
just
provides
any
form
of
management,
whether
it's
you
know
mid-tier
management
or
the
c-suite,
with
a
real-time
view
of
all
operations
and
we've
thought
about
a
lot
of
creative
applications.
A
A
If
you
take
a
look,
we've
got
all
the
core
open
source
components
like
linux
and
self
storage
and
kubernetes
et
cetera,
and
then
we
have
the
open
data
hub
framework
which
allows
you
to
use
open
source
ai
platform
tooling,
to
create
models
and
get
them
into
production
and
maintain
them,
and
then
also
that
would
then
lead
into
the
ai
neurosystem.
And
so
you
would
connect
the
neural
system
to
it,
and
then
it
would
basically
propagate
from
there
and
connect
to
all
these
different
areas.
A
Like
the
finance
area,
network
operations,
facilities,
management,
legal
and
regulatory
frameworks,
human
resources,
I
mean
go
down
the
list.
All
these
different
areas
would
then
be
cross-connected
and
integrated
together
to
feed
back
all
this
data
into
the
system
and
here's
kind
of
a
low-level
architecture
example
and
again
just
an
example.
A
You
would
have
ai
and
ml
instances
in
all
these
different
areas
of
operation,
network
operations,
I.t
and
then
the
knock
itself,
and
what
would
then
happen
is
quite
literally,
they
would
then
be
connected
to
yet
another
kind
of
smaller
and
more.
I
guess
a
streamlined
group
of
ai
and
ml
instances
and
they
could
be
gans.
They
could
be
all
sorts
of
different
ai
frameworks
that
would
take
the
the
lower
level
findings
and
begin
to
create
a
tree
of
logic,
basically
or
a
tree
of
perception.
A
That
would
then
take
all
that
information
begin
to
filter
it
and
begin
to
draw
out
these
kind
of
correlations
that
can
lead
to
deeper
insight
and
so
over
time.
You
would
have
this
same
framework
in
every
different
business
instance,
and
it
would
then
go
up
into
let's
say
a
second
or
third
or
fourth
tier
of
different
gans
or
different
ai
frameworks
into
transformer
frameworks
or
other
ai
frameworks,
because
we'll
be
using
and
borrowing
from
a
lot
of
different
areas
to
create
this
and
ultimately
into
the
recommendation
engine.
A
That
would
then
basically
convey
the
results
and
the
observations
and
the
insights
to
management
and
the
c-suite,
and
this
would
involve
a
federated
intelligence
model,
so
you'd
be
taking
all
the
different
ai
models,
cross-correlating
all
their
data,
creating
a
reporting
intelligence.
That
would
basically
then
turn
to
management.
As
I
said
before
and
relay
all
this
information
and
again
we
would
start
with
perhaps
a
dashboard
on
the
left.
A
Just
as
an
example
then,
on
screen,
maybe
some
form
of
you
know
human
representation
and
then
eventually
a
hologram
or
some
other
form
of
intelligence
that
would
convey
this
to
to
basically
their
their
colleagues
on
the
human
side
and
so
what's
interesting
about
this
too,
is
we
have
found
in
actually
mit
had
discovered
this
as
well,
is
that
the
combination
of
human
and
machine
is
actually
3x
more
powerful
than
either
one
alone.
So
machines
will
have
a
certain
error
rate.
A
Humans
will
have
a
certain
error
rate,
but
together
they
actually
reduce
the
error
rate
to
almost
less
than
a
percentage,
and
so
in
many
use
cases
that
we've
examined,
and
so
really
what
we're
seeing
is
this
kind
of
merging
of
the
abilities
of
both
sides
of
that
coin,
into
something
that's
actually
greater
and
more
powerful,
and
so
in
terms
of
work
streams.
We're
looking
at
different
areas,
we'll
have
a
series
of
excuse
me
open
models
that
we'll
offer
we'll
work
on
an
open
data
platform
and
a
middleware
solution,
basically
to
cross
connect.
A
And
then
the
good
news
is
a
lot
of
existing
open
source
offerings
and
frameworks
frameworks
can
be
applied.
Today
there
will
be
a
few
things
that
need
to
be
created,
but
in
essence
all
the
groundwork
has
already
been
laid
by
open
source
communities
in
terms
of
the
tooling
we
can
use,
and
ultimately
there
are
cross-vertical
applications
in
financial
services
or
oil
and
gas,
and
all
these
different
industries
can
take
this
kind
of
a
framework
and
apply
it
to
their
own
operations.
A
So
it's
actually
a
very
exciting
time
for
us
and
you
know
we're
just
getting
it
off
the
ground
and
we've
already
had
meetings
and
I've
got
things
moving.
So
I'd
like
to
now
turn
basically
to
to
carlo
and
raul,
and
I'd
like
to
ask
you
a
few
questions
along
these
lines
as
well.
I
think,
what's
interesting
is
the
fact
that
america
mobile
got
involved
in
this
so
early
on,
is
really
exciting
and
the
fact
that
you
basically
not
only
kick-started
us
in
this
direction,
but
you're
also
really
embracing
the
open
source.
A
I
guess
you
could
say
methodology
and
way
of
doing
things
we
think
is
wonderful,
so
you
know,
I
think,
really.
Maybe
you
can
talk
a
little
bit
about
the
value
of
collaborating
in
the
open
with
your
peers,
like
verizon,
media,
equinix
and
others.
I'd
love
to
hear
about
like
really
what
convinced
you
to
do
so
to
move
in
that
direction.
B
C
Well,
yeah,
I
totally
agree.
I
totally
agree
sorry
for
that,
for
the
I
mentioned
that
we
think
that
the
open
source
projects
are
now
the
de
facto
option
no
in
order
to
to
solve
big
challenges.
So
today
we
see
more
and
more
and
more
challenges
coming
our
way,
and
it
will
be
impossible
for
us
as
a
single
group,
to
tackle
all
these
constant
change
at
the
pace
as
we
are
seeing
today.
C
You
know
so
so
we
are
doing
this
because
we
think
that
the
future
of
open
source
is
promising
and
from
the
community,
the
open
source
shapes
the
technological
evolution
and
the
creation
of
an
environment
that
leads
to
constant
innovation.
We
think
that
if
we
do
not
do
this
this
way,
it
will
be
impossible
for
us
in
the
future.
A
No,
it's
really
exciting.
You
guys
have
been
wonderful
partners
in
that
regard
and
I
think
it's
been
wonderful
to
see
the
industry
support.
But
what
about
like?
What
about
the
technical
value?
I
mean
what
are
the
advantages
of
creating
this
kind
of
a
multinational
ai
instance
to
manage
and
study
your
global
operations
in
real
time
and
to
help
you
manage
them?
B
Well,
usually,
I
think
operators
like
us
face
very
complex
maintenance
processes.
So
one
of
the
goals
we
have
is
around
the
process,
optimization
with
the
ability
to
take
autonomous
decisions,
considering
dynamic
conditions,
so
in
general,
adopting
an
artificial
intelligence
and
machine
learning.
Logic
will
give
us
the
advantage
to
reduce
operational
costs
and,
at
the
same
time,
reduce
the
failures
in
the
network.
B
By
having
this
predictive
logic
and
as
we
have
operations
across
most
of
the
latin
american
region,
we
will
also
have
the
advantage
to
learn
how
to
apply
this
methodology
in
similar
scenarios
in
all
of
our
outcomes.
With
this
multinational
instance
and
the
common
load
knowledge
between
all
of
the
countries.
C
Yeah,
sorry,
so
we
believe
we
believe
that
having
the
technology
that
focuses
on
on
predicting
and
managing
the
behavior
of
our
operations
will
allow
us
to
forecast
more
effectively
now
and
also,
hopefully,
we
we
will
plan
the
work
assigned
in
in
our
notes,
hopefully
before
every
error
or
mistake
occurs
right.
So
so
before
that
it
happens
now,
so
machine
learning
will
help
us
to
learn
faster
as
well.
C
B
A
B
C
Well
on
it's
interesting
how
how
ai
and
human
cognitions
are
now
collaborating
in
many
ways,
as
you
mentioned
before.
No,
I
think
that
in
one
side
the
humans
train
and
explain
the
machine
learning
models
and
also
they
maintain
new
and
create
new
models.
You
know,
and
on
the
other
hand,
I
think
the
the
ai
brings
more
data
and
better
insights.
C
A
B
C
Yeah
yeah
totally,
I
I.
We
think
that
using
a
property
approach
will
never
give
us
the
openness
and
the
flexibility
we
need
in
order
to
build
the
effective
solution,
so
open
source
communities
from
our
perspective
create
more
competition,
and
when
there
is
more
competition,
the
price
is
reduced
as
well.
So
the
massive
acceptance
of
a
successful
open
source
project
is
very
powerful,
so
so
we
need
to
provide
a
neutral
home
for
it
we
need
and
to
protect
it.
B
Also,
openshift
provides
very
good
devops
tools
with
a
smart
life
cycle
management
of
containers
through
kubernetes
orchestration,
which
give
us
the
advantage
to
accelerate
the
development
around
the
new
trends,
for
instance
like
network
slicing
and
enabling,
for
instance,
solutions
at
the
edge
of
the
network.
So
definitely
openshift
is
very
valuable
for
us.
C
For
sure,
for
sure
for
sure
today,
openshift
allow
us
to
to
take
the
containers
and
put
them
in
the
right
place.
It
allows
us
to
manage
them,
show
them
and
shoot
them
down.
If
we
see
any
problem,
we
are
building
today
microservices
and
moving
workloads
from
different
clouds.
Now,
because
I
think
that
there
is
so
much
to
be
done
that
we
have
not
harnessed
the
full
potential
of
these
type
of
environments,
so
so
container
platforms
provide
an
easy
and
repeatable
and
portable
environments
and
deployments
on
a
diverse,
very
diverse
infrastructure,
and
also
so.
A
Wow
fantastic
well,
thank
you
for
the
endorsement.
I
really
appreciate
that,
but
more
than
that,
thank
you
for
your
partnership
and
your
leadership
in
this
area
with
us.
I
mean
it's
been
really
exciting
to
work
with
both
of
you
and
america
mobile
on
this
initiative
and
with
our
partners
and
wow.
I'm
just
very
grateful
and
just
want
to
thank
you
both
for
your
time
today
and
I
think
we'll
leave
it
at
that.
But
again,
thank
you
very
much.