March 24, 2026
S4E5: AI, Cloud & Sustainability: Reality vs. Hype
AI is everywhere in sustainability right now — but what’s genuinely changing on the ground, and what’s still hype?
In this episode of Sustainability Forward, hosts Wrishi Sutradhar and Carmine Fiume sit down with Carlos Silva Willson, a global technology and partnerships leader at Microsoft Middle East with prior experience across GE/Baker Hughes and AWS.
Carlos brings a practical, “been-in-the-room” perspective on what AI and cloud can realistically deliver for sustainability — and what leaders should be cautious about as adoption accelerates.
In the conversation, we cover:
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Where AI + cloud are already creating measurable sustainability value (beyond dashboards and buzzwords)
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Why partnerships and ecosystems matter if climate solutions are going to scale
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The hard questions around AI’s footprint: data centres, energy demand, and water use
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How to think about trust, accountability, and credible impact claims
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The changing talent landscape: the skills that will define climate-tech careers in the years ahead
If you work in sustainability, climate-tech, energy, or digital transformation, this episode will help you separate signal from noise — and focus on what’s scalable, credible, and useful.
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Hello and welcome to
Sustainability Forward, the show
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where we explore the ideas,
technologies and the leadership
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choices shaping a more
sustainable future and the
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transition to it.
I'm your host Rishi.
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With me is my Co host, Carmine.
How are you, Carmine?
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Ciao Rishi, all good.
Nice to be back.
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Ciao.
OK, Today we are going to talk
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about something that's moving
incredibly fast.
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At least that's the perception
right now.
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And that is the intersection of
AI, cloud and sustainability.
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Every week there seems to be a
new announcement, whether it is
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about new tools, new claims or
new promises.
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But for sustainability leaders,
the real question is quite
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simple and it is what is
actually changing on the ground?
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What is hype and how do we
scale?
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What actually is working?
And to unpack that, we have an
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exciting guest who's experienced
multiple sides of of this
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equation.
Carmine.
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Let's get into the introduction
of our guest for today.
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Sure.
So today we have Carlos Silva
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Wilson with us.
He's a global technology
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partnership leader at Microsoft
Middle East whose Korea spans
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from General Electric, Baker
Yuks in the US and Europe,
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Amazon UK and now in Middle East
rapidly evolving innovation
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landscape.
Carlos is originally from
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Venezuela.
He studied economics as an
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undergraduate as in the US and
then completed an Executive MBA
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at the University of Edinburgh.
Carlos brings a unique lens on
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how cloud and AI can drive
sustainability, economic
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opportunity and social impact,
drawing from deep international
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experience and the passion from
for empowering diverse
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communities.
So, Carlos Hola, welcome to the
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show.
Thank you so much for having me.
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Big fan of your of the work you
are doing on this podcast.
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Thank you, Carlos.
Welcome.
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Now, Carlos, before we get into
the details of of this topic,
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tell us a little bit.
When you look at what's
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happening right now with AI and
cloud, particularly in the area
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of sustainability, what's the
sort of big shift you think most
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leaders, most leaders are
underestimating or or struggling
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with at the moment?
There is, by the way, this is a
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super exciting, super exciting
topic and and I want to give you
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as well some context as to why
it excites me and why I decided
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to to make a bit of a shift
right.
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It's been a quite a journey, as
you described, Carmine, from,
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from helping drilling
contractors and operators in the
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North Sea to being up there in
the cloud, as we say.
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So I've been able to see both
side of the equation.
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I mean, one of the, one of the
parallels I try to draw to
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understand a bit more the, the
shift and, and, and the
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transformational time we're,
we're going through is the, the
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massive investments going into
infrastructure, right?
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And you know, we in, in
humanity, I think we, we, we've
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been here before, right?
If you think about the UK in
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1840 with the railroad
infrastructure building, there
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was what they used to call the
the railway mania, right?
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There was massive amount of
infrastructure that build and,
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and there was a lot of question
marks around whether that's that
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was going to be a success or
not.
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And of course, a lot of
companies went on there and
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they've created a bit of a
bubble, but in the long term, it
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benefited massively, right?
This, this for me, as I think
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about kind of the poles in the
ground, this is kind of the
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question mark, right?
The question mark is, you know,
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is there too much or or too
little infrastructure for for
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what AI is going to be, right?
Is it a bubble or not?
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Is it a hype or not?
And you know, in all honesty, I
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don't think anyone has the
answer.
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But what what we do know and
what we're seeing is a rapid
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transformation that companies
are seeing, at least the ones
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that adopt and the countries
that adopt AI, you know,
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Microsoft with the AI economy
studies, they have been
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releasing what we call the
diffusion report.
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And the diffusion report
clearly, you know, stipulates
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and shows countries that are
Fast forward on adoption of AI
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technologies and, and the
results of those countries that
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are Fast forward on adoption and
their citizens is obviously
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massive amounts of
productivities that we're seeing
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at both the corporate level, but
also at country level.
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So I think I think it's a very
important, you know, aspect to
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grasp, understand and also see
it as an opportunity versus a
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threat, which I'm sure it will
come up in the discussion as
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that's essentially the big
elephant in the room, right?
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The the role of data centers and
infrastructure on the
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sustainability side, both as an
ally but also a potentially as
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an enemy.
Interesting, very interesting.
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And let's post a second about
this, this potential dilemma and
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let's go back more on our
personal, your personal journey.
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So you mentioned you're coming
from the industry from from
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Allegas, you went to G then
Becky Dukes, what they're
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working on now and compared to
that, what's your view on this
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energy transition and
decarbonization?
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This is this is a really good
segue to to give you guys a bit
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of background.
So one of the reasons I joined
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the AWS after spending the 10
plus years in Yi and Baker was
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the pivotal role I really saw on
hyperscalers and data center
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companies having in the
sustainability space, both as
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being on the demand side of
energy.
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Today, hyperscalers dominate the
leaderboard when it comes to
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renewable power purchase
agreements, but also by enabling
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companies to achieve their
climate targets through data
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center infrastructure right.
These being compute, networking,
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storage capacity needed to run
advanced workloads and and
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really solve those harder
problems while providing
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scalability and reliability.
I also had the chance to see
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first hand the leading role that
cloud technologies was playing
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in the sustainability space
during my time in Baker Hughes.
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There was what was a newly
created innovation offer
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development team and we really
work directly with hyperscalers
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on on building tech driven value
proposition in the
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decarbonization space,
especially on hard to abate
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sectors.
So this really allowed me to
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appreciate how many answers to
the climate challenge could be
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influenced by cloud
technologies, right?
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I think another important aspect
that that we'll talk that I
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think a bit more in the in the
podcast is the bilateral
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relationship that is being
developed by hyperscalers and
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energy companies.
You know, today hyperscalers are
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becoming some of the main
customers of their own energy
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customers, right back to the PBA
discussion.
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So this has really opened
exciting opportunities to
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collaborate in different ways.
And you know, I think that the
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funny part is that leaving Baker
Hughes and joining AWS back in
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November 2021 and during COVID
times, the real talk of the
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town, if you guys remember and
maybe this is when you launch
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the podcast, was sustainability
everywhere.
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You know, integrated energy
companies in Europe were
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shifting rapidly strategies and
capital allocation into a
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greener position.
But Fast forward today, the with
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the official launch of course,
of ChatGPT in November 20, 2022,
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the discussion quickly shifted
into AI and it has only
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intensified today and it will
continue that way, right?
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So I think this is where we we
cross that dilemma that you
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Richie and Caminia were were
kind of anticipating, which is,
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you know, data center
infrastructure being seen both
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as an ally for solving climate
change, but also GHE greenhouse
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gas emission offender, right.
And this is what what I think
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it's the bigger question at the
the level that you guys are are
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proposing.
Yeah.
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No, no, exactly.
And it's helpful context to
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understand the world from where
you came to to your current
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current setting.
And just to explore that a
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little bit, I wanted to ask you
about, you know, something
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that's that's more practical.
So in your view today, how is
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cloud or cloud and AI actually
enabling kind of faster climate
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innovation, decarbonization?
Of course, you know, in energy
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companies there's a lot of
modeling going on.
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But beyond these big buzzwords,
do you see specific examples
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that that are helping the
day-to-day activities?
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This is this is a fascinating
topic.
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Thank you, Rishi.
I mean, one, one thing that that
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that I'm really focused on is
really finding those, you know,
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business use cases, right,
because we really believe that
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this is where we will be able to
move the, the needle and find
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those answers.
So when it comes to technology
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driven eye transformation, the
way, the way at least in
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Microsoft, we we interpret these
with our customers is, you know,
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the opportunity side.
You're really touching a couple
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of buckets, right?
These are aligned to, you know,
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reinventing customer engagement,
reshaping business processes and
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reaching employee and
experience.
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And the most fascinating for me
is on the bending the curve of
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innovation to your point, right.
So if we stay on the innovation
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side of things for a second,
which is probably the most
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relevant for our discussion,
there are amazing examples out
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there around how the cloud is
powering sustainable innovation
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at speed and scale.
You know, and this really
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illustrates the potential of
cloud when we focus on
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sustainability more broadly.
Some examples that I really like
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and some are are close to home
here in the UAE.
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There is one around the Emirates
Global Aluminium, right, one of
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the largest aluminium producers.
This is the largest export of
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the UAE after oil and gas, where
the organization is really
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focusing on what what we know is
a very energy intensive process
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of converting of course alumina
to aluminium without getting
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very technical.
It's very important of course
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for automotive, aerospace and
other industries with the cloud.
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Today EGA has established an AI
driven quality monitoring system
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that can inspect 100% of the all
the anodes in real time, which
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was a process that before was
being done manually and only
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covering 2% of the supply.
Yeah.
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So for me, this example brings
the message home of how much,
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you know, cloud technologies can
help companies improve quality
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control and efficiency.
Another one that that I find
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really interesting was the work
that Microsoft this did with
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scientists recently at Pacific
Norwest National Lab to apply AI
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in materials discovery.
AI was used to find a new
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battery material, one that needs
less lithium in a matter of
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weeks.
And normally these kind of
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breakthrough takes years of
trials and and error in lab
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research, right.
So these these AI driven battery
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discoveries is crucial for clean
energy.
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So some of these examples for me
really illustrate the power of
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of cloud technologies. 11 last
one that that I find there that
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I find really interesting
because I'm a I'm a consumer
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myself.
It's a pure harvest on the
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agriculture side.
You know, obviously in the in
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the UAE, it's very hard to grow
things due to the to the land,
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but using AI and machine
learning and IoT, this company
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today is improving food security
by by farming high quality,
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affordable produce.
So today I'm able to buy
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strawberries from, from these
hydroponic farm and, and, and
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this is, and leveraging
essentially cloud technologies
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to, to achieve the right
conditions for, for those, for
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those producers to, to harvest,
right.
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So these, I mean, these are
examples that I think bring the
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point close to home.
And I'm I'm sure there is many
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more out there that people would
resonate with.
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Yeah, no, it's, it's very
pertinent, very exciting as
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well.
I, I read yesterday or maybe the
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day before that the tech GPT 5.2
or GPT 5.2 with the model has,
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has achieved some kind of
breakthrough recently with in
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theoretical physics, right?
Essentially core writing, core
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writing, you know, new
breakthroughs with, with
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academicians and experts.
One side question, Carlos, that
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I had for you was give us a
little bit of, you know, the
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feel of the Middle East when it
comes through comes to AI and
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cloud from here in Europe.
We hear hear stories about how
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many countries in the Middle
East are sponsoring, you know,
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regional initiatives to to make
the region a powerhouse.
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So give us a little bit of
context of how it feels to be to
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be based there and, and, and
actually being involved in this
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field.
Absolutely.
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And I'll probably, I will
probably focus a bit more in the
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UAE since this is where majority
of the work is happening, at
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least on my side, but also some
of the exciting upcoming
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projects in, in Saudi, which we
know it's an economy that is,
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that has lots of potential.
But look, the, the UAE for me,
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it's an amazing example.
If I draw some parallels as well
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or compare with my, with my home
country, Venezuela.
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Venezuela has three times more
the oil and gas reserves of the
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UAE, but we are definitely very
far away in terms of execution.
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The UAE has grasped extremely
well the opportunity in front
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when it comes to to AI.
In fact, the UAE National
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Strategy for AI 2031 states a
clear statement, which is AUA
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wants to become the world's most
prepared country for artificial
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intelligence.
And we can see this on the news
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by funding, you know, very
important projects that that
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we've seen and consortiums
between NVIDIA open AI and
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different announcements that
have been made.
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But also on the ground, I mean
on the ground the UA is really
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walking the talk and a couple of
things are important to to
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share.
So people grasp, grasp a bit of
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of the trajectories.
The UAE today has appointed a
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UAE minister of state for
artificial intelligence.
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They expect to unlock 91 billion
AI driven extra growth for the
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country.
And they have really prioritized
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couple of sectors, resources,
energy, logistics, transport,
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hospitality, healthcare and
cybersecurity.
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The national AI strategy today
from AI ready to AI leader by
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2031 aligns very well as well
with the country's overall
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mission of being the best
country in the world, right?
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So what what we see is a real
kind of multifaceted approach on
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collaboration that has really
dictated the pace for other
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countries to to see it as an
example.
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And then if you go one level
down, sorry, on the cities and
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peace, this is where the
diffusion report is actually
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showing that on adoption of AI
technologies, UAE, it's one of
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the leading countries today.
The last point Rishi, that I
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think is really important to, to
mention is that the, the, the
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countries that we see leading
and UAE of course being one of
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them.
What I see is the multifaceted
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approach that is being driven in
country for this sort of
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innovation, right.
And and there's a couple of
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elements I would like to call
out that are really important.
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On one side, the cross industry
adoption is super important and
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this of course is with customers
at the core.
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The second one for me is human
capital people first, the
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upscaling strategies that the
country is really driving with
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the help of of hyperscalers and
different players.
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It's second to none
partnerships.
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Of course, this continues to be
a a very important point with
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engineering center in the UAE
being established 1,000,000 UAE
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learners on AI by 2027, the
skilling initiatives, the G42 on
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Microsoft partnership, These are
some of the examples.
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Technology at the core again is
really important.
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00:17:01,320 --> 00:17:05,240
The announcement recently of
NVIDIA shipping, shipping chips
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over to to the UA is another
important point.
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And last one is this government
direction with here.
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It's an exemplary.
And then of course, companies
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like us are working backwards
from a clear vision.
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So I hope this gives you a bit
of an idea of what it feels to
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be here.
Just lastly, touching a bit on,
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on Saudi, you know, it was
publicly announced recently
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that, you know, there's going to
be a data center infrastructure
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established by the end of the
year as well.
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00:17:33,600 --> 00:17:36,400
So there's a lot of excitement
about what that means for for
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the Kingdom.
And you know, these are these
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00:17:40,480 --> 00:17:43,600
are, you know, great
opportunities, I think for other
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countries to also learn from
what's happening.
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00:17:45,880 --> 00:17:49,880
You know, if you think about the
UAE 57 years ago, it was, it
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00:17:49,880 --> 00:17:53,800
was, it was not even a country,
you know, and the speed at which
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they have moved and knowing that
today they are ahead of a lot of
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countries in this AI race, it's,
it's a great example and
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inspiration.
Yes, indeed it is.
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Carlos, we know that working on
the the challenge of climate
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change and sustainability, this
is not something that can be
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00:18:15,360 --> 00:18:20,560
solved probably by incremental
addition.
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00:18:20,720 --> 00:18:24,080
It's a probably a system change
and we touched multiple times in
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the podcast around it.
So partnership ecosystems
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00:18:28,080 --> 00:18:34,040
becomes critical.
Based on your experience, what
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00:18:34,520 --> 00:18:37,960
what does good look like when
different companies collaborate
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00:18:38,080 --> 00:18:44,640
on climate solution?
This this is a very important
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00:18:45,080 --> 00:18:50,120
point, Carmina, especially
because touching back on the
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00:18:50,120 --> 00:18:53,600
multi faceted approach, you
know, partnerships are key here,
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not only from the deployment of
capital technology, but also on
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the use case piece.
You know, one of the things that
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00:19:00,200 --> 00:19:05,360
at my level I face very often
is, you know, proving the value
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right.
Because at the end of the day, a
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lot of the use cases that today
contain a big opportunity for
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00:19:12,120 --> 00:19:16,440
transformational change, you
know, the way of course,
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00:19:16,440 --> 00:19:19,200
companies are evaluating these
opportunities tends to be quite
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00:19:19,200 --> 00:19:22,880
traditional, right?
So you have to really, you know,
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00:19:22,880 --> 00:19:26,920
bring a different set of
stakeholders to the table and
315
00:19:26,920 --> 00:19:30,000
proving the the value
proposition that these use cases
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00:19:30,000 --> 00:19:32,760
could could provide in return,
right?
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00:19:32,760 --> 00:19:37,280
So when it comes to this, you
know, you really need a vision
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00:19:37,280 --> 00:19:39,640
that is driven from top.
And this is not only the
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00:19:39,640 --> 00:19:42,800
company, but also from the
different kind of players on
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00:19:42,800 --> 00:19:45,400
the, on the equation to your to
your point.
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00:19:45,400 --> 00:19:48,480
And that includes obviously the
regulatory frameworks in place.
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That includes obviously the
capital allocation from the
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00:19:50,560 --> 00:19:53,440
company, that includes division
from the leadership and that
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00:19:53,440 --> 00:19:55,760
includes as well as strong
partners that can deliver.
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00:19:55,760 --> 00:19:59,280
You know, I think we've seen
very recently on a lot of
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00:19:59,280 --> 00:20:03,840
statistics that were going
around about the the lack of ROI
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00:20:03,840 --> 00:20:07,240
of a lot of projects that are
not, you know, implemented
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00:20:07,240 --> 00:20:10,680
properly are not assessed
properly, data foundations not
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00:20:10,680 --> 00:20:14,000
being in place, so.
There is, there is of course,
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00:20:14,000 --> 00:20:18,000
you know, a big need to come to
the table with the right players
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around the right problem and,
and really looking at it from a
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00:20:20,760 --> 00:20:24,520
problem and not from a company
perspective, right.
333
00:20:25,320 --> 00:20:27,320
This is, this is what I'm seeing
on the ground.
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00:20:27,320 --> 00:20:30,000
This is where I get most
involved with with my job in
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partners, specifically on the
system integration piece.
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00:20:32,880 --> 00:20:36,400
And you know, we spend a lot of
time more on the, you know,
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00:20:36,400 --> 00:20:39,960
ideation phase just to make sure
that we have, you know, minimum
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viable products that are really
bringing all those stakeholders
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00:20:43,320 --> 00:20:47,360
together with confidence around,
you know, the execution and the
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00:20:47,360 --> 00:20:52,000
deployment of a, of a specific
project linked to A to a
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00:20:52,000 --> 00:20:59,080
business problem.
Interesting, Carlos, we
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00:20:59,200 --> 00:21:04,000
obviously talked about, you
know, the the exciting things,
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00:21:04,000 --> 00:21:08,480
things which are likely to be
needle movers in this space.
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00:21:09,000 --> 00:21:16,040
But as AI scales and data center
load tends to, you know,
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00:21:16,080 --> 00:21:19,880
increase and every, every now
and then we hear about a new
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announcement like you mentioned
in the case of Saudi.
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00:21:23,640 --> 00:21:29,520
It also brings us to to this
aspect of are we trying to solve
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one problem and in the process
creating a big one, right?
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00:21:34,360 --> 00:21:37,840
In other words, the risks
associated with this big growth.
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00:21:38,240 --> 00:21:42,920
So we hear frequently about the
high energy consumption, we hear
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00:21:42,920 --> 00:21:49,200
about the high land grab in one
sense and we also hear about the
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00:21:49,680 --> 00:21:54,160
significant consumption of of
water for cooling these data
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00:21:54,160 --> 00:21:57,640
centers, right.
Can you talk a little bit about
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00:21:57,640 --> 00:22:00,920
these aspects and what you are
seeing on the ground?
355
00:22:02,800 --> 00:22:07,640
Absolutely.
So look, this is this is a very
356
00:22:07,640 --> 00:22:11,760
important point of discussion.
If you think about the AI
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00:22:11,760 --> 00:22:15,480
economy, you know, just to put
things into perspective, by
358
00:22:15,480 --> 00:22:18,480
20-30 is expected to reach 4
trillion, right?
359
00:22:18,480 --> 00:22:24,200
This is, you know, this is
slightly below what what India's
360
00:22:24,200 --> 00:22:26,640
economy is today.
So just to give you an idea on
361
00:22:26,640 --> 00:22:29,480
the magnitude, right?
So if we, if we look then on the
362
00:22:29,480 --> 00:22:32,520
other side on the greenhouse gas
emissions that today data
363
00:22:32,520 --> 00:22:37,080
centers are driving, you know,
it's around a 0.5% to 3.5,
364
00:22:37,080 --> 00:22:39,880
right?
But this is expected to reach 8%
365
00:22:39,880 --> 00:22:43,160
by 2030, right?
The reason for that is because
366
00:22:44,440 --> 00:22:48,640
we have more and more power
hungry data centers as we think
367
00:22:48,640 --> 00:22:52,520
about, you know, solving more
complex problems, you know, AI
368
00:22:52,520 --> 00:22:55,720
workloads, we're doing a lot of
training inferencing at the end
369
00:22:55,720 --> 00:22:58,320
of the day, driving logical
conclusion through compute.
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00:22:58,320 --> 00:23:03,240
So this is this is very energy
intensive as as you mentioned,
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00:23:03,240 --> 00:23:05,080
both on the cooling and heating
side.
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00:23:06,400 --> 00:23:10,240
I mean another important point
into perspective just to just to
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00:23:10,240 --> 00:23:13,400
say the same data centers in
terms of percentage of global
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00:23:13,400 --> 00:23:17,160
energy demand today's 1.5 to 3%
and it's going to be 2X by
375
00:23:17,160 --> 00:23:20,200
20-30.
So it's definitely a point that
376
00:23:20,200 --> 00:23:23,600
we cannot avoid and we need to
have the debate around what what
377
00:23:23,600 --> 00:23:26,640
gives me hope is that if you
think about the architecture of
378
00:23:26,640 --> 00:23:31,280
some of these data centers and
the the advanced innovation that
379
00:23:31,280 --> 00:23:34,720
we're seeing the in the out on
chips and we're seeing on as
380
00:23:34,720 --> 00:23:39,160
well on the incorporation of
renewable energy combined with
381
00:23:39,160 --> 00:23:41,840
base loading.
Some of these data centers are
382
00:23:41,840 --> 00:23:43,960
closer and closer to power
sources.
383
00:23:44,720 --> 00:23:48,160
This for me, gives me a lot of
hope around, you know, the way
384
00:23:48,160 --> 00:23:51,720
at which data center
infrastructure is innovating by
385
00:23:51,720 --> 00:23:54,360
answering the question of being
more efficient, being more
386
00:23:54,360 --> 00:23:57,960
reliable and, and, and being
cleaner, right?
387
00:23:57,960 --> 00:24:01,160
I think this is if, if you look
at the, the kind of statements
388
00:24:01,160 --> 00:24:04,560
of, of, of most of the
hyperscalers today by 20-30
389
00:24:04,560 --> 00:24:08,920
around sustainability, it's
really a strong commitment
390
00:24:08,920 --> 00:24:12,200
towards being carbon, carbon
neutral, if not negative, right.
391
00:24:12,200 --> 00:24:16,200
So of course this brings a
different discussion around how
392
00:24:16,200 --> 00:24:19,480
that's measured and the whole
debate around how companies are
393
00:24:20,080 --> 00:24:24,400
are, you know, are proving this.
But for me, the direction of
394
00:24:24,400 --> 00:24:27,680
travel is pretty clear and the
companies that we see leading
395
00:24:27,680 --> 00:24:32,480
the, the kind of data center
landscape are, are really
396
00:24:32,480 --> 00:24:37,400
progressing fast and super,
super focused on driving that
397
00:24:37,400 --> 00:24:44,000
energy demand down.
Carlos, let's try to close the
398
00:24:44,000 --> 00:24:46,240
circle gear with a final
question.
399
00:24:46,240 --> 00:24:51,920
So we started with your journey.
Let's finish also on a question
400
00:24:51,920 --> 00:24:55,440
on the people side.
So let's look, let's look at the
401
00:24:56,960 --> 00:25:03,240
the evolving skill set for
climate tech professional as as
402
00:25:03,240 --> 00:25:06,040
we discussed in cloud AI
technologies become more
403
00:25:06,040 --> 00:25:09,760
foundational.
So what's your take on that and
404
00:25:09,960 --> 00:25:13,720
what kind of advice can you give
to young professional entering
405
00:25:13,720 --> 00:25:18,240
this space, especially those who
are coming from a transition as
406
00:25:18,240 --> 00:25:22,120
you did?
It's a very good point.
407
00:25:22,120 --> 00:25:24,000
I'll start with the last one on
the advice.
408
00:25:24,000 --> 00:25:30,000
I think 11 phrase that is is
very present on on my
409
00:25:30,000 --> 00:25:33,920
day-to-day.
It's AI will replace the people
410
00:25:33,920 --> 00:25:38,000
that, that, that don't get close
to AI, don't understand it and
411
00:25:38,000 --> 00:25:41,000
don't use it.
You know, So my, my advice is,
412
00:25:41,920 --> 00:25:44,720
you know, take advantage of the
opportunity because this is a
413
00:25:44,720 --> 00:25:48,200
really pivotal moment in, in our
society, in our world, in our
414
00:25:48,200 --> 00:25:50,760
countries, in our, in our
workplace as well.
415
00:25:50,760 --> 00:25:54,520
So it presents opportunities and
we need to see it from that lens
416
00:25:54,520 --> 00:25:57,000
because I think it really holds
a lot of the answers we're
417
00:25:57,000 --> 00:26:01,880
looking for when it comes to the
skill set, specifically for
418
00:26:02,520 --> 00:26:06,480
climate tech professionals,
we're seeing a blending of
419
00:26:06,480 --> 00:26:09,640
disciplines, if you will.
You know, traditionally you had
420
00:26:09,640 --> 00:26:12,560
environmental scientists, you
have engineers, you had policy
421
00:26:12,560 --> 00:26:15,880
experts, and separately you had
software developers and data
422
00:26:15,880 --> 00:26:18,960
scientists, right?
Increasingly we're seeing more
423
00:26:18,960 --> 00:26:23,760
and more the the world needs
needs people who who can do both
424
00:26:23,760 --> 00:26:26,600
really or at least work in
multidisciplinary teams
425
00:26:26,600 --> 00:26:29,480
effectively.
For example, a data analyst
426
00:26:29,480 --> 00:26:32,440
today might need to understand
atmospheric science and be able
427
00:26:32,440 --> 00:26:34,600
to write Python code and run AI
models.
428
00:26:34,600 --> 00:26:37,440
An engineer working on renewable
energy might benefit from
429
00:26:37,440 --> 00:26:40,320
knowing cloud computing to
manage IoT sensors, data from
430
00:26:40,320 --> 00:26:45,000
solar forms as well.
So the key skill set for me is
431
00:26:45,000 --> 00:26:47,720
tech fluency and domain
expertise.
432
00:26:47,720 --> 00:26:50,360
If you are coming from the tech
side, I would say get curious
433
00:26:50,360 --> 00:26:52,040
about climate and energy
systems.
434
00:26:52,040 --> 00:26:55,480
Learn the basics of power grids,
carbon accounting, agriculture,
435
00:26:55,960 --> 00:26:59,680
and if you're coming from the
environmental side, it pays to
436
00:26:59,680 --> 00:27:04,160
gain data and AI skills even
through online courses or
437
00:27:04,160 --> 00:27:05,960
machine learning or cloud
platforms.
438
00:27:05,960 --> 00:27:09,960
There's a lot of available free
accessible material out there
439
00:27:09,960 --> 00:27:14,600
that I would recommend people
have a look and with with your
440
00:27:14,600 --> 00:27:16,760
support guys.
I'm happy to also share some
441
00:27:16,760 --> 00:27:21,680
links that Microsoft is also
providing for for people to
442
00:27:21,680 --> 00:27:25,000
understand not only the pace of
Change the Diffusion report, but
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00:27:25,000 --> 00:27:29,120
also to to obscure themselves in
these technologies.
444
00:27:30,040 --> 00:27:32,720
Yeah, that'd be good.
We will reference those in the
445
00:27:32,720 --> 00:27:35,480
show notes.
And by the way, as you were
446
00:27:35,480 --> 00:27:39,080
talking, I was, I mean mind
something I was reading early
447
00:27:39,080 --> 00:27:43,680
this morning.
So yes, probably now we're view
448
00:27:43,680 --> 00:27:46,640
of the world, we think these are
kind of technology that widely
449
00:27:46,640 --> 00:27:48,760
used.
But if I look at it from a
450
00:27:48,760 --> 00:27:53,000
helicopter view, probably 80
between 8090% of the world
451
00:27:53,000 --> 00:27:57,520
population still is not close to
AI, not even having some
452
00:27:57,520 --> 00:28:00,280
accounts.
So there is a sometimes we
453
00:28:00,280 --> 00:28:05,840
forget that in the the many
daily activities that can be
454
00:28:07,280 --> 00:28:10,600
improved or touched by these new
technologies, and today they are
455
00:28:10,600 --> 00:28:15,120
very far from it.
Yeah, from we went from energy
456
00:28:15,120 --> 00:28:18,520
growth to the topic of energy
access as you know a global
457
00:28:18,520 --> 00:28:21,640
community and already coming in
based on what you're saying, we
458
00:28:21,640 --> 00:28:26,440
are going from AI growth to AI
access, which might be the next,
459
00:28:26,920 --> 00:28:29,800
next wave.
Carlos, thank you.
460
00:28:29,800 --> 00:28:34,160
And, you know, this has been a
really interesting conversation.
461
00:28:35,640 --> 00:28:38,520
Thank you very much guys.
Pleasure and looking forward to
462
00:28:38,520 --> 00:28:41,560
continue the discussion from
from different angles as we are
463
00:28:41,560 --> 00:28:44,600
all very important players on on
this topic.
464
00:28:45,520 --> 00:28:49,120
Yes, absolutely.
What I'm taking away from this
465
00:28:49,120 --> 00:28:54,600
conversation, Carmine, is well
one, AI and cloud are very
466
00:28:54,600 --> 00:28:58,400
powerful, especially when
they're tied to some real world
467
00:28:59,040 --> 00:29:01,680
outcomes or operational
decisions and not just
468
00:29:01,800 --> 00:29:06,840
reporting.
And two, I think I also I also
469
00:29:06,840 --> 00:29:10,440
heard Carlos talking about
partnerships as you, as you
470
00:29:10,440 --> 00:29:14,840
mentioned this is not a problem
to be solved by one organization
471
00:29:14,840 --> 00:29:19,920
or one entity and therefore you
know multi stakeholder approach
472
00:29:20,200 --> 00:29:23,120
is needed.
Any takeaways Carmina you had on
473
00:29:23,120 --> 00:29:25,600
this?
And I think the ecosystem
474
00:29:25,600 --> 00:29:29,240
matters.
I think Carlos describes what's
475
00:29:29,240 --> 00:29:31,960
happening for example, in the
Emirates and how they reach the
476
00:29:31,960 --> 00:29:36,040
kind of level of speed also
because of the right probably
477
00:29:36,360 --> 00:29:41,000
ecosystem that is in place.
Indeed, that's that's another
478
00:29:41,000 --> 00:29:44,840
key aspect.
So if you enjoyed this episode
479
00:29:44,880 --> 00:29:49,440
of Sustainability Forward, make
sure to subscribe to the podcast
480
00:29:49,440 --> 00:29:52,440
and share it with someone
working at the intersection of
481
00:29:52,440 --> 00:29:55,960
sustainability and technology
and join the conversation with
482
00:29:55,960 --> 00:30:00,840
us on LinkedIn or one of the
podcast platforms on which we
483
00:30:00,840 --> 00:30:04,240
are present.
Would love to hear what you're
484
00:30:04,240 --> 00:30:07,640
seeing in terms of real progress
and what questions you are
485
00:30:07,720 --> 00:30:10,840
dealing with.
Again, Carlos, thank you for
486
00:30:10,840 --> 00:30:13,320
joining us.
Carmine, thank you to you as
487
00:30:13,320 --> 00:30:15,120
well.
Thanks for listening.
488
00:30:15,120 --> 00:30:17,600
We'll see you next time on
Sustainability Forward.
00:00:08,760 --> 00:00:12,720
Hello and welcome to
Sustainability Forward, the show
2
00:00:12,720 --> 00:00:17,080
where we explore the ideas,
technologies and the leadership
3
00:00:17,080 --> 00:00:20,800
choices shaping a more
sustainable future and the
4
00:00:20,800 --> 00:00:23,560
transition to it.
I'm your host Rishi.
5
00:00:24,000 --> 00:00:26,880
With me is my Co host, Carmine.
How are you, Carmine?
6
00:00:27,920 --> 00:00:29,960
Ciao Rishi, all good.
Nice to be back.
7
00:00:30,480 --> 00:00:35,000
Ciao.
OK, Today we are going to talk
8
00:00:35,000 --> 00:00:38,920
about something that's moving
incredibly fast.
9
00:00:38,920 --> 00:00:41,640
At least that's the perception
right now.
10
00:00:42,160 --> 00:00:46,200
And that is the intersection of
AI, cloud and sustainability.
11
00:00:47,000 --> 00:00:51,000
Every week there seems to be a
new announcement, whether it is
12
00:00:51,000 --> 00:00:54,920
about new tools, new claims or
new promises.
13
00:00:55,680 --> 00:01:01,880
But for sustainability leaders,
the real question is quite
14
00:01:01,880 --> 00:01:05,960
simple and it is what is
actually changing on the ground?
15
00:01:06,360 --> 00:01:10,000
What is hype and how do we
scale?
16
00:01:10,320 --> 00:01:15,720
What actually is working?
And to unpack that, we have an
17
00:01:15,720 --> 00:01:20,480
exciting guest who's experienced
multiple sides of of this
18
00:01:20,480 --> 00:01:22,640
equation.
Carmine.
19
00:01:23,080 --> 00:01:26,640
Let's get into the introduction
of our guest for today.
20
00:01:27,360 --> 00:01:30,680
Sure.
So today we have Carlos Silva
21
00:01:30,680 --> 00:01:33,880
Wilson with us.
He's a global technology
22
00:01:33,880 --> 00:01:38,200
partnership leader at Microsoft
Middle East whose Korea spans
23
00:01:38,320 --> 00:01:41,200
from General Electric, Baker
Yuks in the US and Europe,
24
00:01:41,880 --> 00:01:45,960
Amazon UK and now in Middle East
rapidly evolving innovation
25
00:01:45,960 --> 00:01:48,960
landscape.
Carlos is originally from
26
00:01:48,960 --> 00:01:52,160
Venezuela.
He studied economics as an
27
00:01:52,160 --> 00:01:56,800
undergraduate as in the US and
then completed an Executive MBA
28
00:01:56,800 --> 00:02:01,640
at the University of Edinburgh.
Carlos brings a unique lens on
29
00:02:01,640 --> 00:02:06,080
how cloud and AI can drive
sustainability, economic
30
00:02:06,080 --> 00:02:10,199
opportunity and social impact,
drawing from deep international
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00:02:10,199 --> 00:02:13,440
experience and the passion from
for empowering diverse
32
00:02:13,600 --> 00:02:18,280
communities.
So, Carlos Hola, welcome to the
33
00:02:18,280 --> 00:02:22,680
show.
Thank you so much for having me.
34
00:02:22,760 --> 00:02:25,680
Big fan of your of the work you
are doing on this podcast.
35
00:02:26,760 --> 00:02:28,680
Thank you, Carlos.
Welcome.
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00:02:29,360 --> 00:02:34,200
Now, Carlos, before we get into
the details of of this topic,
37
00:02:35,240 --> 00:02:38,040
tell us a little bit.
When you look at what's
38
00:02:38,040 --> 00:02:42,800
happening right now with AI and
cloud, particularly in the area
39
00:02:42,800 --> 00:02:47,800
of sustainability, what's the
sort of big shift you think most
40
00:02:47,800 --> 00:02:52,320
leaders, most leaders are
underestimating or or struggling
41
00:02:52,320 --> 00:02:57,240
with at the moment?
There is, by the way, this is a
42
00:02:57,240 --> 00:03:01,000
super exciting, super exciting
topic and and I want to give you
43
00:03:01,000 --> 00:03:05,080
as well some context as to why
it excites me and why I decided
44
00:03:05,080 --> 00:03:06,880
to to make a bit of a shift
right.
45
00:03:06,880 --> 00:03:11,000
It's been a quite a journey, as
you described, Carmine, from,
46
00:03:11,000 --> 00:03:13,120
from helping drilling
contractors and operators in the
47
00:03:13,120 --> 00:03:15,280
North Sea to being up there in
the cloud, as we say.
48
00:03:15,280 --> 00:03:18,680
So I've been able to see both
side of the equation.
49
00:03:19,200 --> 00:03:23,480
I mean, one of the, one of the
parallels I try to draw to
50
00:03:23,480 --> 00:03:26,600
understand a bit more the, the
shift and, and, and the
51
00:03:26,600 --> 00:03:29,640
transformational time we're,
we're going through is the, the
52
00:03:29,640 --> 00:03:32,120
massive investments going into
infrastructure, right?
53
00:03:32,520 --> 00:03:36,320
And you know, we in, in
humanity, I think we, we, we've
54
00:03:36,320 --> 00:03:38,840
been here before, right?
If you think about the UK in
55
00:03:38,840 --> 00:03:41,840
1840 with the railroad
infrastructure building, there
56
00:03:41,840 --> 00:03:44,880
was what they used to call the
the railway mania, right?
57
00:03:44,880 --> 00:03:48,520
There was massive amount of
infrastructure that build and,
58
00:03:48,800 --> 00:03:51,640
and there was a lot of question
marks around whether that's that
59
00:03:51,640 --> 00:03:54,240
was going to be a success or
not.
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00:03:54,240 --> 00:03:56,520
And of course, a lot of
companies went on there and
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00:03:56,520 --> 00:03:59,840
they've created a bit of a
bubble, but in the long term, it
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00:03:59,840 --> 00:04:05,480
benefited massively, right?
This, this for me, as I think
63
00:04:05,480 --> 00:04:08,000
about kind of the poles in the
ground, this is kind of the
64
00:04:08,000 --> 00:04:11,120
question mark, right?
The question mark is, you know,
65
00:04:11,200 --> 00:04:15,720
is there too much or or too
little infrastructure for for
66
00:04:15,720 --> 00:04:18,200
what AI is going to be, right?
Is it a bubble or not?
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00:04:18,200 --> 00:04:20,519
Is it a hype or not?
And you know, in all honesty, I
68
00:04:20,519 --> 00:04:22,000
don't think anyone has the
answer.
69
00:04:22,400 --> 00:04:26,000
But what what we do know and
what we're seeing is a rapid
70
00:04:26,000 --> 00:04:29,360
transformation that companies
are seeing, at least the ones
71
00:04:29,360 --> 00:04:31,880
that adopt and the countries
that adopt AI, you know,
72
00:04:32,240 --> 00:04:36,480
Microsoft with the AI economy
studies, they have been
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00:04:36,480 --> 00:04:38,600
releasing what we call the
diffusion report.
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00:04:38,600 --> 00:04:42,480
And the diffusion report
clearly, you know, stipulates
75
00:04:42,480 --> 00:04:45,720
and shows countries that are
Fast forward on adoption of AI
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00:04:45,720 --> 00:04:49,080
technologies and, and the
results of those countries that
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00:04:49,080 --> 00:04:52,480
are Fast forward on adoption and
their citizens is obviously
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00:04:52,760 --> 00:04:54,880
massive amounts of
productivities that we're seeing
79
00:04:54,880 --> 00:04:57,480
at both the corporate level, but
also at country level.
80
00:04:57,480 --> 00:05:02,320
So I think I think it's a very
important, you know, aspect to
81
00:05:02,320 --> 00:05:06,120
grasp, understand and also see
it as an opportunity versus a
82
00:05:06,120 --> 00:05:08,720
threat, which I'm sure it will
come up in the discussion as
83
00:05:09,280 --> 00:05:11,440
that's essentially the big
elephant in the room, right?
84
00:05:11,440 --> 00:05:14,280
The the role of data centers and
infrastructure on the
85
00:05:14,280 --> 00:05:17,600
sustainability side, both as an
ally but also a potentially as
86
00:05:17,600 --> 00:05:22,000
an enemy.
Interesting, very interesting.
87
00:05:22,720 --> 00:05:27,200
And let's post a second about
this, this potential dilemma and
88
00:05:27,200 --> 00:05:29,920
let's go back more on our
personal, your personal journey.
89
00:05:29,960 --> 00:05:35,000
So you mentioned you're coming
from the industry from from
90
00:05:35,000 --> 00:05:39,840
Allegas, you went to G then
Becky Dukes, what they're
91
00:05:39,840 --> 00:05:43,720
working on now and compared to
that, what's your view on this
92
00:05:43,720 --> 00:05:45,840
energy transition and
decarbonization?
93
00:05:46,960 --> 00:05:50,000
This is this is a really good
segue to to give you guys a bit
94
00:05:50,000 --> 00:05:52,720
of background.
So one of the reasons I joined
95
00:05:52,760 --> 00:05:56,640
the AWS after spending the 10
plus years in Yi and Baker was
96
00:05:56,720 --> 00:06:00,400
the pivotal role I really saw on
hyperscalers and data center
97
00:06:00,400 --> 00:06:03,600
companies having in the
sustainability space, both as
98
00:06:03,600 --> 00:06:05,480
being on the demand side of
energy.
99
00:06:06,200 --> 00:06:09,080
Today, hyperscalers dominate the
leaderboard when it comes to
100
00:06:09,080 --> 00:06:11,800
renewable power purchase
agreements, but also by enabling
101
00:06:11,800 --> 00:06:14,920
companies to achieve their
climate targets through data
102
00:06:14,920 --> 00:06:18,240
center infrastructure right.
These being compute, networking,
103
00:06:18,240 --> 00:06:21,600
storage capacity needed to run
advanced workloads and and
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00:06:21,600 --> 00:06:24,360
really solve those harder
problems while providing
105
00:06:24,360 --> 00:06:28,320
scalability and reliability.
I also had the chance to see
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00:06:28,320 --> 00:06:31,400
first hand the leading role that
cloud technologies was playing
107
00:06:31,400 --> 00:06:34,400
in the sustainability space
during my time in Baker Hughes.
108
00:06:34,960 --> 00:06:38,200
There was what was a newly
created innovation offer
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00:06:38,200 --> 00:06:42,480
development team and we really
work directly with hyperscalers
110
00:06:42,520 --> 00:06:45,000
on on building tech driven value
proposition in the
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00:06:45,000 --> 00:06:47,800
decarbonization space,
especially on hard to abate
112
00:06:47,800 --> 00:06:50,200
sectors.
So this really allowed me to
113
00:06:50,200 --> 00:06:53,440
appreciate how many answers to
the climate challenge could be
114
00:06:53,440 --> 00:06:55,320
influenced by cloud
technologies, right?
115
00:06:57,120 --> 00:07:02,480
I think another important aspect
that that we'll talk that I
116
00:07:02,480 --> 00:07:05,400
think a bit more in the in the
podcast is the bilateral
117
00:07:05,400 --> 00:07:08,480
relationship that is being
developed by hyperscalers and
118
00:07:08,480 --> 00:07:11,440
energy companies.
You know, today hyperscalers are
119
00:07:11,440 --> 00:07:14,480
becoming some of the main
customers of their own energy
120
00:07:14,480 --> 00:07:16,840
customers, right back to the PBA
discussion.
121
00:07:16,840 --> 00:07:20,400
So this has really opened
exciting opportunities to
122
00:07:20,400 --> 00:07:23,200
collaborate in different ways.
And you know, I think that the
123
00:07:23,200 --> 00:07:28,280
funny part is that leaving Baker
Hughes and joining AWS back in
124
00:07:28,280 --> 00:07:31,680
November 2021 and during COVID
times, the real talk of the
125
00:07:31,680 --> 00:07:35,200
town, if you guys remember and
maybe this is when you launch
126
00:07:35,200 --> 00:07:37,120
the podcast, was sustainability
everywhere.
127
00:07:37,120 --> 00:07:39,440
You know, integrated energy
companies in Europe were
128
00:07:39,440 --> 00:07:42,600
shifting rapidly strategies and
capital allocation into a
129
00:07:42,600 --> 00:07:46,400
greener position.
But Fast forward today, the with
130
00:07:46,400 --> 00:07:51,120
the official launch of course,
of ChatGPT in November 20, 2022,
131
00:07:51,440 --> 00:07:54,320
the discussion quickly shifted
into AI and it has only
132
00:07:54,320 --> 00:07:57,360
intensified today and it will
continue that way, right?
133
00:07:57,360 --> 00:08:02,560
So I think this is where we we
cross that dilemma that you
134
00:08:02,560 --> 00:08:06,200
Richie and Caminia were were
kind of anticipating, which is,
135
00:08:06,600 --> 00:08:09,480
you know, data center
infrastructure being seen both
136
00:08:09,520 --> 00:08:13,360
as an ally for solving climate
change, but also GHE greenhouse
137
00:08:13,360 --> 00:08:18,080
gas emission offender, right.
And this is what what I think
138
00:08:18,080 --> 00:08:23,040
it's the bigger question at the
the level that you guys are are
139
00:08:23,040 --> 00:08:24,880
proposing.
Yeah.
140
00:08:25,400 --> 00:08:28,360
No, no, exactly.
And it's helpful context to
141
00:08:28,360 --> 00:08:32,559
understand the world from where
you came to to your current
142
00:08:33,080 --> 00:08:36,360
current setting.
And just to explore that a
143
00:08:36,360 --> 00:08:40,679
little bit, I wanted to ask you
about, you know, something
144
00:08:40,679 --> 00:08:45,440
that's that's more practical.
So in your view today, how is
145
00:08:45,840 --> 00:08:53,080
cloud or cloud and AI actually
enabling kind of faster climate
146
00:08:53,080 --> 00:08:57,560
innovation, decarbonization?
Of course, you know, in energy
147
00:08:57,560 --> 00:09:00,120
companies there's a lot of
modeling going on.
148
00:09:00,120 --> 00:09:06,080
But beyond these big buzzwords,
do you see specific examples
149
00:09:06,080 --> 00:09:10,440
that that are helping the
day-to-day activities?
150
00:09:11,560 --> 00:09:14,240
This is this is a fascinating
topic.
151
00:09:14,240 --> 00:09:17,960
Thank you, Rishi.
I mean, one, one thing that that
152
00:09:18,440 --> 00:09:22,200
that I'm really focused on is
really finding those, you know,
153
00:09:22,240 --> 00:09:25,160
business use cases, right,
because we really believe that
154
00:09:25,160 --> 00:09:28,440
this is where we will be able to
move the, the needle and find
155
00:09:28,440 --> 00:09:31,280
those answers.
So when it comes to technology
156
00:09:31,280 --> 00:09:34,360
driven eye transformation, the
way, the way at least in
157
00:09:34,360 --> 00:09:40,120
Microsoft, we we interpret these
with our customers is, you know,
158
00:09:40,120 --> 00:09:42,400
the opportunity side.
You're really touching a couple
159
00:09:42,400 --> 00:09:45,960
of buckets, right?
These are aligned to, you know,
160
00:09:45,960 --> 00:09:49,640
reinventing customer engagement,
reshaping business processes and
161
00:09:49,640 --> 00:09:51,160
reaching employee and
experience.
162
00:09:51,160 --> 00:09:54,440
And the most fascinating for me
is on the bending the curve of
163
00:09:54,440 --> 00:09:58,160
innovation to your point, right.
So if we stay on the innovation
164
00:09:58,160 --> 00:10:01,240
side of things for a second,
which is probably the most
165
00:10:01,520 --> 00:10:05,080
relevant for our discussion,
there are amazing examples out
166
00:10:05,080 --> 00:10:08,080
there around how the cloud is
powering sustainable innovation
167
00:10:08,080 --> 00:10:11,000
at speed and scale.
You know, and this really
168
00:10:11,000 --> 00:10:13,960
illustrates the potential of
cloud when we focus on
169
00:10:13,960 --> 00:10:19,120
sustainability more broadly.
Some examples that I really like
170
00:10:20,040 --> 00:10:22,720
and some are are close to home
here in the UAE.
171
00:10:24,000 --> 00:10:27,280
There is one around the Emirates
Global Aluminium, right, one of
172
00:10:27,280 --> 00:10:30,800
the largest aluminium producers.
This is the largest export of
173
00:10:30,800 --> 00:10:34,760
the UAE after oil and gas, where
the organization is really
174
00:10:34,760 --> 00:10:39,960
focusing on what what we know is
a very energy intensive process
175
00:10:39,960 --> 00:10:43,160
of converting of course alumina
to aluminium without getting
176
00:10:43,160 --> 00:10:45,800
very technical.
It's very important of course
177
00:10:45,800 --> 00:10:49,160
for automotive, aerospace and
other industries with the cloud.
178
00:10:49,160 --> 00:10:53,400
Today EGA has established an AI
driven quality monitoring system
179
00:10:53,400 --> 00:10:58,640
that can inspect 100% of the all
the anodes in real time, which
180
00:10:58,640 --> 00:11:01,920
was a process that before was
being done manually and only
181
00:11:01,920 --> 00:11:03,880
covering 2% of the supply.
Yeah.
182
00:11:04,440 --> 00:11:09,840
So for me, this example brings
the message home of how much,
183
00:11:09,880 --> 00:11:13,000
you know, cloud technologies can
help companies improve quality
184
00:11:13,000 --> 00:11:16,680
control and efficiency.
Another one that that I find
185
00:11:16,800 --> 00:11:20,920
really interesting was the work
that Microsoft this did with
186
00:11:21,040 --> 00:11:25,880
scientists recently at Pacific
Norwest National Lab to apply AI
187
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in materials discovery.
AI was used to find a new
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battery material, one that needs
less lithium in a matter of
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weeks.
And normally these kind of
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breakthrough takes years of
trials and and error in lab
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research, right.
So these these AI driven battery
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discoveries is crucial for clean
energy.
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So some of these examples for me
really illustrate the power of
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of cloud technologies. 11 last
one that that I find there that
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I find really interesting
because I'm a I'm a consumer
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myself.
It's a pure harvest on the
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agriculture side.
You know, obviously in the in
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the UAE, it's very hard to grow
things due to the to the land,
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but using AI and machine
learning and IoT, this company
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today is improving food security
by by farming high quality,
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affordable produce.
So today I'm able to buy
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strawberries from, from these
hydroponic farm and, and, and
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this is, and leveraging
essentially cloud technologies
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to, to achieve the right
conditions for, for those, for
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those producers to, to harvest,
right.
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So these, I mean, these are
examples that I think bring the
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point close to home.
And I'm I'm sure there is many
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more out there that people would
resonate with.
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Yeah, no, it's, it's very
pertinent, very exciting as
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well.
I, I read yesterday or maybe the
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day before that the tech GPT 5.2
or GPT 5.2 with the model has,
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has achieved some kind of
breakthrough recently with in
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theoretical physics, right?
Essentially core writing, core
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writing, you know, new
breakthroughs with, with
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academicians and experts.
One side question, Carlos, that
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I had for you was give us a
little bit of, you know, the
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feel of the Middle East when it
comes through comes to AI and
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cloud from here in Europe.
We hear hear stories about how
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many countries in the Middle
East are sponsoring, you know,
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regional initiatives to to make
the region a powerhouse.
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So give us a little bit of
context of how it feels to be to
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be based there and, and, and
actually being involved in this
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field.
Absolutely.
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And I'll probably, I will
probably focus a bit more in the
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UAE since this is where majority
of the work is happening, at
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least on my side, but also some
of the exciting upcoming
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projects in, in Saudi, which we
know it's an economy that is,
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that has lots of potential.
But look, the, the UAE for me,
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it's an amazing example.
If I draw some parallels as well
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or compare with my, with my home
country, Venezuela.
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Venezuela has three times more
the oil and gas reserves of the
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UAE, but we are definitely very
far away in terms of execution.
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The UAE has grasped extremely
well the opportunity in front
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when it comes to to AI.
In fact, the UAE National
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Strategy for AI 2031 states a
clear statement, which is AUA
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wants to become the world's most
prepared country for artificial
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intelligence.
And we can see this on the news
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by funding, you know, very
important projects that that
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we've seen and consortiums
between NVIDIA open AI and
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different announcements that
have been made.
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But also on the ground, I mean
on the ground the UA is really
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walking the talk and a couple of
things are important to to
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share.
So people grasp, grasp a bit of
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of the trajectories.
The UAE today has appointed a
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UAE minister of state for
artificial intelligence.
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They expect to unlock 91 billion
AI driven extra growth for the
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country.
And they have really prioritized
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couple of sectors, resources,
energy, logistics, transport,
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00:15:25,000 --> 00:15:26,920
hospitality, healthcare and
cybersecurity.
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The national AI strategy today
from AI ready to AI leader by
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2031 aligns very well as well
with the country's overall
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mission of being the best
country in the world, right?
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So what what we see is a real
kind of multifaceted approach on
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collaboration that has really
dictated the pace for other
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countries to to see it as an
example.
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And then if you go one level
down, sorry, on the cities and
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peace, this is where the
diffusion report is actually
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showing that on adoption of AI
technologies, UAE, it's one of
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00:16:00,240 --> 00:16:03,160
the leading countries today.
The last point Rishi, that I
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think is really important to, to
mention is that the, the, the
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countries that we see leading
and UAE of course being one of
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them.
What I see is the multifaceted
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00:16:15,280 --> 00:16:18,160
approach that is being driven in
country for this sort of
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00:16:18,160 --> 00:16:20,120
innovation, right.
And and there's a couple of
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00:16:20,120 --> 00:16:22,400
elements I would like to call
out that are really important.
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On one side, the cross industry
adoption is super important and
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this of course is with customers
at the core.
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The second one for me is human
capital people first, the
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upscaling strategies that the
country is really driving with
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the help of of hyperscalers and
different players.
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It's second to none
partnerships.
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Of course, this continues to be
a a very important point with
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engineering center in the UAE
being established 1,000,000 UAE
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learners on AI by 2027, the
skilling initiatives, the G42 on
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Microsoft partnership, These are
some of the examples.
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Technology at the core again is
really important.
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00:17:01,320 --> 00:17:05,240
The announcement recently of
NVIDIA shipping, shipping chips
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over to to the UA is another
important point.
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And last one is this government
direction with here.
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It's an exemplary.
And then of course, companies
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like us are working backwards
from a clear vision.
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So I hope this gives you a bit
of an idea of what it feels to
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be here.
Just lastly, touching a bit on,
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on Saudi, you know, it was
publicly announced recently
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that, you know, there's going to
be a data center infrastructure
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established by the end of the
year as well.
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So there's a lot of excitement
about what that means for for
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the Kingdom.
And you know, these are these
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are, you know, great
opportunities, I think for other
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countries to also learn from
what's happening.
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You know, if you think about the
UAE 57 years ago, it was, it
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was, it was not even a country,
you know, and the speed at which
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they have moved and knowing that
today they are ahead of a lot of
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countries in this AI race, it's,
it's a great example and
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inspiration.
Yes, indeed it is.
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Carlos, we know that working on
the the challenge of climate
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change and sustainability, this
is not something that can be
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solved probably by incremental
addition.
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00:18:20,720 --> 00:18:24,080
It's a probably a system change
and we touched multiple times in
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the podcast around it.
So partnership ecosystems
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becomes critical.
Based on your experience, what
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what does good look like when
different companies collaborate
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on climate solution?
This this is a very important
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00:18:45,080 --> 00:18:50,120
point, Carmina, especially
because touching back on the
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multi faceted approach, you
know, partnerships are key here,
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not only from the deployment of
capital technology, but also on
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the use case piece.
You know, one of the things that
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at my level I face very often
is, you know, proving the value
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right.
Because at the end of the day, a
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lot of the use cases that today
contain a big opportunity for
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00:19:12,120 --> 00:19:16,440
transformational change, you
know, the way of course,
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companies are evaluating these
opportunities tends to be quite
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traditional, right?
So you have to really, you know,
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bring a different set of
stakeholders to the table and
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00:19:26,920 --> 00:19:30,000
proving the the value
proposition that these use cases
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could could provide in return,
right?
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So when it comes to this, you
know, you really need a vision
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that is driven from top.
And this is not only the
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company, but also from the
different kind of players on
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the, on the equation to your to
your point.
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And that includes obviously the
regulatory frameworks in place.
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That includes obviously the
capital allocation from the
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company, that includes division
from the leadership and that
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includes as well as strong
partners that can deliver.
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00:19:55,760 --> 00:19:59,280
You know, I think we've seen
very recently on a lot of
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statistics that were going
around about the the lack of ROI
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00:20:03,840 --> 00:20:07,240
of a lot of projects that are
not, you know, implemented
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00:20:07,240 --> 00:20:10,680
properly are not assessed
properly, data foundations not
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00:20:10,680 --> 00:20:14,000
being in place, so.
There is, there is of course,
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you know, a big need to come to
the table with the right players
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around the right problem and,
and really looking at it from a
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problem and not from a company
perspective, right.
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00:20:25,320 --> 00:20:27,320
This is, this is what I'm seeing
on the ground.
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This is where I get most
involved with with my job in
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partners, specifically on the
system integration piece.
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And you know, we spend a lot of
time more on the, you know,
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ideation phase just to make sure
that we have, you know, minimum
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viable products that are really
bringing all those stakeholders
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00:20:43,320 --> 00:20:47,360
together with confidence around,
you know, the execution and the
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00:20:47,360 --> 00:20:52,000
deployment of a, of a specific
project linked to A to a
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business problem.
Interesting, Carlos, we
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00:20:59,200 --> 00:21:04,000
obviously talked about, you
know, the the exciting things,
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things which are likely to be
needle movers in this space.
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But as AI scales and data center
load tends to, you know,
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increase and every, every now
and then we hear about a new
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announcement like you mentioned
in the case of Saudi.
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It also brings us to to this
aspect of are we trying to solve
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one problem and in the process
creating a big one, right?
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In other words, the risks
associated with this big growth.
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00:21:38,240 --> 00:21:42,920
So we hear frequently about the
high energy consumption, we hear
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00:21:42,920 --> 00:21:49,200
about the high land grab in one
sense and we also hear about the
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00:21:49,680 --> 00:21:54,160
significant consumption of of
water for cooling these data
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00:21:54,160 --> 00:21:57,640
centers, right.
Can you talk a little bit about
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00:21:57,640 --> 00:22:00,920
these aspects and what you are
seeing on the ground?
355
00:22:02,800 --> 00:22:07,640
Absolutely.
So look, this is this is a very
356
00:22:07,640 --> 00:22:11,760
important point of discussion.
If you think about the AI
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00:22:11,760 --> 00:22:15,480
economy, you know, just to put
things into perspective, by
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00:22:15,480 --> 00:22:18,480
20-30 is expected to reach 4
trillion, right?
359
00:22:18,480 --> 00:22:24,200
This is, you know, this is
slightly below what what India's
360
00:22:24,200 --> 00:22:26,640
economy is today.
So just to give you an idea on
361
00:22:26,640 --> 00:22:29,480
the magnitude, right?
So if we, if we look then on the
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00:22:29,480 --> 00:22:32,520
other side on the greenhouse gas
emissions that today data
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00:22:32,520 --> 00:22:37,080
centers are driving, you know,
it's around a 0.5% to 3.5,
364
00:22:37,080 --> 00:22:39,880
right?
But this is expected to reach 8%
365
00:22:39,880 --> 00:22:43,160
by 2030, right?
The reason for that is because
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we have more and more power
hungry data centers as we think
367
00:22:48,640 --> 00:22:52,520
about, you know, solving more
complex problems, you know, AI
368
00:22:52,520 --> 00:22:55,720
workloads, we're doing a lot of
training inferencing at the end
369
00:22:55,720 --> 00:22:58,320
of the day, driving logical
conclusion through compute.
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00:22:58,320 --> 00:23:03,240
So this is this is very energy
intensive as as you mentioned,
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both on the cooling and heating
side.
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00:23:06,400 --> 00:23:10,240
I mean another important point
into perspective just to just to
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00:23:10,240 --> 00:23:13,400
say the same data centers in
terms of percentage of global
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00:23:13,400 --> 00:23:17,160
energy demand today's 1.5 to 3%
and it's going to be 2X by
375
00:23:17,160 --> 00:23:20,200
20-30.
So it's definitely a point that
376
00:23:20,200 --> 00:23:23,600
we cannot avoid and we need to
have the debate around what what
377
00:23:23,600 --> 00:23:26,640
gives me hope is that if you
think about the architecture of
378
00:23:26,640 --> 00:23:31,280
some of these data centers and
the the advanced innovation that
379
00:23:31,280 --> 00:23:34,720
we're seeing the in the out on
chips and we're seeing on as
380
00:23:34,720 --> 00:23:39,160
well on the incorporation of
renewable energy combined with
381
00:23:39,160 --> 00:23:41,840
base loading.
Some of these data centers are
382
00:23:41,840 --> 00:23:43,960
closer and closer to power
sources.
383
00:23:44,720 --> 00:23:48,160
This for me, gives me a lot of
hope around, you know, the way
384
00:23:48,160 --> 00:23:51,720
at which data center
infrastructure is innovating by
385
00:23:51,720 --> 00:23:54,360
answering the question of being
more efficient, being more
386
00:23:54,360 --> 00:23:57,960
reliable and, and, and being
cleaner, right?
387
00:23:57,960 --> 00:24:01,160
I think this is if, if you look
at the, the kind of statements
388
00:24:01,160 --> 00:24:04,560
of, of, of most of the
hyperscalers today by 20-30
389
00:24:04,560 --> 00:24:08,920
around sustainability, it's
really a strong commitment
390
00:24:08,920 --> 00:24:12,200
towards being carbon, carbon
neutral, if not negative, right.
391
00:24:12,200 --> 00:24:16,200
So of course this brings a
different discussion around how
392
00:24:16,200 --> 00:24:19,480
that's measured and the whole
debate around how companies are
393
00:24:20,080 --> 00:24:24,400
are, you know, are proving this.
But for me, the direction of
394
00:24:24,400 --> 00:24:27,680
travel is pretty clear and the
companies that we see leading
395
00:24:27,680 --> 00:24:32,480
the, the kind of data center
landscape are, are really
396
00:24:32,480 --> 00:24:37,400
progressing fast and super,
super focused on driving that
397
00:24:37,400 --> 00:24:44,000
energy demand down.
Carlos, let's try to close the
398
00:24:44,000 --> 00:24:46,240
circle gear with a final
question.
399
00:24:46,240 --> 00:24:51,920
So we started with your journey.
Let's finish also on a question
400
00:24:51,920 --> 00:24:55,440
on the people side.
So let's look, let's look at the
401
00:24:56,960 --> 00:25:03,240
the evolving skill set for
climate tech professional as as
402
00:25:03,240 --> 00:25:06,040
we discussed in cloud AI
technologies become more
403
00:25:06,040 --> 00:25:09,760
foundational.
So what's your take on that and
404
00:25:09,960 --> 00:25:13,720
what kind of advice can you give
to young professional entering
405
00:25:13,720 --> 00:25:18,240
this space, especially those who
are coming from a transition as
406
00:25:18,240 --> 00:25:22,120
you did?
It's a very good point.
407
00:25:22,120 --> 00:25:24,000
I'll start with the last one on
the advice.
408
00:25:24,000 --> 00:25:30,000
I think 11 phrase that is is
very present on on my
409
00:25:30,000 --> 00:25:33,920
day-to-day.
It's AI will replace the people
410
00:25:33,920 --> 00:25:38,000
that, that, that don't get close
to AI, don't understand it and
411
00:25:38,000 --> 00:25:41,000
don't use it.
You know, So my, my advice is,
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you know, take advantage of the
opportunity because this is a
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really pivotal moment in, in our
society, in our world, in our
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countries, in our, in our
workplace as well.
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So it presents opportunities and
we need to see it from that lens
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because I think it really holds
a lot of the answers we're
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looking for when it comes to the
skill set, specifically for
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climate tech professionals,
we're seeing a blending of
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disciplines, if you will.
You know, traditionally you had
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environmental scientists, you
have engineers, you had policy
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experts, and separately you had
software developers and data
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scientists, right?
Increasingly we're seeing more
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and more the the world needs
needs people who who can do both
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really or at least work in
multidisciplinary teams
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effectively.
For example, a data analyst
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today might need to understand
atmospheric science and be able
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to write Python code and run AI
models.
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00:26:34,600 --> 00:26:37,440
An engineer working on renewable
energy might benefit from
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knowing cloud computing to
manage IoT sensors, data from
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solar forms as well.
So the key skill set for me is
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tech fluency and domain
expertise.
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If you are coming from the tech
side, I would say get curious
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00:26:50,360 --> 00:26:52,040
about climate and energy
systems.
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Learn the basics of power grids,
carbon accounting, agriculture,
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and if you're coming from the
environmental side, it pays to
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00:26:59,680 --> 00:27:04,160
gain data and AI skills even
through online courses or
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00:27:04,160 --> 00:27:05,960
machine learning or cloud
platforms.
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00:27:05,960 --> 00:27:09,960
There's a lot of available free
accessible material out there
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00:27:09,960 --> 00:27:14,600
that I would recommend people
have a look and with with your
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00:27:14,600 --> 00:27:16,760
support guys.
I'm happy to also share some
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00:27:16,760 --> 00:27:21,680
links that Microsoft is also
providing for for people to
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00:27:21,680 --> 00:27:25,000
understand not only the pace of
Change the Diffusion report, but
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also to to obscure themselves in
these technologies.
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00:27:30,040 --> 00:27:32,720
Yeah, that'd be good.
We will reference those in the
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00:27:32,720 --> 00:27:35,480
show notes.
And by the way, as you were
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00:27:35,480 --> 00:27:39,080
talking, I was, I mean mind
something I was reading early
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00:27:39,080 --> 00:27:43,680
this morning.
So yes, probably now we're view
448
00:27:43,680 --> 00:27:46,640
of the world, we think these are
kind of technology that widely
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00:27:46,640 --> 00:27:48,760
used.
But if I look at it from a
450
00:27:48,760 --> 00:27:53,000
helicopter view, probably 80
between 8090% of the world
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00:27:53,000 --> 00:27:57,520
population still is not close to
AI, not even having some
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00:27:57,520 --> 00:28:00,280
accounts.
So there is a sometimes we
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00:28:00,280 --> 00:28:05,840
forget that in the the many
daily activities that can be
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00:28:07,280 --> 00:28:10,600
improved or touched by these new
technologies, and today they are
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00:28:10,600 --> 00:28:15,120
very far from it.
Yeah, from we went from energy
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00:28:15,120 --> 00:28:18,520
growth to the topic of energy
access as you know a global
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00:28:18,520 --> 00:28:21,640
community and already coming in
based on what you're saying, we
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00:28:21,640 --> 00:28:26,440
are going from AI growth to AI
access, which might be the next,
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00:28:26,920 --> 00:28:29,800
next wave.
Carlos, thank you.
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00:28:29,800 --> 00:28:34,160
And, you know, this has been a
really interesting conversation.
461
00:28:35,640 --> 00:28:38,520
Thank you very much guys.
Pleasure and looking forward to
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00:28:38,520 --> 00:28:41,560
continue the discussion from
from different angles as we are
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00:28:41,560 --> 00:28:44,600
all very important players on on
this topic.
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00:28:45,520 --> 00:28:49,120
Yes, absolutely.
What I'm taking away from this
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00:28:49,120 --> 00:28:54,600
conversation, Carmine, is well
one, AI and cloud are very
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00:28:54,600 --> 00:28:58,400
powerful, especially when
they're tied to some real world
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00:28:59,040 --> 00:29:01,680
outcomes or operational
decisions and not just
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00:29:01,800 --> 00:29:06,840
reporting.
And two, I think I also I also
469
00:29:06,840 --> 00:29:10,440
heard Carlos talking about
partnerships as you, as you
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00:29:10,440 --> 00:29:14,840
mentioned this is not a problem
to be solved by one organization
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00:29:14,840 --> 00:29:19,920
or one entity and therefore you
know multi stakeholder approach
472
00:29:20,200 --> 00:29:23,120
is needed.
Any takeaways Carmina you had on
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00:29:23,120 --> 00:29:25,600
this?
And I think the ecosystem
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00:29:25,600 --> 00:29:29,240
matters.
I think Carlos describes what's
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00:29:29,240 --> 00:29:31,960
happening for example, in the
Emirates and how they reach the
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00:29:31,960 --> 00:29:36,040
kind of level of speed also
because of the right probably
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00:29:36,360 --> 00:29:41,000
ecosystem that is in place.
Indeed, that's that's another
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00:29:41,000 --> 00:29:44,840
key aspect.
So if you enjoyed this episode
479
00:29:44,880 --> 00:29:49,440
of Sustainability Forward, make
sure to subscribe to the podcast
480
00:29:49,440 --> 00:29:52,440
and share it with someone
working at the intersection of
481
00:29:52,440 --> 00:29:55,960
sustainability and technology
and join the conversation with
482
00:29:55,960 --> 00:30:00,840
us on LinkedIn or one of the
podcast platforms on which we
483
00:30:00,840 --> 00:30:04,240
are present.
Would love to hear what you're
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00:30:04,240 --> 00:30:07,640
seeing in terms of real progress
and what questions you are
485
00:30:07,720 --> 00:30:10,840
dealing with.
Again, Carlos, thank you for
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00:30:10,840 --> 00:30:13,320
joining us.
Carmine, thank you to you as
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00:30:13,320 --> 00:30:15,120
well.
Thanks for listening.
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00:30:15,120 --> 00:30:17,600
We'll see you next time on
Sustainability Forward.
Global technology and partnerships leader, Microsoft Middle East
Carlos Silva Willson, a global technology and partnerships leader at Microsoft Middle East, whose career spans General Electric/Baker Hughes in the U.S. and Europe, Amazon UK and now the Middle East’s rapidly evolving innovation landscape.
Carlos is originally from Venzuela, with an economics undergrad from SWU in the US Finance and an Executive MBA from the University of Edinburgh
Carlos brings a unique lens on how cloud and AI technologies can drive sustainability, economic opportunity, and social impact, drawing from deep international experience and a passion for empowering diverse communities
