Karina Dahlke sits down with Gabriele Di Piazza and Erik McLaughlin to explore what it really takes to reach “level five” autonomous networking. They break down what autonomous networks mean in practice – self-configuring, self-healing, self-optimizing, and ultimately zero-touch operations – and why the conversation has accelerated again in the last few years with the rise of AI.
From cost pressure and growing network complexity to the foundational need for real-time observability, this episode offers a clear view into the technology, data, and governance required to make autonomous networks achievable at scale. Network experts and engineers at Ciena and Blue Planet bring deep network control plus cross-domain orchestration and intelligence, giving customers the visibility, context, and automation needed to accelerate the journey to level 5 autonomy.
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Hi, and welcome to
the latest edition
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of the Ciena Insights podcast.
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Today, we will be
talking about autonomous
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networks, getting
to level five.
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My name is Karina
Dahlke. I'm the head of
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marketing for Blue Planet,
a division of Ciena.
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I'm joined by two
Ciena leaders who
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work together
frequently and are very
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knowledgeable about
autonomous networks.
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Gabriele Di Piazza, VP of
Products, AI, Data Science,
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and Alliance at Blue
Planet, and And Erik
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McLaughlin, Senior Director
of Product Line Management.
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So, let's kick it off. Gabriele,
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do you want to
introduce yourself?
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Hi, everyone.
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As Karina said, my
name is Gabriele. I
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head up the products portfolio
here at Blue Planet.
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Obviously, autonomous
network is a key, not
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just a focus of ours,
but it's probably a strategic
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direction for the
portfolio, given that we
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operate in the space of
intelligent automation,
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telecom, telecom space.
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Great. And Erik?
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Hi, folks. I lead the
Navigator Network Control
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Suite, Product Line Management,
and Solutions Engineering
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here at Ciena, supporting
our hardware portfolio.
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Super.
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Okay, let's dive right in.
A lot of people are talking
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about autonomous networks.
So if you go to any trade
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show, you'll see that
theme everywhere, and it is
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definitely top of mind for
many of the service provider
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executives that we are
meeting with. So how about
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we start by defining what
autonomous networks means?
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Gabriele, if you want
to take a pass at it.
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Autonomous networks is not
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a new term for the industry.
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It's been an aspirational
path on how to
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basically evolve towards
this self-configuring,
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self-healing,
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self-optimizing, and ideally
zero-touch operations
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networks. It's a path
that is achieved across multiple
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steps. Ideally you would
remove manual operations across
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individual devices, domains,
and for overall services.
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I think there are some core
aspects here looking at
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real-time observability
expressing an intent of where you
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would like your network or
service to be reconciling
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this intent and of course,
perform a closed-loop
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remediation or automation and
over time, remove some of the
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manual interaction in these
different steps. Makes
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sense. So you're taking
out a lot of those manual
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processes, automating those
and injecting intelligence into
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the network. Erik, I'm
going to toss this question
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over to you. A few years ago,
we saw autonomous networks
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everywhere. It was all the
rage. And then all of a
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sudden it went out of style.
You didn't see it so much.
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You didn't hear people talking
about it. You didn't see
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it at trade shows. What do
you think has changed in
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the last two to three years
that makes autonomy feel
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like it's really achievable
now? Great question, Karina.
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And we go back a couple of
years when ChatGPT entered
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everyone's lives and everyone
started to interface with
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it. I think the visibility
of these frontier models
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like Gemini and Copilot in
everyone's day-to-day lives
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really opened up the door
to people starting to really
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think of how I could
leverage these large language
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models in a networking use
case. That brought to the
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attention of a lot of people
and a lot of focus around
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networking. Networking is
a prime place to drive some
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of these large language
models to drive reasoning.
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They're perfect. They require
a bunch of different aspects
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of the network to make
a decision, whether it's
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telemetry, instrumentation
from the devices, logs, alarms.
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So what better way to
have something than
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to have something that
can come and help and
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reason and act like
your virtual engineer?
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Exactly. It's like
augmenting your staff, right?
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That's right. Great. So
as you know, you both
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know, very familiar, TM
Forum provides a lot of tools
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for corporations to do
self-assessments on their
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level of autonomy. Gabriele,
what are you seeing
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in the market today?
What level of autonomy
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are we seeing when we
talk to customers today? I
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think this is a very
interesting question, Karina,
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because there is a wide
spectrum of responses to
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this. What we start to
see, which is refreshing,
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is the focus actually has
increased dramatically the
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last 6 to 12 months with
all this self-certification,
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self-valuation on these
levels i would say that we
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always see this aspect around
level two to level three
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but a lot of discussion
around how do we bridge this
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gap from level three to
level four but let me give
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a couple of examples just
in the last month we've been
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working with some fairly
large carriers and one of
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those they self-evaluating
themselves to be at level
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one which was a big surprise
On the other hand, I
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think this is a very humble
but practical assessment
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where they basically decided
that they need to get serious
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in instrumenting this
change. On the other hand,
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we see some advanced carriers
looking at, of course,
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you need to look at this
service by service, right?
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There's not a single number
of valuation for this.
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Looking at having reached
level four and starting to look
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at how to push towards a
level five autonomy and
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already talking about
managing hundreds of plus of
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agents in their networks. So
you see the spread varies,
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but I think this is the
natural state of the market.
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You can also think of some
of these operators having
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achieved some high level
of autonomy on a specific
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service and a lower level
autonomy in some other service.
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That's also very, very
typical. That makes a lot of
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sense. So like you said,
it's a pretty wide spectrum.
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There are going to be certain
instances that it would
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be a lot easier to have
some quick wins and achieve
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some autonomy. But to
achieve that, like level
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four, level five, you
really need to go across the
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different domains, which
is really, really complex,
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given the size and the
complexity of the networks.
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But I would say that if I
have to characterize this,
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a majority of the discussion
right now revolves
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around how to bridge level
three to level four autonomy,
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which means looking at
cross-domain automation,
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looking at injecting AI and
agenting capabilities for
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the reasoning that Erik
was discussing in order to
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understand intent and act
on basically having self
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-configuration based on that
specific intent. Perfect.
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Yeah. Taking that intent
and turning it into action.
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Erik, looking at this,
obviously the journey,
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there's a wide spectrum.
The journey is not something
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that's going to happen
overnight. So as service
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providers are thinking
about attaining this
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autonomy, what do you think
is a realistic progression
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or do you have some
suggestions for quick
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wins that you've seen
with your customers today?
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Definitely a pragmatic
progression I think is what
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we're hearing from our
customer conversations where
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they're looking to see how
can we embed intelligence
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into their existing workflows
and existing applications.
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So the engineers that
are using applications
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can see what's happening
and why. I think that then
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that starts to progress
towards guided actions,
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supervised actions, and then
eventually we get to the
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closed-loop operation, which
then introduces another
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area of test before you touch
or digital twin concepts,
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which is an important piece
of the whole autonomous
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network. So what I've
seen with our customers.
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It's they want to take a
very pragmatic approach
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around getting to that level
four, level five vision.
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And there's a lot of value
of what they can get today
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with some of the capabilities
that the industry is
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coming out with. So switching
gears a bit, what do you
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both of you think are some
of the operational pain
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points that are pushing service
providers towards autonomy
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today? Like we said, people
talked about it for a
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long time, and now it's
becoming a reality. So what do
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you think are some of those
pain points that are driving
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this change that we're
seeing with our customers?
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Gabriele, I'll ask
you first and then turn
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it over to Erik. I think
the key pain point is
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the cost pressure, that
it's unprecedented.
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We've observed this over
the years but we're not
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discussing anymore some
incremental two, three, four, five
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percent for example OPEX
reduction we know that there's
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an imbalance between
revenues and costs in the
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telecom space so we start
to see the desire or the
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pressure of reducing 20, 25, 30
or more on some operational
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costs. A lot of the operational
costs can be attributed
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to automation therefore
Autonomous Network
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becomes a recipe on how to
attain that. And I would say
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that this is not just
about cost, it's also about
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agility and the ability to,
as a result, being able to
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introduce new services
or create that cloud-like
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approach in provisioning
services in the front end, which
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is a big desire for many
carriers. So these are
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some of the two key aspects,
cost pressure on one side
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and the agility to introduce
services on the other.
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Yeah, and if I could maybe
add to Gabriele's point,
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I think the complexity
of networks, they're not
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necessarily getting simpler.
From a hardware CAPEX
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perspective and a lot of
new optical configurations
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where people are deploying
coherent plugs on routers
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and mixing and matching,
right? Looking for the best
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performing plugs on the
market and wanting to deploy
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on their existing router
base. So that might
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introduce CAPEX savings from
a hardware perspective, but
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adds some complexity on
the automation side and the
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software side. So that's
kind of an area where
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people are very interested
in looking at automation and
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simplifying those workflows
and just the scale of
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networks that are growing,
with AI on the network
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and training data sets,
there's a huge pressure on
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optical networks across the
globe. So how do we bring
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automation, not just from
a monitoring standpoint,
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but also from a commissioning point?
How do I get the
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equipment faster and deployed
quicker in the ground?
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From putting in the ground
to lights on to optimizing
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the solution for the use
case that it's delivering.
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And Erik, I like your
point here because
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you started by saying
that networks are not
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becoming simpler these
days. Configuration,
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you mentioned data,
different endpoints,
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but also the amount of
services. We are discussing many
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cases where they realize
that there's an overlaying
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of cloud services and B2B
services. And this also
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introduces new areas of
what you need to manage and
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automate. So it actually
becomes a matrix of complexity,
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not just one single dimension,
but it becomes almost an
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exponential complexity going
forward. Yeah, exactly.
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And that complexity is not
slowing down at all. I was
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at a recent industry
conference and a large tier
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one provider was talking about
why he was moving towards
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an autonomous network.
And that was exactly the
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point that he brought up.
The thousands of different
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parameters in the network,
the thousands of different
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devices, hundreds of
different domains. It was just
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beyond human capacity to
manage it all. So that's a
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big push, right? It's just
that it's got beyond us.
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There's not many
greenfield networks
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out there. They
got to worry about
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what's in the
ground already too.
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Exactly. How to tie that
all together. Super.
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Okay. So if we look at,
now we understand there's
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definitely a need for
autonomous networks. We're
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seeing people move in that
direction. We're seeing
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real examples. How do we
get there? Gabriele, I'll
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toss this one over to
you. What are some of the
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foundational things that
you need for an autonomous
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network? If somebody wants
to start their journey,
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what is one of the first
steps they should take?
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I touched a little bit at
the beginning where some of
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the core aspects are really
starting to abstract the
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majority of your network
resources. In this way, you
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can actually treat this as
individual services that you
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can then compose over time.
The ability to express
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an intent to start in terms
of your desired state,
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having observability at
different levels that can then be
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composed into something that
you want to feed into an
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engine. We haven't talked
deeply yet about how AI
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plays a role here and how you
can interpret what actions
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to be taken. There's the
understanding of the different
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domain and how each domain
has its own specific
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needs and what is programmable
or not. Ideally, the
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journey here, you don't go
from one to five or zero to
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five just by implementing
some AI, but you need to start
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looking at each of the
building blocks and exposing
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and abstract some of these
building blocks. This is on
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the technology side. Then
there's a cultural aspect
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where you need to apply new
skills these days. You need
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to look at how analytics
AI and even DevOps or net
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DevOps and cloud plays a role
into this. And that's why
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we see some of the most
transformational projects
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here needs to be driven top
down, not just bottoms up.
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That's a really good point.
So it's a cultural shift.
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Yeah, adding to Gabriele's
points, a lot of the
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activities that we've been
spending over the last couple of
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years is what I'd call
cleaning up the network, just
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getting the right visibility
of what's in the network
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at the software domain.
Because deploying networks from
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whatever, 5, 10, 15 years
ago, it was all about how do
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we get the network up? Is
it passing traffic, passing
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bit-error test, but no one's
put that same amount of
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energy on the software
side. So if the software
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applications can't see the
data from the network, then you
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have a partial AI insight or
partial insights from your
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applications. So that presents
a problem. So that's why
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we've been very focused
over the last little while,
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getting our networks cleaned
up through a variety of
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methods. And I think once
you have that foundation and
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ensuring that telemetry is
coming from the network,
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enabling those telemetry
interfaces off the devices
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themselves. So you're streaming
data as opposed to SNP data.
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So you can have those intelligent
insights flow through.
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Both of you brought up a
great point that in order
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for the network to take actions
and take the appropriate
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actions, the network needs
to have visibility into
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the underlying data. What
is actually in the network,
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the data. So if you could
comment a little bit more on
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that, because I do think
that's foundational and both
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Ciena and Blue Planet have
done a lot of work in that
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area to make sure that we
can give our customers access
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to the right data at the
right time so that agents,
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the acting with autonomy,
can act on the basis of
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correct information and take
the appropriate actions. I
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want to go back to one of
our monikers here. We keep
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saying you cannot AI what
you cannot see, which was a
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little bit of an evolution of
you cannot automate what you
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cannot see. Visibility is
key. We start to introduce
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and discuss the topic of
AI. Erik mentioned the
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observability. It's very, very
important now. So network is
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an incredible source of data.
It has been forever, but
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now this data can be used
with different techniques.
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And by the way, this is one
of the best aspects of having
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Ciena and Blue Planet part of the
same company here because
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we can go so deep in the
network to the network control
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that Ciena provides through
the Navigator Control
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Suite, at the same time applying
some of the cross-domain
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capability or cross-platform
capabilities that Blue Planet
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provides. So to me, the
aspect is having clean data
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is very important. It's
not enough because you need
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to apply one of the key aspects
that the industry needs.
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It is domain knowledge.
You need to understand the
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domain. You need to understand
the constructs of this
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data. You need to understand
the entity relationships.
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And only through that,
you can extract the
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right insights, whether
those insights are
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related to planning
aspects or operational
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aspects or customer
experience aspects.
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So I would say this is a key
aspect. In our world, this
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happens through, obviously,
deep integration in how
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we keep our teams aligned.
Erik and I, we work very
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closely together. So right
off the factory, you can
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say that we have our platforms
being integrated. And
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it's actually refreshing
to see how this is evolving
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from having been integrated
API levels and data level
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and now evolving into deep
agentic level as well.
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So we can actually apply
advanced reasoning through
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agents that are basically
interacting with each other.
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One of the points you
brought up, Gabriele, is on
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domain knowledge. I think
that's a huge thing of
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providing strong context to
networking from a networking
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company. Who better to
provide actionable insights or
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autonomous capabilities on
the IP optical layer than
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Ciena and Blue Planet? That's
what our customers come to
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us for our expertise and a
software package that can
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deliver on that and drive
those insights with a
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specific view around context,
around the domains. And if
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you think about it, this
combination is almost
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unmatched in the industry to
have the ability to span this
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knowledge from some of
the business constructs or
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the way down to the network
constructs. It's very
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interesting to see. Perfect.
And having that rich telemetry
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fed into the upper layers
of the network and to
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be able to have that two
-way communication back and
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forth, provide that context
is incredibly important.
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As we wrap it up, it's been
a great discussion today.
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I know we talked a little
bit about the end, about
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how Ciena and Blue Planet
are working together. Are
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there any final closing
thoughts? Erik, I'll start
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with you that you'd like
to leave our customers with
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on their journey. Maybe just
to reiterate Gabriele's
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point. We're under the same
roof and we're executing
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on our program plans the
benefit of having stuff
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being tested prior to going
to the market, conversations
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across product line
management and across our
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customer base, looking at
key use cases that address
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from the device to the OSS
level. And we're on our way
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to having that full agentic
framework from the device
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level all the way to
the OSS level across the
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portfolio. Great. Gabriele,
any closing thoughts? The
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other aspect is it's also
very important to understand
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the type of governance that
we put in place. In the
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past, we discussed about
devices, then evolved into
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software platforms. Now
we are injecting this AI
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domain, which means how do
you secure, how do you govern,
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how you manage a lifecycle,
some of these aspects. And
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this is also key for the
success of this evolution to
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make basically the automation
components moving from
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reactive to proactive and
eventually to prescriptive.
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So you can have true
simulation, gaining
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confidence and so forth to
move towards a level five
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of autonomy that would
remove some of the
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manual actions or any
manual actions out there.
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Great. Well, thank you
both. And with that, I will
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wrap it up. I want to thank
both of you for sharing your
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insights and really for working
daily with our customers
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to support them in their
autonomous networking
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journeys, both at the OSS
layer and the control layer.
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So thank you for the
great conversation today.
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Thanks, Karina.
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And to our listeners, you
can subscribe to our Ciena
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00:20:27,790 --> 00:20:31,590
Insights podcast on Apple
Podcasts, on the public
371
00:20:31,590 --> 00:20:35,950
radio apps for Android
users, and now on Spotify. So
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00:20:35,950 --> 00:20:39,330
you can also find all of our
podcasts on our website at
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ciena.com slash podcast
thanks for your time today