Speaker 1: All right, it's time now for our daily Wall Street
Speaker 1: Week conversation, and the rise of AI is posing challenges
Speaker 1: to data centers. Applied Digital, which designs, develops, and operates
Speaker 1: data centers, is looking at how to adapt its infrastructure.
Speaker 1: Wes coom and See is the company's co founder, chairman,
Speaker 1: and CEO. He joins us now alongside Wall Street Week's
Speaker 1: David Weston and data centers. I mean, it's one of
Speaker 1: the hottest toppings out there, it really is.
Speaker 2: Every day we're talking about data centers somehow, some way.
Speaker 2: But we thanks so much for joining us because normally
Speaker 2: when Katie and I talk with people who at data centers,
Speaker 2: it tends to be the commercial real estate side of
Speaker 2: it and investig in it. But you actually developed these
Speaker 2: things and actually install and operate them. So give us
Speaker 2: a sense of what's the big deal with data centers
Speaker 2: now that didn't exist before the rush to AI. We've
Speaker 2: had them around for some time, right.
Speaker 3: Yeah, David, I think that the key to understand, the
Speaker 3: primary thing to understand is the difference in the compute
Speaker 3: workload that's going into data.
Speaker 4: Centers now versus what it was in the past.
Speaker 3: So in the past, you know, we were building data
Speaker 3: centers that were in population centers that we're providing ultralo
Speaker 3: latency communications so that.
Speaker 4: We could get YouTube, so that we could get Netflix.
Speaker 3: So we could get TikTok, right, so we can get
Speaker 3: all of our things that have been driven mostly by
Speaker 3: video applications.
Speaker 4: Now, as we're moving.
Speaker 3: From applications that need ultralo latency communications outside the data
Speaker 3: center to applications that need massive amounts of compute. So
Speaker 3: think of, you know, doing large math problems algorithms. This
Speaker 3: is what AI is doing inside the data center. Compute
Speaker 3: equals power, and then inside the data centers you need
Speaker 3: a lot of compute close together, so you need really
Speaker 3: high power density. And so these are kind of some
Speaker 3: weird numbers, but you know, historically data centers were let's
Speaker 3: call it seven kilowatts for an entire rack of computing,
Speaker 3: and Nvidia a one hundred server one by itself takes
Speaker 3: ten ten kilo wants. So and then you need to
Speaker 3: stack all of these together, so you have a massive
Speaker 3: amount of power consumption that needs to be close together.
Speaker 3: The latency inside the data center now versus outside, needs
Speaker 3: to be ultralove, and so you have to build a
Speaker 3: completely different style of data center, you need large amounts
Speaker 3: of power in the same location, and so that's what
Speaker 3: we're doing. We find large amounts of power, typically different
Speaker 3: locations than you would do city center.
Speaker 4: So it's no.
Speaker 3: Longer New York or Virginia or Dallas or Los Angeles.
Speaker 3: We're building in different locations where we use a lot
Speaker 3: of renewable energy that have these hundreds of megawatts, if
Speaker 3: not gigawat of power so that you can run these
Speaker 3: workloads because they're just very different style workloads versus what
Speaker 3: we're used to.
Speaker 1: Right and when it comes to that adaption process really
Speaker 1: sort of converting those existing data centers to be able
Speaker 1: to handle the AI workload that people are trying to do.
Speaker 1: I mean, how long the process is that? How long
Speaker 1: is that timeline?
Speaker 3: So I'm a big believer that you're better doing green
Speaker 3: Field in that you just build an entirely new style
Speaker 3: of data center versus trying to retrofit.
Speaker 4: Cooling is different.
Speaker 3: Again, the power density is significantly different, so there's there's
Speaker 3: a big issue.
Speaker 4: So the number one issue right now is finding power.
Speaker 4: Where's near term power? We have we have a very.
Speaker 3: Unique way of finding power, which is we find things
Speaker 3: that are called stranded power, and we typically use a
Speaker 3: lot of renewable energy that's more in the middle of
Speaker 3: the country.
Speaker 4: So number one is power, and then number two is
Speaker 4: supply chain.
Speaker 3: So this is electrical components, it's just you know, it's transformers,
Speaker 3: it's chillers, it's high voltage switch here. So the supply
Speaker 3: chain because of the demand for this has become really
Speaker 3: stretched as well.
Speaker 4: So number one is power. Number two supply chain.
Speaker 2: So wes are you building your own power? I mean
Speaker 2: you're building those wind farms or solar event or even
Speaker 2: nuclear for that matter, or are you tapping into some
Speaker 2: other part of the grid. And similarly on the supply chains,
Speaker 2: how long is the lag time on all this? It
Speaker 2: sounds like it's going to take an awful lot of
Speaker 2: time to build that power and also come up with
Speaker 2: all that supply chain.
Speaker 3: So right now we're not building the power that's something
Speaker 3: for the future for us. So there's there's a unique
Speaker 3: setup in North America with that we take advantage of
Speaker 3: what I call it is stranded power.
Speaker 4: So there is power that is generated and not used.
Speaker 3: And I know a lot of people would think that
Speaker 3: if you can generate an electron anywhere in the US,
Speaker 3: it can be used anywhere else.
Speaker 4: In the US, and that's just not the case.
Speaker 3: You need the transmission infrastructure to actually be able to
Speaker 3: do that. So we find places where, you know, for Ellendale,
Speaker 3: North Dakota, for example, there's a massive amount of wind
Speaker 3: power that feeds into a substation, and oftentimes they have
Speaker 3: to curtail the wind farms because there's not enough demand,
Speaker 3: there's not enough load to use the power that's generated.
Speaker 4: So we go to that location.
Speaker 3: And we have several of these locations where we use
Speaker 3: power that's currently not being used now to go to
Speaker 3: the other part of your question is for new power,
Speaker 3: so you can build power gen on renewables over you know,
Speaker 3: let's call it a twenty four maybe thirty six month
Speaker 3: time frame.
Speaker 4: The bigger issue is transmission.
Speaker 3: So transmission to transmit that power that typically is built
Speaker 3: somewhere in the middle of the country to end users.
Speaker 3: You know, that's more of a tend thirteen year process,
Speaker 3: and so we're kind of shortcutting that by taking these
Speaker 3: workloads directly to the point of generation.
Speaker 1: I want to talk about the competitive landscape here because
Speaker 1: you think about AI and it's just really made its
Speaker 1: way into every part of the market. It seems like
Speaker 1: every investor in every asset class is trying to figure
Speaker 1: out what's the AI narrative in their industry. When you
Speaker 1: think about your own industry and data centers right now,
Speaker 1: how fierce is the competition.
Speaker 4: So it's an interesting time for sure.
Speaker 3: So if you go back a year ago, everyone is
Speaker 3: trying to figure out on the data center side, what's
Speaker 3: happening in this market right Why is all of this demand?
Speaker 4: Why for the high power density?
Speaker 3: Now in this industry figured it out, and now it's
Speaker 3: trying to make this solution because again, getting the amount
Speaker 3: of power that's needed and operating the style of data
Speaker 3: centers is extremely difficult. And so think of on the
Speaker 3: data center side, we're the picks and shovels. This is
Speaker 3: digital infrastructure. This is the digital infrastructure was built out
Speaker 3: to run everything that we're you know, everyone's used to
Speaker 3: running on their phone or on their TV at home,
Speaker 3: and now it has to be rebuilt. It's not a replacement,
Speaker 3: by the way, this is an add on, but rebuilt
Speaker 3: for compute and AI workloads. So we're just we're at
Speaker 3: the building blocks. We're the infrastructure that runs all the
Speaker 3: AI that you know, everyone wants to do and we
Speaker 3: talked about you know, everyone knows chat GBT, but if
Speaker 3: you're doing anything in in uh, you know, in video
Speaker 3: and visual anything generative AI runs on this infrastructure and
Speaker 3: a massive amount of this infrastructure used to be built,
Speaker 3: you know, and when Jensen and in Video talks about
Speaker 3: AI factories. So so what we've done we actually designed
Speaker 3: our data center and you know, in partnership with in Video,
Speaker 3: we work with their team to build the style of
Speaker 3: data center that we're doing because it's this is the
Speaker 3: issue in the data center industry is it's just a
Speaker 3: very different style from data centers that were done in
Speaker 3: the past. But we're running all AI workloads and you
Speaker 3: know these are really split between training and inference. So
Speaker 3: the terms that are used in AI, but the entire
Speaker 3: industry is i would call it scrambling to build the
Speaker 3: amount of infrastructure that's needed to house the compute to
Speaker 3: run these applications.
Speaker 2: Well, it wasn't that long that we hadn't even heard
Speaker 2: about all these data centers. What's going to prevent absolutcence?
Speaker 4: So that's a great question.
Speaker 3: So when we build our facilities, we think about what
Speaker 3: we call future proofing. Right, so we think the power
Speaker 3: density goes higher cooling, but I think you know, the
Speaker 3: last twenty thirty years were again really driven by applications
Speaker 3: that required call comms, high speed communications, and as we
Speaker 3: go for the next twenty or thirty years, applications are
Speaker 3: really going to be driven by compute and that's what
Speaker 3: AI is, and so we're working to future proof that.
Speaker 3: And by the way, the older style data centers, those
Speaker 3: are not obsolete. We still need all of that capacity
Speaker 3: for the applications that we continue to use. This is
Speaker 3: absolutely a complete add on to what's been done in
Speaker 3: the past and so but trying to not be obsolete
Speaker 3: is making sure that your future proofing your facilities as
Speaker 3: much as possible. With power density, with cooling, we're trying
Speaker 3: to run an extremely high efficiency so that we lower
Speaker 3: our carbon footprint. You know, we build where there are
Speaker 3: renewable we mostly use renewable resources. But those are the
Speaker 3: things you try to do obviously, you know, not being
Speaker 3: obsolete in the world is one of the keys here.
Speaker 1: All right, future proofing, that's a good place to leave it.
Speaker 1: Really enjoyed this conversation our thanks to wes Coomins. He
Speaker 1: is Applied Digital co founder, chairman and CEO