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Speaker 1: dot com. That's f I R S T L I
Speaker 1: T E dot com. Okay, folks, here, by popular demand
Speaker 1: is our show where we dive into data centers from
Speaker 1: a natural resources perspective. People are always writing in asking
Speaker 1: about why don't we cover this more?
Speaker 2: We should do it. Part of the.
Speaker 1: Problems I was trying to find the perfect person to
Speaker 1: do it, because I just want someone that can look
Speaker 1: at this at the data center debate from an informed perspective,
Speaker 1: from an even perspective, someone that's not trying to drive
Speaker 1: a particular narrative or that's in the pocket of a
Speaker 1: certain set of interests, like someone to take a journalistic
Speaker 1: look at what is going on with data centers. And
Speaker 1: she's here and Davis Vaughan and was a longtime Wall
Speaker 1: Street journal Energy and Finance reporter. Then she became an
Speaker 1: investment analyst, which is basically where you like do investigative
Speaker 1: reporting on companies.
Speaker 3: That's right. I was like an investigative reporter for portfolio managers.
Speaker 1: Got it so if they wanted to make an investment,
Speaker 1: you go dig up the dirt or they.
Speaker 3: Get the best version of the truth you can find.
Speaker 2: Best version of the truth you can find.
Speaker 1: And now Anne has re entered journalism and is writing
Speaker 1: a book which likely likely will be called Gigawatt, and
Speaker 1: it is about the AI industrial boom, how it is
Speaker 1: reshaping the energy industry, the industrial landscape, and the American heartland.
Speaker 1: She currently writes this is this is where I found Anne.
Speaker 1: She currently writes a column for the Information So it's
Speaker 1: information dot Com, the Information dot Com, the Information friends
Speaker 1: send me, friends would send me your columns. And she
Speaker 1: writes a column on AI infrastructure for the Information dot Com.
Speaker 1: That's a publication based out of Silicon Valley. And what
Speaker 1: I liked about it about your writing when I would
Speaker 1: read it is it was like it was very refreshing
Speaker 1: to hear someone looking at the issue that I felt
Speaker 1: hadn't already arrived at all. The answers I was just
Speaker 1: asking questions and also taking, as we're going to get into,
Speaker 1: taking a lot of measurements, measurements of water, measurements of energy,
Speaker 1: measurements of footprint, and putting those measurements sort of into
Speaker 1: context and comparing them to things that people might understand.
Speaker 1: So rather than hearing about some kind of wattage, comparing
Speaker 1: that to other industrial applications, other things that we're all
Speaker 1: familiar with, so you start to form a relative picture.
Speaker 1: So thank you for coming on, and thank you for
Speaker 1: sharing a bunch of your reporting, especially because you're doing
Speaker 1: this before your book comes out, which is which is
Speaker 1: good of you.
Speaker 3: Yeah, well, thank you. I'm excited to be here. I'm
Speaker 3: excited about your podcast and having come from the Blue
Speaker 3: Ridge Mountains and love the outdoors. It's a big part
Speaker 3: of sorting through what's happening today.
Speaker 2: Got it right?
Speaker 1: Can you start out by this kind of a dumb
Speaker 1: question about this I want, I want to do it.
Speaker 1: Can you start out by like telling people in twenty
Speaker 1: twenty six, when they see data center in a headline
Speaker 1: in the newspaper, Okay, what exactly.
Speaker 2: Are they talking about?
Speaker 1: It's a dumb question of just seting what is a
Speaker 1: data center today.
Speaker 3: Well, I'll tell you what it is not. It is
Speaker 3: not clouds in the sky. The data center is referred
Speaker 3: to as the cloud. It's like the I think it's
Speaker 3: one of the best marketing decisions tech has ever made
Speaker 3: for itself is to call data centers a cloud. These
Speaker 3: are in the cloud. It's in the cloud, and this
Speaker 3: cloud is really an industrial complex and so it's an
Speaker 3: industrial scale facility back kind of pre AI when we
Speaker 3: just thought of it as the cloud that holds our
Speaker 3: entire digital lives, and that means everything that you know,
Speaker 3: we waste our time on, and everything that is vital
Speaker 3: to our society. So you know, how you save your pictures,
Speaker 3: how you strain your movies, how you listen to your podcasts,
Speaker 3: how you get money out of the ATM, you know
Speaker 3: how your payroll gets paid, how you know life saving
Speaker 3: machines stay on and scan your body and track data.
Speaker 3: It's all that and the you know, cloud. Data centers
Speaker 3: have been a pretty big part of the digital landscape
Speaker 3: since you know, kind of the mid two thousands. A
Speaker 3: lot of companies used to have basically their own data rooms,
Speaker 3: computer rooms, and they'd have servers that were in a closet,
Speaker 3: and eventually some of those got bigger. And of course,
Speaker 3: since you know, for decades we've had government supercomputers that
Speaker 3: were far bigger than that. But this idea of a
Speaker 3: data center that started to grow commercially came with the
Speaker 3: rise of the Internet. These these buildings, you know, would
Speaker 3: uh serve a variety of different customers. And the notion
Speaker 3: of these big tech software companies becoming cloud giants really
Speaker 3: meant that Google, Microsoft, Amazon began to build buildings with rows,
Speaker 3: hallways of chips and servers and all the equipment that
Speaker 3: keeps them at this goldilocks you know, environment and temperature
Speaker 3: and fiber would go in and out and and data
Speaker 3: would you know, Uh, it was very important to have
Speaker 3: data have what is called low latency, so they tended
Speaker 3: to be in urban centers and the low latency low
Speaker 3: latency means quick like you know, you know when you
Speaker 3: when you remember the days when you would try to
Speaker 3: watch a video and it would say buffering, buffering, Yeah,
Speaker 3: that's low latency. And so you need instantaneous data for
Speaker 3: something life saving, like you know, an emergency response system.
Speaker 3: Traders want instantaneous data. We get upset if we can't
Speaker 3: you know, if a text doesn't come through right away.
Speaker 3: There are certain businesses that really are mission critical and
Speaker 3: that need to be near a city. So a lot
Speaker 3: of data centers got built in smaller fashion before the
Speaker 3: AI age, in especially northern Virginia near Washington, d C.
Speaker 3: And then some big cities like Dallas, Chicago, Phoenix out
Speaker 3: on you know, the West coast and both the Silicon
Speaker 3: Valley area and then up in the Pacific Northwest near Seattle.
Speaker 1: Was it was it really that proximity in those days,
Speaker 1: which is just like yesterday. Yeah, the proximity to you
Speaker 1: to user groups was important, like physical proximity to big
Speaker 1: populations of people.
Speaker 3: Yes, because the there's a limit to how quickly data,
Speaker 3: you know, will travel on fiber. And we're talking, you know,
Speaker 3: just nanoseconds. We're not talking, you know, we're we're really
Speaker 3: unwilling to wait for a few seconds for something to
Speaker 3: come through. So they were built under that, you know
Speaker 3: premise that giant amounts of fiber got built in the
Speaker 3: dot com era, there was a whole bunch of it left,
Speaker 3: you know, didn't get used, and then we kind of
Speaker 3: built into that in the two thousands and in the
Speaker 3: twenty tents, and when COVID happened, people started using online
Speaker 3: digital resources like crazy, and even more continued to be built.
Speaker 3: And so then when chat, GPT and AI as a
Speaker 3: new paradigm kind of really came on the scene around
Speaker 3: twenty twenty two, there began to be the conception of
Speaker 3: a whole nother kind of scale of data center. So
Speaker 3: AI data centers are bigger, more power hungry, more resource hungry,
Speaker 3: really because AI models operate on a scaling phenomenon, and
Speaker 3: so the idea is that it's not just a building
Speaker 3: with a whole bunch of different companies siloed computing taking place,
Speaker 3: but instead it is one big campus where all the
Speaker 3: chips are connected to all the other chips and they're
Speaker 3: all talking to each other, and it's like one big brain.
Speaker 3: And the more powerful models that have been trained have
Speaker 3: operated on this concept, and so we're building even bigger
Speaker 3: ones now and that they operate all together big that
Speaker 3: means bigger footprint for these data centers, more industrial equipment
Speaker 3: to bring them the electricity and to cool them. And
Speaker 3: that's why they are basically factories.
Speaker 1: And all the time that we've been like, well, let
Speaker 1: me reapproach that maybe you can correct me on the timeline,
Speaker 1: but at what point was it a year ago?
Speaker 2: Was it eighteen months ago?
Speaker 1: At what point was it that all of a sudden
Speaker 1: this debate about data centers and the environmental impact of
Speaker 1: data centers exploded. You probably have a different view of
Speaker 1: it because you follow this and report on it, But
Speaker 1: try to, like in your mind, think of think of
Speaker 1: just a normal, concerned citizen who reads a few newspapers
Speaker 1: in the morning. Like, help me, remember when was it
Speaker 1: at all sudden? It was just like the issue.
Speaker 3: It was that issue around the end of twenty twenty
Speaker 3: five and early twenty twenty six.
Speaker 1: Okay, so it was recent, yeah, Because what struck me
Speaker 1: is where was the argument about data centers prior to that?
Speaker 2: Was there one?
Speaker 3: Yes, there was, And if you go back you will
Speaker 3: find some pushback from a few years ago. I think
Speaker 3: that the scale just had not hit people. And so
Speaker 3: this AI boom has gone through several stages, and you know,
Speaker 3: at first it was just like, what is this AI thing?
Speaker 3: What is chat GPT? It's going to change everything? And
Speaker 3: then there was this stage when I was actually still
Speaker 3: working as an investment analyst where everyone was saying how
Speaker 3: much power are we going to need and where is
Speaker 3: it going to go? And you know, the financial and
Speaker 3: energy and tech types were mobilizing and everyone was saying,
Speaker 3: can we really use this much power? Then there was,
Speaker 3: like maybe in the fall of last year, an absolute
Speaker 3: panic over whether AI was a bubble and whether we're
Speaker 3: spending too much because at that stage everyone was really
Speaker 3: focused on how much the tech guys were going to
Speaker 3: be spending and you know, every quarter and how they
Speaker 3: had gone from just being so cash rich to spending
Speaker 3: you know, a great deal of their cash flow. And
Speaker 3: so all during that time, the the the you know,
Speaker 3: wildcatters that were trying to put AI together and find
Speaker 3: places to put it were going to communities and starting
Speaker 3: to make plans for data centers and individual communities were
Speaker 3: having meetings and saying, what do we think about this?
Speaker 3: But the populace in general is not super engaged on
Speaker 3: you know, their local community level. There's we've kind of
Speaker 3: turned polarized and less local news to consume anyway, and
Speaker 3: the digital age sadly, and and you know, people have,
Speaker 3: you know, whatever they're concerned about on the national level,
Speaker 3: and all of a sudden, these campuses started to get
Speaker 3: constructed and people started to say, wait a minute, like,
Speaker 3: I didn't know this was happening, and well, you know,
Speaker 3: some of some of this may have been done just
Speaker 3: like any kind of industrial real estate project might have
Speaker 3: been in the past, where people go to the local
Speaker 3: zoning authorities they say, Hey, we're with this company, we
Speaker 3: want to buy this land. Can we put this application in?
Speaker 3: You know, normally the public is not watching every move
Speaker 3: on that front, but all of a sudden, there was
Speaker 3: this collective realization that there have been a kind of
Speaker 3: rush out into the middle of the country because these
Speaker 3: data centers were on a totally different scale than the
Speaker 3: cloud data centers, and we're going to need to go
Speaker 3: places where there was enough land or where there was
Speaker 3: enough power, where there was some headroom in you know,
Speaker 3: whether it was water, the grid, and.
Speaker 2: That is.
Speaker 3: It kind of started to reach a fever pitch. I
Speaker 3: would say, I noticed it on a trip to Wisconsin
Speaker 3: in early February, where the backlash had grown just exponentially.
Speaker 1: Yeah, I want to do a thing where you give
Speaker 1: me you can pick, or you can do neither, or
Speaker 1: we can play a game to figure out who does it. Like,
Speaker 1: I want to do the positives. Just before we get
Speaker 1: into some of the details. I want to do the
Speaker 1: positives and negatives. You can take both of them. I
Speaker 1: can take one, you can do both. You can sell
Speaker 1: me on the hysterical view. I don't want to load
Speaker 1: it too much. You can sell me on like why
Speaker 1: this is upsetting the people, and you can sell me
Speaker 1: on why it's exciting to some right, or we can.
Speaker 2: Split the job up to you.
Speaker 3: Well, okay, So the worries are that data centers are
Speaker 3: going to destroy our environment, They're going to you know,
Speaker 3: destroy our health, That they'll drain Lake Michigan, they'll you know,
Speaker 3: raise the temperature above the buildings and into our neighborhoods
Speaker 3: so poison the water supply. They'll spike our power bills,
Speaker 3: they'll only take subsidies and not give anything back to
Speaker 3: you know, local communities, and and that it's all happening
Speaker 3: in secret. So I think that's part of the that's the.
Speaker 1: That's the vibe I get. That's the vibe I get
Speaker 1: of the panic.
Speaker 3: Yeah, yeah, yeah. And and not to even mention that
Speaker 3: it's existential to humanity and it could destroy humanity. Not
Speaker 3: a small concern either.
Speaker 1: Yeah, because that's a certain thing, is it'd be in
Speaker 1: looking at water consumption, energy consumption footprint, there's also just
Speaker 1: it's fueled by a general apprehension.
Speaker 2: And it'd be like, so that it can take my job.
Speaker 1: Yeah, right, I got to give up all that, I
Speaker 1: got to give up clean water, I got to give
Speaker 1: up all this stuff. I got to accept this I
Speaker 1: sore into my community so that then this can take
Speaker 1: my friend's.
Speaker 3: Jobs, that's right, and my future, my children's future jobs.
Speaker 2: Yeah.
Speaker 3: And I don't think that the tech industry has done
Speaker 3: itself any favors by you know, carrying out a narrative
Speaker 3: that is you know, potentially quite exaggerated in that view,
Speaker 3: but you know, candidly, we all have a lot to
Speaker 3: learn as time unfolds. So so yeah, I mean you
Speaker 3: ask like, how do you separate or or figure out
Speaker 3: what is truth and what is what is crazy? And
Speaker 3: what what is rational to worry about? And I guess
Speaker 3: I I would start with what what is rational to
Speaker 3: worry about? It is very rational to worry about, you know,
Speaker 3: to fear change and uncertainty. And we are facing an incredible,
Speaker 3: uh turning point. We're in the early days of the
Speaker 3: Ai Revolution, and there's incredible fear and uncertainty, and that's rational.
Speaker 3: And I think it's rational to love your community and
Speaker 3: to love the character of your community. And you know,
Speaker 3: especially if you've you know, uh, even if there's been
Speaker 3: some economic decline, you've kind of made peace with that,
Speaker 3: or you you kind of love where you're from and
Speaker 3: you kind of enjoy a little bit of the piece
Speaker 3: that has come with some of the economic decline in
Speaker 3: your region and the natural beauty instead making you know,
Speaker 3: like coming to grips with it looking completely different. Is
Speaker 3: I think that's very rational. Like some of the scale
Speaker 3: of what I'm talking about in rural communities we are
Speaker 3: talking about in the end, a campus that I sometimes
Speaker 3: think of it as like, you know, five pentagons, like
Speaker 3: landing in the field across from your house. These are
Speaker 3: huge campuses, some of them. Yeah, like uh, well, uh,
Speaker 3: it's many more than Walmart super campuses. Like a Meta
Speaker 3: campus in Louisiana is five miles long and one mile wide,
Speaker 3: are you kidding? And so I've driven the perimeters of
Speaker 3: concrete not a concrete it's many buildings. So it's many
Speaker 3: buildings with land in between. And when they're finished, they
Speaker 3: will have some grass and they will have some parking lots,
Speaker 3: and they will.
Speaker 1: The footprint of that thing is five miles by a mile. Yeah,
Speaker 1: that particularly it's the footprint. It's it's the footprint of
Speaker 1: a large municipal airport.
Speaker 3: Yes, it's not dissimilar from an airport. And so it
Speaker 3: is rational to say, wait, this scale is truly it
Speaker 3: feels nuts to me, and and and and you know
Speaker 3: the truth is that the landscape has changed through many
Speaker 3: years of other industrial revolutions. Railroads have you know, crisscrossed
Speaker 3: and and you know, maybe maybe some thought at the
Speaker 3: time scarred the landscape and we got used to those
Speaker 3: we have area.
Speaker 1: Someone n like today was proposedly the railroad infrastructure as
Speaker 1: a new concept.
Speaker 2: You'd never get it done.
Speaker 3: You'd never get it on today.
Speaker 2: Like, hey, I got an idea I never run.
Speaker 1: You know, we're going to run these continuous lines all
Speaker 1: across the country and eminent domain everything.
Speaker 2: You'd never get it through.
Speaker 3: I'm going to put poles up with wires all over
Speaker 3: every single street.
Speaker 2: Polled wires and people would be like, no, what you're
Speaker 2: not doing that?
Speaker 3: Yeah, So I mean I think it's it's it's rational
Speaker 3: to you know, uh, and it's it's it's understandable too
Speaker 3: that people see technology and these they see data centers
Speaker 3: as see embodiment of how tech has changed our lives
Speaker 3: and you know, for the worse perhaps, and they sort
Speaker 3: of see it for the worse, and of course tech
Speaker 3: has also changed our lives for the better. And so
Speaker 3: I guess I would say what is not rational is
Speaker 3: to not look at and do this with some common
Speaker 3: sense and put context around it. So you know, one
Speaker 3: piece of context, right, like, well, look we now have
Speaker 3: airports that are these giant pieces of land that we
Speaker 3: all depend on. The truth is we do all depend
Speaker 3: on day centers every single day. Our lives are you know,
Speaker 3: as dependent on energy as they are in digital and
Speaker 3: now AI and energy are completely intertwined and they pull
Speaker 3: in all kinds of other resources and we're grappling with
Speaker 3: that and in real time in a hurry. The tech
Speaker 3: industry is in a big hurry. And that's another part
Speaker 3: of people's unease is how fast fast.
Speaker 1: Let's talk about some of the specifics, some of the
Speaker 1: specific impacts. Is we start with water, Okay, what amount
Speaker 1: of water? What amount of water are we talking about?
Speaker 1: I mean, let's look at it. You know, there's another
Speaker 1: question I got prior to that, because it just kind
Speaker 1: of sets this whole thing up. When we talk about
Speaker 1: what's going to happen, what is a comfortable timeline ten years?
Speaker 1: We have no idea, right so there's sort of like
Speaker 1: what's proposed right now, what's in process right now? So
Speaker 1: if I say to you how much water our data
Speaker 1: center is going to use? At what date are we
Speaker 1: looking at?
Speaker 2: Like?
Speaker 1: What date is it fair to look at? Is it
Speaker 1: like right now? Is it two years from now?
Speaker 3: People use twenty thirty as the.
Speaker 1: Guidepost, Okay, so when we're talking about it's just for
Speaker 1: people to reminder here we're in twenty twenty six. When
Speaker 1: we're talking about how much water, how much footprint, we're
Speaker 1: sort of looking at reasonable projections about four years from now.
Speaker 2: Is that cool? Okay? So when I read articles.
Speaker 1: Talking about data centers and resistance to data centers and things,
Speaker 1: one of the big issues that comes up is where
Speaker 1: is all this water coming from? And that winds up
Speaker 1: being like relevant. It's relevant to all Americans because we
Speaker 1: all rely on abundant clean water. It's relevant to agriculture
Speaker 1: obviously because food, and then in a sort of niche way,
Speaker 1: it's very relevant to like me as a fisherman and
Speaker 1: an outdoorsman, you know, like like the fact that our country,
Speaker 1: as wealthy as it is and as populous as it is,
Speaker 1: still has this like abundance of clean water full of
Speaker 1: fish relative to other places around the world. That's like
Speaker 1: a tremendous value. So when I hear something that might
Speaker 1: threaten that, I get anxious. You know, how do we
Speaker 1: look at the water issue here?
Speaker 3: Yeah, so I think so I just a couple of
Speaker 3: caveats that I'm not a water scientist, and and I'm
Speaker 3: also in the process as I work on this book
Speaker 3: of interrogating this topic from every angle that I can,
Speaker 3: and you know, striving to figure out the best version
Speaker 3: of the truth so that you know, we can all
Speaker 3: talk apples to apples. And so I've attempted recently did
Speaker 3: a column on water for the Information and have attempted
Speaker 3: to do that for the book as well, sort of
Speaker 3: saying what how much water, you know, does this industry
Speaker 3: really consume? And has that changed? So it has changed.
Speaker 3: Actually the data centers are getting bigger, but they're getting
Speaker 3: more water efficient. So let's put kind of water broadly
Speaker 3: speaking in perspective, so that this is this is kind
Speaker 3: of a rough exercise. And again, like you know, there
Speaker 3: are many resources that folks who have like helped me
Speaker 3: think through this are drawing from. Okay, but so we
Speaker 3: don't get alarmed by contextless numbers. You hear something like
Speaker 3: billions of gallons of water being used a year, and
Speaker 3: that sounds astonishingly large, sure, but in fact, big industries,
Speaker 3: including agriculture, are using trillions of gallons a year.
Speaker 2: So the other thing you hear, and is kind of glib,
Speaker 2: is you'll do it.
Speaker 1: You'll do a search, right, you do like a thing
Speaker 1: on chat GPT, and then people be like, well, there
Speaker 1: goes a gallon of water. Yeah, yeah, you hear it,
Speaker 1: but you don't really no one knows what I should say,
Speaker 1: No one.
Speaker 2: Most people don't really know what they're saying.
Speaker 3: Yeah, okay, so let's start big and we kind of
Speaker 3: telescope you know, out and then go go in a
Speaker 3: little bit. So there's like, you know, if you maybe
Speaker 3: you can keep a number in your head of like
Speaker 3: fresh water consumption in the US and the like thirty
Speaker 3: trillion gallons a year range, and.
Speaker 2: Well that's what that's what we're using.
Speaker 3: Yeah, and you know, and and thirty gallons thirty trillion
Speaker 3: gallons a year, and single crops in the United States
Speaker 3: use as much as three trillion gallons a year. Okay,
Speaker 3: so corn or alfalfa like for for livestock, and a
Speaker 3: third of the corn, uh, you know harvest is going
Speaker 3: to ethanol. So so this these are just single crops,
Speaker 3: and so agriculture. Irrigation for agriculture does consume something like
Speaker 3: you know, the like seventy percent of our fresh water,
Speaker 3: So we're already using a lot of our fresh water
Speaker 3: for irrigated crops. And so corn like three trillion gallons
Speaker 3: a year California almonds one point two to one point
Speaker 3: eight trillion gallons.
Speaker 1: Seriously, seriously see corned alfalfa.
Speaker 2: I get it because like.
Speaker 3: You're not an almond lover.
Speaker 2: Well no, no almond now man.
Speaker 1: But you know, the country's not going to without alfalfa
Speaker 1: and be able to feed cattle, right, It's not going
Speaker 1: to happen.
Speaker 3: Yeah, we might get along with that on.
Speaker 1: For ethanol and livestock feed and other things. It's not
Speaker 1: going to happen. But it's like, I don't mean to
Speaker 1: hack on the almond people like I like almond joy
Speaker 1: as much as the next gap, and I'm just saying,
Speaker 1: like the almond thing seems uh, I don't know, I
Speaker 1: don't want to hack.
Speaker 3: You know, we don't need to pick on them because
Speaker 3: there's there's plenty of examples of the dairy farming. Dairy
Speaker 3: farming is enormously water consumpted, and about an estimated like
Speaker 3: ninety three percent of the water footprint of dairy farming
Speaker 3: is actually just to feed cows or you know, basic.
Speaker 1: Blow dairy's got to blow almonds out of the water
Speaker 1: as like a not quite a pun.
Speaker 3: But yeah, I you know, I think it's it's it's
Speaker 3: way up there. I guess it's like the statistic that
Speaker 3: I came to armed with is that a gallon of milk,
Speaker 3: and this is from the US airy industry, like Sustainability reports,
Speaker 3: a gallon of milk takes one hundred and forty four
Speaker 3: gallons of water to produce, really, and a pound of
Speaker 3: cheese takes one hundred and sixty four gallons of water.
Speaker 1: When you take a sip, like when I put a
Speaker 1: little half and half in my coffee, no one goes like, well,
Speaker 1: there goes three gallons of water.
Speaker 3: I think that we have normalized We love our farms.
Speaker 3: We love our food, well farm we you know, we
Speaker 3: love field blowing in the breeze and we having.
Speaker 2: A farm field across the road. Yes, that's a selling point.
Speaker 3: You know. And a lot of people will say and
Speaker 3: I had a farmer say this to me who sold
Speaker 3: a very large chunk of lant to Meta. You know,
Speaker 3: I hear over and over nobody can eat a data center.
Speaker 3: He's like, well, these are you know, his words, not mine.
Speaker 3: But he's like, don't tell that to me when you
Speaker 3: know we have seven million acres of sorry, when we're
Speaker 3: using you know, yeah, seven million acres in just in
Speaker 3: Illinois or thirty thirty million acres of corn that is
Speaker 3: harvested is going to ethanol. So we're not eating ethanol.
Speaker 3: We shouldn't be eating ethanol.
Speaker 2: Yeah, that's a miss.
Speaker 1: Like on the land used front, I think that that's
Speaker 1: a little bit of a I don't know how wide
Speaker 1: spread it is, but I would say with people not
Speaker 1: adjacent to agriculture, I would say, when you're driving when
Speaker 1: you're in the in the Upper Midwest and you're driving
Speaker 1: through corn monocultures, I think that I think that most people,
Speaker 1: most urban people feel that they are in a food
Speaker 1: production landscape. Yeah, and they don't view it that they
Speaker 1: are in a energy they are in a fuel and
Speaker 1: energy production landscape. And it'd be like, it's like, I
Speaker 1: don't even want to equate it to an oil field
Speaker 1: because it's it's soil. It could be repurposed for other things. Right,
Speaker 1: it's not developed, it's not under concrete and use. You
Speaker 1: could grow different crops there next year if you wanted to.
Speaker 2: But it's it's energy. Yeah, you're looking at energy production.
Speaker 3: So that's some of the agg let's take like lawn
Speaker 3: irrigation and golf courses. All lawn irrigation in the United
Speaker 3: States also equates to about three trillion a year, and
Speaker 3: golf courses use about a half a trillion gallons of
Speaker 3: water a year. You get into individuals.
Speaker 1: That the golf course, that you take all the water
Speaker 1: used by Americans to water their grass or gardens in
Speaker 1: that and that that's three trillion, and that golf courses
Speaker 1: are sucking up a half trillion.
Speaker 3: Yeah, So like golf courses, there's a difference between consumptive
Speaker 3: water use and water that is used return to its sources.
Speaker 1: We can talk about that just I want to tell listeners. Yeah,
Speaker 1: We'll get into this because, of course, the amount of
Speaker 1: water on Earth is a constant, so we need to
Speaker 1: talk about when you say that you're using water, what
Speaker 1: does it mean. Yeah, Like, just to give one example,
Speaker 1: at our fish shack, we pull water out of a creek.
Speaker 1: It runs through our fish shack, but goes back into
Speaker 1: the creek. Yes, doe, I mean, so it's like we're
Speaker 1: just detaining it for a minute and putting it right
Speaker 1: back where it came from at the same temperature in
Speaker 1: like measured in quartz. But I'm saying it's like, so
Speaker 1: you'd be like, are we using water? Like when I
Speaker 1: turn the hose on, am I using water? Because that
Speaker 1: water's flowing right back into where I got it from.
Speaker 1: So we'll get into that a little bit, like like
Speaker 1: when the data centers using water, how are they using it?
Speaker 1: And why can't they put it back where they found it?
Speaker 2: We'll talk about this.
Speaker 3: Well, your fish shack, let's now zoom into a much
Speaker 3: higher industrial scale, which would be a power plant is
Speaker 3: doing something similar to your fish shack. It is withdrawing
Speaker 3: a pretty large amount of water from water sources like
Speaker 3: lakes and rivers, but approximately ninety five percent of the
Speaker 3: water gets returned to its source.
Speaker 1: Good now way still gets counted as usage though.
Speaker 3: It's counted as usage but not. But if you really
Speaker 3: think of consumption, it's not all like you know, maybe
Speaker 3: water is considered consumed and this is where you want
Speaker 3: to go to an expert. But like generally speaking, when
Speaker 3: it evaporates and it doesn't, it's not directly Okay, yeah.
Speaker 1: That's the number. I'm interested in where you've moved it.
Speaker 1: I don't want to get two in the weeds on this.
Speaker 1: But like, once you evaporate it and put into cloud cover,
Speaker 1: you're moving it to different drainages, you're moving it to
Speaker 1: different basins, and you're like you're redistributing water rather than
Speaker 1: you're keeping it in a closed circuit system. That's right,
Speaker 1: but it was keep hitting me with how much the
Speaker 1: relative unwaters.
Speaker 3: Let's look at the electric sector though, but it's still
Speaker 3: it uses around forty five trillion gallons annually the power
Speaker 3: generating electricity too cool thermal power, So thermal power would
Speaker 3: be like coal plants, natural gas plants and nuclear plants
Speaker 3: so as a posed to like solar or you know,
Speaker 3: hydroelectric and the but you know, only about five percent
Speaker 3: of that is fully consumed and it's returned to its source,
Speaker 3: and there are regulations around this, but you know, I
Speaker 3: none of us like to think of warm water going
Speaker 3: into a pristine ecosystem. So there's regulation around this, and
Speaker 3: there's ways that it has dealt with.
Speaker 1: From from a fishing perspective, yeah, which is how I
Speaker 1: look at many things in life. A hot water discharge
Speaker 1: is a blessing and a curse, you know, because like
Speaker 1: a hot water discharge could be the best fishing place
Speaker 1: in the world, it can also be what destroys a
Speaker 1: body of water, Yeah, by changing the water temperature. So
Speaker 1: it's like it's a it's a funny you know, like
Speaker 1: many anglers, especially in the Great Lakes area, you have
Speaker 1: like a complicated relationship with hot water discharges.
Speaker 2: You know.
Speaker 1: Yeah, fisher like the fish are just there, right, and
Speaker 1: you're like it's kind of like you're cheating. They're there
Speaker 1: for the hot water discharge. Then at the time other
Speaker 1: times year it makes the water too dam warm, you.
Speaker 3: Know, right, Yeah, and it changes to fishing conditions and
Speaker 3: you can't fish at all.
Speaker 1: Yeah, So people have a there's like in my world,
Speaker 1: there's a there's like a complicated relationship with those things. Yeah,
Speaker 1: but yeah, they're putting it back, they're putting it back
Speaker 1: where they got it from.
Speaker 2: But it's just a lot hotter.
Speaker 3: Yeah. Yeah. So the electric sector that this is where
Speaker 3: you really want to focus when you're thinking about data centers.
Speaker 3: So members of the data center industry have made significant
Speaker 3: strides in changing how they do water out of necessity.
Speaker 3: So AI runs hotter than traditional computing. It takes a
Speaker 3: lot more electricity, and it puts it into much denser
Speaker 3: racks of like you know, tightly tightly networked chips and
Speaker 3: servers and memory and all this stuff. And so there
Speaker 3: they've now learned to do what's called closed loop cooling.
Speaker 3: Literally they'll run a cooling liquid which you know can
Speaker 3: include water and glycol in, you know, over chips and
Speaker 3: and in these tiny tubes that get into bigger tubes
Speaker 3: and you know, eventually also need to go up to
Speaker 3: a or or out to a big set of equipment
Speaker 3: that cools that water and then it sends it all
Speaker 3: back to do it all over again. When today's really
Speaker 3: advanced AI data centers get built, they get filled up
Speaker 3: with a pretty small amount of water, like for example,
Speaker 3: a Microsoft facility in Wisconsin was filled. I think it's
Speaker 3: a handful of swimming pools worth of water. It's about
Speaker 3: what a car wash would use in a year, not
Speaker 3: not too much when you people have forgotten how much
Speaker 3: water other industrial things, you know, factories, steel mill you know,
Speaker 3: like any any industrial plant uses water. Right, so chip
Speaker 3: foundries use a giant amount of water. So on a
Speaker 3: relative basis, the data center guys will sometimes say we're
Speaker 3: hardly using any water, but there is a trade off
Speaker 3: that they you know, I think would be smart to
Speaker 3: just upfront acknowledge because the closed loop cooling is using
Speaker 3: a lot of new advanced equipment and existing technologies that
Speaker 3: we've known about that basically are very energy intensive, and
Speaker 3: so that means they draw more power to do that,
Speaker 3: and that means that if they are using the output
Speaker 3: of a thermal power plant that is up the road,
Speaker 3: that thermal power plant is using a lot of water
Speaker 3: to you know, cool as facilities and make the power.
Speaker 3: And so we're kind of trading one problem for another day.
Speaker 1: Yeah, they're dropping off on water used to pick but
Speaker 1: then they need energy to cool the water.
Speaker 3: Yeah then they Yeah, then they need energy and that
Speaker 3: needs to be cool to the power plant. So the
Speaker 3: much bigger offenders in the water for the digital economy
Speaker 3: are electric power plants. And actually chip foundries are extremely
Speaker 3: water intensive and they use ultra pure water and it
Speaker 3: takes you know, a large, you know, kind of extra
Speaker 3: amount of water to get it fully pure and to
Speaker 3: do that, and and some of it is consumptive. And
Speaker 3: so there are some water treatment and you know, technology
Speaker 3: companies that have done some really interesting studies. You know,
Speaker 3: Xylum's done one that I wrote about in my last column,
Speaker 3: just showing Uh, it's if you kind of if you
Speaker 3: can visualize like these two layers of giant mountains of
Speaker 3: water use, and they are semiconductor plants and power plants,
Speaker 3: and there's kind of a ribbon on the top which
Speaker 3: is data centers.
Speaker 1: So with all those, hit a couple of those again,
Speaker 1: like hit me with with the water use of agriculture. Yeah,
Speaker 1: it's like the total water use. Hit me with the
Speaker 1: couple and then tell me in twenty thirty where we're
Speaker 1: looking at cross.
Speaker 3: Single crops, big big crops in the US might be
Speaker 3: three trillion gallons a year.
Speaker 2: Of water.
Speaker 3: Direct water use of data centers has been estimated at
Speaker 3: roughly eighteen billion gallons. So remember a billion is one
Speaker 3: thousand less order of magnitude one thousand less than a trillion,
Speaker 3: So three trillion for a single crop, US data center
Speaker 3: use eighteen billion. We're talking way way smaller.
Speaker 1: That's project projection.
Speaker 3: Like a quarter of a percent, And so it's just
Speaker 3: important to kind of keep some of that in perspective
Speaker 3: because if even the data center footprint of on site
Speaker 3: plus the amount consumed in the electric sector, you take
Speaker 3: how much power they're using, you have to haircut it
Speaker 3: because not all power is thermal power. And you also
Speaker 3: have to haircut it because it's not just as we said,
Speaker 3: all consumed. And it's still like we're talking one percent
Speaker 3: of fresh one even maybe by twenty thirty, the data
Speaker 3: centers might be using in a, you know, a more
Speaker 3: consumptive fashion.
Speaker 1: Is it safe to say that it's the part of
Speaker 1: the concerns. It's like it's it's it's added mortality on water.
Speaker 2: Meaning we're used to we're.
Speaker 1: Comfortable with how much water we're using for energy, how
Speaker 1: much water we're using for agriculture, and we've just become
Speaker 1: numb to it.
Speaker 2: We we just look.
Speaker 1: At it like it's just like how we're to it,
Speaker 1: and so when someone comes and says, I'm going to
Speaker 1: draw yeah, blank billion gallons, it is an added stressor
Speaker 1: for sure. But in the context of the and I
Speaker 1: know you're not you know, and you know, I know
Speaker 1: you're not looking at this from from an apologist perspective,
Speaker 1: But it's just very interesting to hear from a relative
Speaker 1: sense of other industries what we're talking about, because the
Speaker 1: impression one would get, the impression one would get is
Speaker 1: that we're talking about a level of water, like an
Speaker 1: unprecedented level of water use.
Speaker 3: Yeah, well, then we should also talk about why people
Speaker 3: are alarmed. And well, first I'll tell you something that's
Speaker 3: really depressing, which is about it depends on the estimate,
Speaker 3: but eighteen to thirty percent of municipal water system water
Speaker 3: is getting wasted completely because of leaks, leaky pipes, old infrastructure.
Speaker 3: Water utilities are typically like owned by municipalities, They are underfunded,
Speaker 3: and they didn't have great technology. Today it exists to
Speaker 3: kind of monitor and figure out where leaks are. And
Speaker 3: so even as we use more water for industrial purposes,
Speaker 3: for data centers, we're leaving so much of it, you know,
Speaker 3: like where we can't access it, Like it's just fallen
Speaker 3: out of our water system. So that's tough. The other
Speaker 3: problem is that a lot of digital infrastructure is going
Speaker 3: to water stressed places and so in individuals, it's a
Speaker 3: bigger incremental stress on the system. It's a very big
Speaker 3: incremental What is.
Speaker 1: What is the rational? Well maybe we should do that one.
Speaker 1: Next is the physical footprint? Well, go on on water,
Speaker 1: We'll talk about physical footprint next.
Speaker 3: Yeah. So, well, you know, the you've seen a lot
Speaker 3: of chip plants locate in the Southwest, in the Phoenix area.
Speaker 3: A lot of data centers are there too. And when
Speaker 3: when I have been traveling the country looking at the
Speaker 3: AI boom and where the next generation of digital infrastructure
Speaker 3: is getting built, it's getting built in the middle of
Speaker 3: the country effectively, so and some of them are in
Speaker 3: water stressed areas. So we kind of think of the
Speaker 3: American West and the sort of more desert landscape as
Speaker 3: water stress. The Colorado River basin, for sure, is a
Speaker 3: is an area of significant water stress. The Ogalala Water
Speaker 3: Aquifer which goes from South Dakota down.
Speaker 2: To Texas basically the American Great Plans.
Speaker 3: And you know, in both cases there have been alarms
Speaker 3: sounded about water before the AI boom in these regions.
Speaker 3: But they're they're for a variety of different reasons, good
Speaker 3: places to build AI data center campuses.
Speaker 1: At this point, like if if if I carry in
Speaker 1: my mind from just being a concerned citizen, if I
Speaker 1: carry in my mind an idea that water consumption is
Speaker 1: a major implication of AI infrastructure. And then someone tells
Speaker 1: me that that data centers, that people are building data
Speaker 1: centers and they're they're they're tending toward the Colorado basin,
Speaker 1: the Galawa aquifer, So like the American planes the Southwest,
Speaker 1: and I have the water thing in my mind. I'm like,
Speaker 1: that seems ridiculous.
Speaker 2: But is it?
Speaker 1: Are are they going? Are data centers now going where
Speaker 1: it makes sense to put a data center or are
Speaker 1: they going where they're welcome? Like like when they look
Speaker 1: at when they look at like where should we try?
Speaker 2: Right?
Speaker 1: Is it they won't put up a fuss, Let's go there,
Speaker 1: water be damned or are they like no, for for
Speaker 1: all these reasons of infrastructure, this is the place to be.
Speaker 3: Yeah, So water is a factor and where they go,
Speaker 3: and there are data centers being placed in areas with
Speaker 3: plentiful water too.
Speaker 2: I just got they don't want it either them.
Speaker 3: But well, you know, water is less, it's less of
Speaker 3: an of a footprint than the energy that these facilities.
Speaker 3: But they're going to different spots. So for example, you know,
Speaker 3: they're going to the Mississippi River delta and sorry, really
Speaker 3: in Mississippi and Louisiana.
Speaker 2: Okay, why let's take that one for instance.
Speaker 3: Okay, so water availability is a draw to go there, right,
Speaker 3: And I literally was driving a week and a half
Speaker 3: ago through Louisiana past you know Bayous where the tree
Speaker 3: trunks are basically swimming in water. Right. There's water everywhere,
Speaker 3: and and it's you know, if a farmer said to
Speaker 3: me that you know, this water, this aquifer will not
Speaker 3: you know, it does not have a drain drain the
Speaker 3: you know, the water supply risk. Now, that does not
Speaker 3: mean that water is not precious everywhere, right, And so
Speaker 3: Texas is getting an enormous number of these new data centers,
Speaker 3: and water scarcity is a big issue in Texas. And
Speaker 3: you know, in like there's a new study out of
Speaker 3: the University of Texas that looks at both the direct
Speaker 3: water use, which as I've said, is getting better data centers,
Speaker 3: and the indirect water use from power, which is getting
Speaker 3: worse in some ways. It depends on what what we
Speaker 3: end up putting in as the power source. Right, if
Speaker 3: we don't build coal plants, you know, that's a whole
Speaker 3: lot better for the water supply. But the Texas could
Speaker 3: end up having you know, right now it's only data
Speaker 3: centers are only point four percent of water use, but
Speaker 3: growing water needs for a I could bump up just
Speaker 3: in Texas the water used directly and indirectly from AI
Speaker 3: to as much as five percent, and that would be
Speaker 3: you know, that would exceed that of livestock and mining.
Speaker 3: It would still be well short of irrigated farming. But
Speaker 3: there are places that are water stressed where you know,
Speaker 3: it is not trivial that the build up of what
Speaker 3: we're trying to what the tech industry is intending.
Speaker 1: Yeah, and then their thing in Texas is you have
Speaker 1: you have an exploding human population. So when when when
Speaker 1: urban planners are thinking about water consumption into the future,
Speaker 1: and you're talking about an industry going from point four
Speaker 1: to five percent, that's like meaningful water. But like, but
Speaker 1: to that question of when when these entities that build
Speaker 1: data centers survey the country, why are they picking where
Speaker 1: they pick.
Speaker 3: Why are they picking it? The very biggest factor is power.
Speaker 3: So we have an aging power grid. And while we
Speaker 3: have lost some power users because we have de industrialized,
Speaker 3: we have a grid that it has not kept up
Speaker 3: with with the progress of the economy and and now
Speaker 3: needs both because of extreme weather and uh just general
Speaker 3: you know, age needs a lot of investment and the
Speaker 3: you know, power grid just cannot handle gigawatt scale, uh
Speaker 3: power just anywhere. So what is a gigawatt? Gigawatt is
Speaker 3: as much power as the whole city of San Francisco
Speaker 3: or Denver consumes.
Speaker 2: In how much time.
Speaker 3: It's a capacity figure. You can also look at at
Speaker 3: energy as like you need plants capable of producing this
Speaker 3: much a gigawatt.
Speaker 1: So so a plant would you're saying, like an AI
Speaker 1: data center and AI campus data center campus would feasibly
Speaker 1: use the same amount of power that is being used
Speaker 1: in Denver.
Speaker 3: Correct or more.
Speaker 1: There are multis and that's like the residents, the businesses,
Speaker 1: the manufacturing, yeah, the.
Speaker 3: Whole community, and as going to this concentrated place. Yeah,
Speaker 3: it's a big land mask, but we're talking a few
Speaker 3: thousand acres where that much power could be going into
Speaker 3: a single place. So it's it's the scale.
Speaker 1: Of it is selecting areas where there's where there's the
Speaker 1: possibility of getting and moving that amount of power.
Speaker 3: Yeah, and that has It's not like, you know, just
Speaker 3: because there are power lines going through a property or
Speaker 3: just because there's a power plant, a nuclear power plant
Speaker 3: in the vicinity that is available. So then you get
Speaker 3: to things like power congestion and the ability to pull
Speaker 3: a large amount of power to a single location. And
Speaker 3: so it becomes this really complicated matrix of factors that
Speaker 3: are bringing people places. So it's you know, can the
Speaker 3: power are there? Are there pockets of power that are accessible?
Speaker 3: Does the the community or the state make it easy
Speaker 3: to build? Is there water? This is not the very
Speaker 3: first concern though, Is there fiber? Fiber is easier to lay,
Speaker 3: but you know, we also had a glot of fiber
Speaker 3: that was laid in the you know, in the dot
Speaker 3: com days, So you know there these are some of
Speaker 3: the concerns. You know, others are our land value and
Speaker 3: so you will now see data center developments going up.
Speaker 3: It's in you know, virtually everywhere, and.
Speaker 1: Like when you factor all this in, they are are
Speaker 1: they actually looking for land deals like the costs of
Speaker 1: the land matter to them.
Speaker 3: Yeah, the cost of the land matters. Places where data
Speaker 3: centers are quite saturated, like northern Virginia, the you know,
Speaker 3: the land values have approached, you know, the millions of
Speaker 3: per acre and you can't really even get a campus
Speaker 3: that's that big. And so you know, AI starts with
Speaker 3: these big training campuses that are big. But eventually, and
Speaker 3: not too long from now, where you're going to hear
Speaker 3: a lot more about how do you fill in the
Speaker 3: smaller but you know, state of the art data centers
Speaker 3: to do what is called inference, which is basically the
Speaker 3: thing that makes money, which is finding the answers to
Speaker 3: your questions, querrying the model and getting back the answer
Speaker 3: like which could be, you know, driving your autonomous car
Speaker 3: through a town. A data center is going to do
Speaker 3: that for you. It could be you know, figuring out
Speaker 3: the cure for you know, a rare disease. The data
Speaker 3: center we'll do that for you.
Speaker 2: Do you have little kids?
Speaker 3: I have three older kids. There are teenagers and once
Speaker 3: inn or twenty.
Speaker 1: And it weird that you run around yelling at them
Speaker 1: about leaving the lights on. Yeah, well you should do
Speaker 1: you should yell at them about not looking stuff up
Speaker 1: on the internet. Yeah, you should be like, don't look
Speaker 1: pancake recipes up on the internet. You can look it
Speaker 1: up in a cookbook. Well, I did also leaveing the
Speaker 1: lights on in your room. It's inconsequential. It's just it's insane.
Speaker 3: There are calculators that show you asked about, like, just
Speaker 3: to go back to the water thing for a minute,
Speaker 3: does a chat stoopetee query really use a bottle of water?
Speaker 2: Yeah, I don't even know. I hear all the numbers,
Speaker 2: but I don't know what.
Speaker 3: There was a study that said so there are also
Speaker 3: data points that indicate a far smaller amount, like a
Speaker 3: teaspoon two teaspoons. And I'm not the expert to fully,
Speaker 3: you know, parse that out. But the one thing that
Speaker 3: I could, I could say with some confidence is that
Speaker 3: computing is getting more efficient, even AI computing every day.
Speaker 3: It's this, you know, it's this quandary that the industry has.
Speaker 3: They can't find enough power, water, land, they can't you know,
Speaker 3: get enough of their computing end at these places. So
Speaker 3: everybody in the whole value chain is like innovating trying
Speaker 3: to do it with less, and so I wouldn't be
Speaker 3: surprised if you know they're there are big advances and
Speaker 3: and and perhaps these newer estimates of what a chat
Speaker 3: gypt search does use and water are taking into account
Speaker 3: some of that efficiency. But you're going to have the
Speaker 3: problem right now is that there are wildly different estimates
Speaker 3: and plenty of them are scary numbers that have no
Speaker 3: context around them. They haven't been compared to anything else.
Speaker 1: Yeah, that's that's the that's the problem you run into.
Speaker 1: Before we started record, we were having we were talking
Speaker 1: and you had mentioned you'd mentioned that there's become like
Speaker 1: a sort of red state blue state divide on data
Speaker 1: center placement.
Speaker 3: Yeah, well, except this now become bipartisan against.
Speaker 2: It's become bipartisan against.
Speaker 3: Yeah.
Speaker 1: Yeah, Like like, let's talk a little bit about because
Speaker 1: just on this, on this idea of physical placement, right,
Speaker 1: there's a there's a big I think that there's generally
Speaker 1: like a nimby, a not in my backyard component to this,
Speaker 1: where most of the fights you see about data centers
Speaker 1: from my perspective, you might have a different perspective. Most
Speaker 1: of the fights you see about data centers are localized,
Speaker 1: meaning one's going in near you one's going near you
Speaker 1: in Wisconsin, one's going in near you in Michigan, one's
Speaker 1: going in near you in Montana. And all of a
Speaker 1: sudden it gets real right, and and then you want
Speaker 1: to talk about what does this mean? Water use is here?
Speaker 1: What does this mean? Energy use here? What does it
Speaker 1: mean for just the visual quality of the landscape here.
Speaker 1: I'm sure there are crusaders on a national sense, but
Speaker 1: I'm more familiar with the localized fights. Right as you've
Speaker 1: looked at this, what have you found about the mentalities
Speaker 1: or like the communities that are wanted the communities that
Speaker 1: don't like? What sort of differentiates them? Is it? Is
Speaker 1: it ideology like political ideology?
Speaker 2: What is it?
Speaker 1: You know, a friendly town versus an antagonistic town.
Speaker 3: Well, I it's a combination of how they feel they
Speaker 3: were treated from the beginning and how you know, their
Speaker 3: their ability to imagine what the future could be hold
Speaker 3: for them, possibly economically. So, the northern Virginia has a
Speaker 3: very heavy concentration of data centers today and it takes
Speaker 3: twenty five percent of power use in Virginia now goes
Speaker 3: to data centers, and it's mostly the whole state, and
Speaker 3: people in northern Virginia have have benefited economically from the
Speaker 3: tax revenue. Okay, so, uh, data centers don't employ as
Speaker 3: many people, especially the older data centers. They therefore don't
Speaker 3: bring a big burden on hospitals, schools, roads, ambulance all
Speaker 3: that stuff.
Speaker 2: Town once they're built like ghost towns.
Speaker 3: Right the cloud data centers employed, you know, it could
Speaker 3: be like twenty people, although the bigger AI data centers
Speaker 3: are going to employ hundreds of people, some of them
Speaker 3: even say in the four figures. But but the so
Speaker 3: some of these places have have had a huge influx
Speaker 3: of tax revenue, they've improved their schools. Northern Virginia fits
Speaker 3: that even so, so it gets to a certain point
Speaker 3: where people you know, are living with with these developments
Speaker 3: right up in their backyard in some cases nice homes
Speaker 3: and a big data center right behind and and they're
Speaker 3: starting to say no more. They're starting to worry about backup.
Speaker 3: Power doesn't run all the time, but it has to
Speaker 3: test and then if there's a power outage, that's going
Speaker 3: to burn diesel. Diesel is one of the worst things
Speaker 3: that you can burn for air pollution and health.
Speaker 1: And so.
Speaker 3: Northern Virginia is an example of a community that welcomed
Speaker 3: data centers, you know, kind of prospered with them, and
Speaker 3: is starting to hit a breaking point of.
Speaker 2: The moods starting to sour.
Speaker 3: The mood has started to get much tougher, and there's
Speaker 3: going to have to be a conversation. Even so, even
Speaker 3: in northern Virginia, the actual land use of data centers,
Speaker 3: by just square footage is the campuses themselves are still
Speaker 3: less than three percent of the land and loud In County,
Speaker 3: the most data center populated county. And if you and
Speaker 3: if you just looked at the buildings, it's less than
Speaker 3: you know, one percent of the land and not a
Speaker 3: data center capital. But it's like, but that's it's not
Speaker 3: nothing because we I.
Speaker 1: Know, but that's a weird way to think about landscape.
Speaker 1: That you're saying a percent of a county, yeah, is
Speaker 1: under a data center. I think I would want to
Speaker 1: know what percent of the county is under a house, because.
Speaker 2: I mean, like, I don't even know what to make
Speaker 2: of that, you know.
Speaker 1: I mean it's like it's like the point you made
Speaker 1: about that you hear these numbers, but without context, it's
Speaker 1: hard to understand. Like I don't think that I don't
Speaker 1: hear that a percent of a county sits underneath the
Speaker 1: data center.
Speaker 2: I don't hear that and think that's not much.
Speaker 1: Yeah, yeah, but I don't know.
Speaker 2: But again I don't know what percents under.
Speaker 1: Schools.
Speaker 2: I don't know what percent is under homes, you.
Speaker 1: Know, right right, But it feels to me like a ton.
Speaker 3: There are you know, certainly denser urban environments. This becomes
Speaker 3: a real concern with with you know, so many resources
Speaker 3: and waterflow and everything, so that the communities that, you know,
Speaker 3: some communities that have welcome data centers are still experiencing backlash.
Speaker 3: And I think it's because it's just such a profound change.
Speaker 3: But there are parts of the country that also have
Speaker 3: economic synergies. I guess you could say with with this
Speaker 3: type of an industry, they have factories that can and
Speaker 3: are producing the equipment that goes inside. They've got a
Speaker 3: workforce of electrical and mechanical and trades craft workers who
Speaker 3: have been underemployed for a long time, and and that's
Speaker 3: our to kind of work together. Like there are there
Speaker 3: are some several areas in the rost belt that the
Speaker 3: economic development authorities have you know, either recruited data centers
Speaker 3: or we're open to data centers coming the workforce, especially
Speaker 3: like organized unions are very in favor of it. And
Speaker 3: then other residents who live in the midst of farmland
Speaker 3: are not in favor of it and don't want it.
Speaker 3: And so there are some really hard trade offs, you know,
Speaker 3: because we all need jobs and economic activity in our
Speaker 3: community and that is actually what ends up funding all
Speaker 3: of the infrastructure that makes the city livable.
Speaker 2: Yeah, I want to hate you two ideas.
Speaker 1: One is, you had mentioned that it used to be
Speaker 1: that like blue states or left leaning states or antagonistic
Speaker 1: data sent just speaking very generally right leaning states were
Speaker 1: more welcoming to data centers. But you had said that
Speaker 1: it is it is becoming that that you're finding resistance
Speaker 1: in right leaning states. We always thought about this state.
Speaker 1: You familided this like horseshoe deal. We're like the right
Speaker 1: and left kind of come together, the radical right and
Speaker 1: the radical left come together at.
Speaker 3: The bottom of them. Yeah, it's these two different sides.
Speaker 1: Yeah, but they like they almost meet, they almost Is
Speaker 1: that what is the sort of what is the right
Speaker 1: leaning what is the emerging right leaning argument against data centers?
Speaker 1: Is it like antagonism to big tech.
Speaker 3: It's partially antagonism to big tech. You know, they're spying
Speaker 3: on my life. They you know, are driving our young people,
Speaker 3: you know, the wrong direction. It's partially property rights. I
Speaker 3: will not have my property, you know, seized for a
Speaker 3: transmission line that you know sends power to you know,
Speaker 3: Eline Musk's you know, or Sam Altman's data center, and
Speaker 3: so they can.
Speaker 2: Get rich off my land or that's.
Speaker 3: Right and it's their way of life. I will tell
Speaker 3: you that when you go to some of those communities, though,
Speaker 3: people will acknowledge a mixed feeling because some of them
Speaker 3: have sold there. You don't even have to have sold
Speaker 3: a big piece of property inside the data center to
Speaker 3: possibly have your property value, you know, a potential potential gain,
Speaker 3: like maybe they want to lay down equipment in a
Speaker 3: in a yard and you've got a few acres where
Speaker 3: you could do that that's nearby. Or you decided that
Speaker 3: you want to run a food truck and you know,
Speaker 3: go sell to the workers, or you know, there's uh,
Speaker 3: there're a variety of maybe your your land was used
Speaker 3: to build worker housing like a man camp.
Speaker 1: So is it generally are data centers generally raising property levels?
Speaker 3: The inverse there's such a land rush right now and once,
Speaker 3: and these are such big construction projects that I think
Speaker 3: in many cases the properties near these projects do experience
Speaker 3: you know, rising property value.
Speaker 1: Yeah, because picture we're talking about that they're putting in
Speaker 1: a municipal wastewater treatment plant.
Speaker 3: Yeah okay, compared that to like a landfill coming to town.
Speaker 1: Yeah, maybe that's going to be like good for some,
Speaker 1: but the people around that are going to be like,
Speaker 1: that's going to tank my home value right right. So
Speaker 1: with in the data center landscape, when it comes to
Speaker 1: land ownership and land use in the data center landscape,
Speaker 1: I could see if they're coming in, they're going to
Speaker 1: they need this, you know whatever many you know that
Speaker 1: they need five square miles ten square miles of land.
Speaker 1: That the impact that the people that own those properties
Speaker 1: are going to see perhaps a little gold rush. Yeah,
Speaker 1: But what is the conversation about people that are outside
Speaker 1: of the footprint.
Speaker 3: Yeah, it's tough.
Speaker 2: I mean what are they seeing?
Speaker 3: They hate the well, everybody hates traffic, artisan rage against
Speaker 3: the traffic, and that lasts for several years in these big,
Speaker 3: big projects, Like people bring that up way before global warming,
Speaker 3: They bring it up way before traffic, you know, traffic, traffic,
Speaker 3: dust traffic, you know. So, you know, they were giving
Speaker 3: free car washes out in Wisconsin near the Port Washington
Speaker 3: data center. No, maybe people appreciated it. It's a it's
Speaker 3: a pretty small you know, uh, it's a small token
Speaker 3: of something, but you know, seriously, oh yeah, oh yeah,
Speaker 3: because it was it's going to be dusty and dirty
Speaker 3: for a really long time.
Speaker 1: There had been a lot of people that just did
Speaker 1: not want to accept that free car yeah car wash,
Speaker 1: my god man.
Speaker 3: But you do go to places where this has been
Speaker 3: underway for at least a year, and there are hotels
Speaker 3: being redone, there are new restaurants that have come in,
Speaker 3: there are and you know, like that's the case in Louisiana,
Speaker 3: and that's thirty minutes away from the data center site.
Speaker 1: So some revitalization, some investment that's not totally tied to
Speaker 1: the data center.
Speaker 3: That's right, and the you know, like these are they're
Speaker 3: criticized as temporary jobs, but often these projects last for
Speaker 3: a few years, longer than many people hold jobs. And
Speaker 3: then there they they tend to cluster, like you know,
Speaker 3: a good you know environment where people think they can
Speaker 3: get business done, they can build more come. So then
Speaker 3: it turns out that there are a lot of projects
Speaker 3: and a lot of people kind of moving from one
Speaker 3: to the other, and they're supervisors and they're you know,
Speaker 3: will rent apartments in a lot.
Speaker 1: Of this is just like ephemeral activity. It generates general
Speaker 1: economic activity.
Speaker 3: Yeah, but you know that there's but I've also knocked
Speaker 3: on the door of houses that like the guy wasn't home,
Speaker 3: but he was. He was sitting across from a new
Speaker 3: RV camp that was gonna and he just had a
Speaker 3: little ranch house and flat as far as I could
Speaker 3: see in Texas grappling, and across the street was being
Speaker 3: placed a three thousand RV camp, you know, with telephone
Speaker 3: not telephone of contractors poles. They were basically putting in
Speaker 3: water and power poles on an expansive land that was
Speaker 3: extremely flat, broad huge imagine three thousand recreational vehicles. So
Speaker 3: this is where the workers would come. And so all
Speaker 3: of a sudden, what was in an empty field in
Speaker 3: front of him was almost looked like, you know, a
Speaker 3: future airport or something. He wasn't there that day when
Speaker 3: I knocked on a store, but I'm telling you might
Speaker 3: have had a really different view and so like, there
Speaker 3: are some growing pains and some real, real concerns about growth.
Speaker 1: On the power front. Can you tell me again in
Speaker 1: Northern Virginia that the power increase for data centers.
Speaker 3: Again, well, it's twenty five percent of power in the
Speaker 3: state those to data centers and probably growing.
Speaker 1: So however they're generating electricity. However they're generating power. It's
Speaker 1: not like, I mean, to a point you probably go
Speaker 1: and just turn the dial up right and make more. Yeah,
Speaker 1: but I imagine when you're talking about a twenty five percent
Speaker 1: increase in power, you need to start looking at make
Speaker 1: like it's more than just cranking up what you got
Speaker 1: going on. Meaning, if you're running hydro electric, you know
Speaker 1: you got turbines one through thirteen running and you just
Speaker 1: kick fourteen and fifteen and sixteen on to make up.
Speaker 2: For the heavy use.
Speaker 1: There's a point at which that doesn't work anymore and
Speaker 1: you need new ways. Yes, you need new power that
Speaker 1: new power production.
Speaker 3: But I mean one thing that is, you know, a
Speaker 3: very hot topic of conversation that would be good for
Speaker 3: everybody is something called grid utilization, which we all as
Speaker 3: a as a society contribute to shared resources and the
Speaker 3: power grid is one of those, and we are not
Speaker 3: utilizing the grid that we've already paid for to the
Speaker 3: extent that we could be. But technology is only now
Speaker 3: helping us understand how far up that level of headroom
Speaker 3: you could really go safely. And so there's all these
Speaker 3: new technologies and utilities are starting to be open to
Speaker 3: it to say, hey, yes, we do need to build
Speaker 3: more power. But turns out the grid is only you know,
Speaker 3: actually we're only using thirty to fifty percent of the
Speaker 3: power that we've already built on a given day because
Speaker 3: we overbuilt it for those days of peak power demands
Speaker 3: and our ability as a human mind to do the
Speaker 3: simulations to figure out how far you could push it
Speaker 3: just didn't go that far. So we just built a lot.
Speaker 3: We bought a lot of extra.
Speaker 1: Understand Like, let's say you're in a Let's say you're
Speaker 1: in a town. You live in a coastal community that's
Speaker 1: a very popular summer destination.
Speaker 2: Yeah, and when it's awful, you.
Speaker 1: Know, I was recently on really hot Yeah, I was
Speaker 1: recently on an island and there's this little community on
Speaker 1: this island and someone told me, you know, we people
Speaker 1: live here here around because there's ten residents year round.
Speaker 2: Yeah, in the summer there are four hundred residents. Yeah.
Speaker 1: Okay, so picture a town like that, and then picture
Speaker 1: the hottest day in the summer, everyone's electric turning on
Speaker 1: a c I see your point where it's capable of that, yes,
Speaker 1: but then come here in February winters right, nobody here.
Speaker 1: So yeah, presumably there's infrastructure that's not completely utilized. I
Speaker 1: hadn't really, I never thought.
Speaker 2: Of that before.
Speaker 3: Yeah, and like that, the utility industry really needed somebody
Speaker 3: to wake it. So wake it up, you know, or
Speaker 3: to push it, because they are not incentivized to. Utilities
Speaker 3: have this perverse way of getting paid. It's just it's
Speaker 3: an incentive that got put in when we created monopoly
Speaker 3: utilities in the dawn of the electric age, and they
Speaker 3: make more money by spending more money. Basically, they go
Speaker 3: to a utility commission and say we need power for
Speaker 3: reliability purposes. I want to build a new thing, a
Speaker 3: new power plant, a new line, a new and they
Speaker 3: get a guaranteed rate of return if it is approved
Speaker 3: to compensate them for you know, the capital that is
Speaker 3: needed for that. And so we we all pay that.
Speaker 3: We all pay the cost of what it was to
Speaker 3: build plus an added rate of return. And sometimes you
Speaker 3: could argue that they didn't need to build that brand
Speaker 3: new thing. They should learn how to use what we've got.
Speaker 3: And so the tech industry is looking at they're in
Speaker 3: such a hurry, and they've they've realized there are certain
Speaker 3: inefficiencies in the way the system is built, and they
Speaker 3: have the money and the motivation to shake up the
Speaker 3: system and say, well, hang on, yes, I you know
Speaker 3: I will if I don't offer to pay my full
Speaker 3: share on all this new infrastructure. I know I will
Speaker 3: not have the social license to build and I will
Speaker 3: be vilified. But at the same time this let me
Speaker 3: fund you know, these pilot projects, or let me add
Speaker 3: these sensors to lines, because we could we could be
Speaker 3: determining how far we could push this. And I'm also
Speaker 3: willing to spend my own money to put batteries behind
Speaker 3: the meter and other systems. So when everybody is at
Speaker 3: that four hundred person seaside resort and that state is,
Speaker 3: you know, hurting for electricity, I disappear from the grid.
Speaker 3: So much of this is happening.
Speaker 2: Yeah, that's interesting.
Speaker 1: People don't but why are you seeing art like not
Speaker 1: you like, why do you see articles where it's that
Speaker 1: they're going to be building like you know, nuclear plants
Speaker 1: to power the base of the scale of what.
Speaker 3: We're doing requires all of it, literally.
Speaker 1: So you do expect, like even though you could find
Speaker 1: there's efficiencies to be found in energy production and we're
Speaker 1: generating electricity and running it through the grid and it's
Speaker 1: not being tapped and it just you know, isn't being
Speaker 1: stored in batteries. Whatever there is going to be in
Speaker 1: our twenty thirty outlook, there will need to be like
Speaker 1: net new.
Speaker 2: There will generation.
Speaker 3: And you can ask like, can we stop this from half?
Speaker 3: And I I'm not sure that we can. I think
Speaker 3: money finds a way when it's trying to you know,
Speaker 3: get to a goal. So I think we will uh
Speaker 3: build quite a bit of additional generation. Utilizing the grid
Speaker 3: we have right now is just a faster way to
Speaker 3: do it.
Speaker 1: It's really built.
Speaker 3: So we're we are revitalizing old nuclear plants that have
Speaker 3: you know, we're built fifty years ago. We are putting
Speaker 3: in newer, more efficient forms of power generation both you know,
Speaker 3: solar and batteries as well as you know, newer generations
Speaker 3: of gas plants, which is uh not necessarily a popular thing,
Speaker 3: but is uh going to happen. And there's all kinds
Speaker 3: of other really interesting things happening in the energy industry.
Speaker 3: We are applying a set of pioneers that came from
Speaker 3: the oil and gas industry in fracking, are using those
Speaker 3: techniques to reimagine geothermal power so that you can you
Speaker 3: don't have to go where there are pockets of steam
Speaker 3: already in the earth. You can go to a location
Speaker 3: and inject water, create steam, create the steam that spins
Speaker 3: the turbine, send that water back down in a closed loop,
Speaker 3: and again like more water efficient, huh. And the better
Speaker 3: you get at it, the more you do it, the
Speaker 3: lower your costs. Aren't There's a company called Fervo that
Speaker 3: is kind of the darling of new geothermal.
Speaker 2: That's incredible.
Speaker 1: It's it's like that I'm not familiar with that concept,
Speaker 1: but it's basically you're making a steam engine, but you're
Speaker 1: using instead of burning coal to heat the water, you're
Speaker 1: you're using the Earth's thermal.
Speaker 3: That's exactly right, really, and you're using techniques and workers
Speaker 3: who came from an industry that you know either you
Speaker 3: know needs the worker needs to be transitioned into a
Speaker 3: cleaner form, but have the skills, and so that's been
Speaker 3: a popular thing. And that's you know, here we are
Speaker 3: in Montana. Some of the interesting projects on that are
Speaker 3: near you. There's work being done in Utah and in
Speaker 3: Nevada and I and there's work on this you know,
Speaker 3: enhanced geo thermal in Texas. There's there's a lot going
Speaker 3: on in that. So you have to get the cost down.
Speaker 3: But they're actually making great progress getting the cost down.
Speaker 1: Wouldn't it be interesting if it'd be interesting if unexpected
Speaker 1: upside amid all the downsides, an unexpected upside is just
Speaker 1: like this this sort of like American ideal that you
Speaker 1: know need driving innovation.
Speaker 3: Yeah. I mean that's a big theme in the book.
Speaker 1: That you're going to get these certain like you're gonna
Speaker 1: like for a while you had this certain these certain
Speaker 1: types of brain chasing renewables, right, but now you have
Speaker 1: like a whole different class and category of.
Speaker 2: Humans, right that are like looking at energy.
Speaker 1: Right, Just like it'd be kind of an it'd be
Speaker 1: like a weird irony if if that sector, if that
Speaker 1: sector figured out maximizing renewables.
Speaker 3: That's right, And I think we'll end up. So not
Speaker 3: to scare you were your viewers here, but I think we're,
Speaker 3: like I said earlier, we're at the beginning of this
Speaker 3: more of an industrial revolution that is catalyzed by AI.
Speaker 3: We think today of energy demand for things like chatbot prompts,
Speaker 3: but we're going into an era of physical AI where
Speaker 3: all of this high performance computing is going to be
Speaker 3: used to guide cars, guide robots in factories, make uh
Speaker 3: you know, whether you like it or not, weaponry autonomous uh,
Speaker 3: you know, change the way industrial automation makes things so
Speaker 3: that we possibly can make factories viable again. A lot
Speaker 3: of that demand and a lot of that uh you know,
Speaker 3: just activity to make that happen is just barely beginning.
Speaker 3: And so we may end up just creating more energy
Speaker 3: generation to feed more applications of AI than we can
Speaker 3: imagine today. And so that's where it gets a little scary.
Speaker 3: You think about the ramp up and how you know,
Speaker 3: this could change everything. It can bring positives and it
Speaker 3: can bring negatives. And I think, you know, one of
Speaker 3: the things that I'm trying to do is look at
Speaker 3: what each side wishes the other would acknowledge about both
Speaker 3: the promise and the and the peril of what is
Speaker 3: facing us?
Speaker 1: How would you put that? Like, like, how would you
Speaker 1: put those two questions if you had to answer them?
Speaker 1: You know, if if you imagine the brightest minds, like
Speaker 1: the brightest most rational minds in the in the anti
Speaker 1: data center movement, and you say that I and they're
Speaker 1: saying to the and they're saying to the industry, I
Speaker 1: wish you would acknowledge, right, And and on the flip side,
Speaker 1: what is the what is the thing you found?
Speaker 3: Yeah? Well I would say what uh, the energy industry
Speaker 3: would say, I wish we would all acknowledge is that
Speaker 3: the modern world runs on energy. And you can draw
Speaker 3: an uppard line of uh, you know, press arity and
Speaker 3: energy that that's pretty much aligned. The more energy society consumes,
Speaker 3: the higher it's quality of life and replacing what we
Speaker 3: Modern life has become really convenient. So you don't even
Speaker 3: really see the power plant. You just plug your phone in.
Speaker 3: Modern life has become so convenient. You don't really understand
Speaker 3: how we get water. You just turn the faucet on.
Speaker 3: You just order, you know, stuff from Amazon. You just
Speaker 3: assume that you know, steel is coming from somewhere to
Speaker 3: build your buildings. Yeah, you know, it's all industrial. It's
Speaker 3: it's and we assume these days that solar is just
Speaker 3: really cheap and batteries are just getting better. They are
Speaker 3: they and they're improving, but they too have an environmental
Speaker 3: and industrial footprint. I mean, you've got to you know,
Speaker 3: you've got to convert raw material to make the products.
Speaker 3: They need to be recycled eventually too. Modern life is
Speaker 3: is industrial and so I think that that is what
Speaker 3: you know, in some ways, the the you know, guys
Speaker 3: who have been in industry building physical things want everyone
Speaker 3: to understand and they want people to understand that what
Speaker 3: we've done so far has made a dent in you
Speaker 3: to make a greener world and planet has improved. You know,
Speaker 3: we we've we've improved emissions by introducing green energy, and
Speaker 3: we need to do a lot more of it. But
Speaker 3: we also you know, we have a long way to
Speaker 3: go to uh decarbonize the world, and it's going to
Speaker 3: take a lot of new technology, new new thinking, some
Speaker 3: adapt and so I would say that, you know, on
Speaker 3: the on the energy side, they're saying like the world
Speaker 3: needs more energy because we prosper with more energy. More energy,
Speaker 3: you know, is part of just progressive civilization. But we
Speaker 3: need we need lower emissions, we need cleaner water, we
Speaker 3: need all those things.
Speaker 1: You feel the industry is asking for lower emissions and
Speaker 1: cleaner water. I mean, I feel like the industry is
Speaker 1: largely I mean, you know, I mean right, I mean,
Speaker 1: the industry is largely given up on the green energy conversation.
Speaker 1: I mean, like the dry like the main driving factors,
Speaker 1: like the administer, the administration, big tech. I mean, this
Speaker 1: isn't a concern of theirs anymore. It's so twenty twenty three.
Speaker 3: It is so twenty twenty three. I think that, uh,
Speaker 3: it's it could come full circle again with some of
Speaker 3: the innovation that we're seeing. The the tech companies are
Speaker 3: still still standing by goals that now look increasingly impossible
Speaker 3: to meet in terms of zero by twenty thirty. And
Speaker 3: look at the direction that they're going.
Speaker 1: Yeah, whenever you see like a like a twenty thirty year,
Speaker 1: everyone come on.
Speaker 3: And so then you know, on the other side, that's
Speaker 3: where the you know, advocates for climate action, for the environment,
Speaker 3: for health are saying, you know, you need to acknowledge
Speaker 3: your full life cycle footprint and communities need to uh
Speaker 3: hear everything transparently that you are are coming into a
Speaker 3: community and going to do and there's a lot that
Speaker 3: there's a lot of dialogue that you know, it's kind
Speaker 3: of hard to have when the two sides are at odds.
Speaker 3: But I would say, you know, the environmental groups are saying,
Speaker 3: look like, don't don't de emphasize, like you know, the
Speaker 3: truth is, you know, if you're backing up your data
Speaker 3: center with diesel, you know that creates air pollution for
Speaker 3: the community. If we're all using shared water and you
Speaker 3: are adding incremental water demand, this is an issue for
Speaker 3: the community. If you are removing virgin land and wild places,
Speaker 3: you know, we ought to have a say on it.
Speaker 3: And so it is a natural kind of back and
Speaker 3: forth that is happening right now. And it is concerning that.
Speaker 3: You know, there's there's a lot of money on the
Speaker 3: pro development side, and so you know, that's where I'm
Speaker 3: trying to kind of watch and see, you know, how
Speaker 3: is this happening. There's a you know, maybe it's a
Speaker 3: it's a the voice is not as loud, but there
Speaker 3: are voices within tech companies, within even guys who who
Speaker 3: have been in the field developing data centers, who say, look,
Speaker 3: we need to get to a place. Communities have a
Speaker 3: lot of leverage now to ask for more. They've now
Speaker 3: realized like, hey, we're you know, we're kind of a
Speaker 3: unicorn here. We've got a big pot of you know, uh,
Speaker 3: available power or water or what have you. And maybe
Speaker 3: our community is open to doing business with you, but
Speaker 3: you know, we we don't want to give you know,
Speaker 3: tax incentives that we used to.
Speaker 2: They realized they might have more leverage and more leverage.
Speaker 3: Yeah, you know, we used to give these certain breaks
Speaker 3: to low margin industrial users that you know, we're trying
Speaker 3: to afford to build a big car plan. It's a
Speaker 3: really different community, you know, of potential users of the
Speaker 3: land that are coming in now. And not only that,
Speaker 3: they do have technologies that can actually improve the community.
Speaker 3: So not only can they give money for a new
Speaker 3: firehouse or fix the you know, give money for schools,
Speaker 3: they could use high performance computing and help the community
Speaker 3: figure out, you know, and they are doing this there.
Speaker 3: You know, there are good partnerships happening with with water
Speaker 3: where they're saying, if we come in, let us spend
Speaker 3: tens of millions of dollars in your community to help
Speaker 3: shore up your leaky water system and in exchange, you know,
Speaker 3: that will help us replenish more water than we're actually
Speaker 3: using at our data center. So there there are things
Speaker 3: like that. There's a there's a guy who was kind
Speaker 3: of known as the sort of conscience of the data
Speaker 3: center industry, Christian Ballotti, and I've gotten to know him.
Speaker 3: He was at Microsoft. He he's basically coined some metrics
Speaker 3: about how efficient a data center could be. And then
Speaker 3: the the latter part of his career Microsoft, he did
Speaker 3: a lot of R and D into community positive data centers.
Speaker 3: And he's now independent on working, you know, as an
Speaker 3: advisor in a lot of ways. And you know, he
Speaker 3: says that his industry needs to think about what would
Speaker 3: make a community want the data center, he said, and
Speaker 3: tells and tells his peers. Until you're willing to live
Speaker 3: next to that data center, then you haven't finished doing
Speaker 3: your job and you wanted to be like please in
Speaker 3: my backyard. And there are some some really interesting ways
Speaker 3: that he's seen infrastructure get developed. Like he he often
Speaker 3: will cite a like a a plant, a water desalination plant,
Speaker 3: the difference between one that was done in Australia and
Speaker 3: one was done in Singapore and the one that was done,
Speaker 3: you know, more community positive way. You know, it's got
Speaker 3: like a roof of grass and has you know, all
Speaker 3: these different ways that it recycles the water that flows
Speaker 3: in the community. He's gone to places that you know,
Speaker 3: are farming communities and small simple things like we will
Speaker 3: plant trees that improve the pollination in your community for
Speaker 3: your agriculture. Okay, Like this industry is willing to do
Speaker 3: some of those things if you ask for them. But
Speaker 3: you know, there's a big difference between a large company
Speaker 3: that's coming in trying to get permission social license to operate,
Speaker 3: and then there's a lot of other you know, just
Speaker 3: private developers that are looking for, you know, something to
Speaker 3: develop fast and flip quick.
Speaker 1: And yeah, I feel like they've done a poor job
Speaker 1: like well, I mean it's kind of university, except that
Speaker 1: they've done a very poor job of, uh, their social.
Speaker 2: Management of the issue, for sure.
Speaker 1: And I think it's because on one hand of like
Speaker 1: pushing the radical amount of change and then also thinking
Speaker 1: that they were going to do the data center move
Speaker 1: in a lot of communities quietly. Yeah, you know, and
Speaker 1: I understand the approach you're making because I think that
Speaker 1: a lot of times people. There's an expectation that towns, villages, communities,
Speaker 1: whatever are gonna sort of like bait the hook to
Speaker 1: bring them in, and if the tide turns enough, it's
Speaker 1: going to flip that right. And rather than saying, oh,
Speaker 1: we'll give you these tax breaks, we'll give you this land,
Speaker 1: we'll give you all these incentives that you that you'd
Speaker 1: play that political game enough to the point where it's like, well, why.
Speaker 2: Don't you tell me what you're going to do for me?
Speaker 3: Right?
Speaker 1: And maybe and maybe that switch will you know, maybe
Speaker 1: that switch will happen and there's so much there's so
Speaker 1: much need that it'll it'll push, it'll push that negotiating
Speaker 1: process in a totally different direction.
Speaker 3: I think that that's happening now. I think that there's uh,
Speaker 3: you know, communities are understanding that the ones like ironically
Speaker 3: that you know, got started first and are probably going
Speaker 3: to be the most economically viable because they got started first,
Speaker 3: you know, they they kind of came into being in
Speaker 3: a little earlier place where there is real competition between
Speaker 3: states for big economic projects. And so I've been traveling
Speaker 3: all over the country a lot of places like literally
Speaker 3: for a decade, they were looking for a car manufacturing
Speaker 3: plant and and had assembled a big megaproject site and couldn't.
Speaker 3: They were like second and third and more than the West,
Speaker 3: and they lost it again and again and again. And
Speaker 3: when data centers came along, you know, there's a rival,
Speaker 3: and they know who their rivals are, and they know,
Speaker 3: you know, maybe it's Wisconsin versus Indiana, maybe it's Louisiana
Speaker 3: versus Mississippi, and so they didn't want to lose it,
Speaker 3: and they they offered incentives which in retrospect maybe they
Speaker 3: needed them at the time or they certainly, you know,
Speaker 3: were intending to bring business economic prosperity to their state.
Speaker 3: But there's a lot of things when we look with
Speaker 3: hindsight later at this year, maybe we should have done
Speaker 3: it this way instead.
Speaker 2: Are you seeing that when you talk to people.
Speaker 3: Yeah, I mean I I've talked with with mayors who say, boy,
Speaker 3: I would have asked for even more had I realized
Speaker 3: how much leverage I have and the you know, and
Speaker 3: some things are getting retraded. You know. Microsoft came to
Speaker 3: a community in Indiana and said, we'd actually like to
Speaker 3: give you a better financial deal. And it has to
Speaker 3: do with the way that they've structured taxes, and it
Speaker 3: gave a lot more money to the school system right away,
Speaker 3: and they just came back and said, this is more
Speaker 3: in keeping with what we're doing now. So it's kind
Speaker 3: of a given and take. But what we're going up
Speaker 3: to is data center backlash has gotten worse. I think
Speaker 3: part of it is, you know, people have facts about
Speaker 3: their town and fears that it's just really hard to
Speaker 3: separate the truth from the noise. And and sometimes the
Speaker 3: truth is not good either. And so we're going to
Speaker 3: have an election cycle where is I just wrote a
Speaker 3: column about this where you know, I was talking about
Speaker 3: the political consultant who said, you know, if you are
Speaker 3: running a governor's race, he was speaking of a specific state,
Speaker 3: but I think it's broader than that. And you're a
Speaker 3: Republican or a Democrat, you have to be you can't
Speaker 3: really be for AI data centers, or you have to
Speaker 3: be demanding you know, a new uh, a new policy
Speaker 3: on how how the power gets done or how you
Speaker 3: know it works.
Speaker 1: Man, that's funny you mentioned that for me, for me
Speaker 1: to get behind a politician, state level politician, if their
Speaker 1: if their deal was, if they're sort of if their
Speaker 1: take on it was I'm going to do everything in
Speaker 1: my power to bring data centers to our state.
Speaker 2: In my mind, they're out.
Speaker 1: Yeah, it doesn't need to be that they're going to
Speaker 1: do everything in their power to prevent it. But they
Speaker 1: would have to like articulate late a level of skepticism
Speaker 1: and a level of negotiating prowess about how this was
Speaker 1: going to go down, and then if it happens, it's
Speaker 1: going to be good for us, Like I would have
Speaker 1: to hear it, so it doesn't surprise me to hear
Speaker 1: that just across the country. You have to be like
Speaker 1: a I don't know what the best word for it.
Speaker 1: You have to be like maybe at least a data
Speaker 1: center skeptic, you know, because really the thing that like
Speaker 1: the thing that makes me pay attention is is And
Speaker 1: it sounds trite, like I don't want to look at it.
Speaker 2: Yeah, I don't want to look at it. You know.
Speaker 2: When I look out, I like to see things.
Speaker 1: Like like green, how God made it, wildlife, habitat you
Speaker 1: know what I mean, Like like I don't like to
Speaker 1: I don't want to look out and see it.
Speaker 2: And so it would take a lot and there's a
Speaker 2: sense that like.
Speaker 1: There's a sense that even if there's tons of resistance,
Speaker 1: I'm not going to see it in my laptop. Yeah,
Speaker 1: do you follow me? Like there could be like it's
Speaker 1: never gonna be like I'm gonna I'm never gonna try
Speaker 1: to use Google, you know, drive right and realize, ah,
Speaker 1: there's no I just know it'll resolve itself, right. And
Speaker 1: so the resistance part of it, like the resistance the
Speaker 1: data center part of it, never feels real to me, like.
Speaker 2: It's going to cost me.
Speaker 1: Yeah, And so maybe that's a paradigm shift that will
Speaker 1: need to happen where people start seeing like some way
Speaker 1: that like if we resist this all the time, we're
Speaker 1: going to lose out on a global scale, or we're
Speaker 1: gonna lose out on some geopolitical scale. But I think
Speaker 1: that people would have to see it first, because there's
Speaker 1: plenty of people that hate data centers that are probably
Speaker 1: organizing their anti data center activities with cloud computing and.
Speaker 3: Using social media algorithms to elevate I.
Speaker 1: Mean not probably, they definitionally are the anti data center
Speaker 1: movement is driven by data centers. So, but Americans are
Speaker 1: comfortable with that kind of Americans are comfortable with that
Speaker 1: kind of hypocrisy.
Speaker 3: They are, and we we do face you know, some
Speaker 3: some risks you know, in the as we think about
Speaker 3: where the world could go. Uh, you know, we're it
Speaker 3: has become very difficult to build infrastructure in this country,
Speaker 3: and we're in desperate need of a better power grid.
Speaker 3: We're depending on which side of the you know, political
Speaker 3: al you walk down, we're in desperate need of more
Speaker 3: transmission and we're in desperate need of more natural gas pipelines,
Speaker 3: both of which are considered quote linear infrastructure. You know,
Speaker 3: they go through people's land. One is buried, so maybe
Speaker 3: neither one are easy to get through, okay, And and
Speaker 3: so we're at a moment where there's maybe some bipartisan
Speaker 3: discussion about whether we make that easier. Uh. From what
Speaker 3: I've seen of some polls like it, people do find
Speaker 3: like the threat of China and h Ai enabled warfare
Speaker 3: to still be abstract. And you know, if they're like
Speaker 3: in a community where it was pastoral, maybe it was
Speaker 3: pastoral because the factories closed and they you know, just
Speaker 3: became cornfields again. But the if it but they see
Speaker 3: their community first and don't want it to change with
Speaker 3: so much else changing. And so the truth is that
Speaker 3: China has built a grid that's you know, triple our
Speaker 3: size that they've been powering manufacturing all this time that
Speaker 3: we've been doing less manufacturing. Right, So their grid is
Speaker 3: super modern. It is capable of ramping up for whatever
Speaker 3: it may be economic wartime. They've got a grid that
Speaker 3: is quite capable, and they've got a burgeon advanced manufacturing sector.
Speaker 3: You know, we're not talking cheap toys and furniture. We're talking,
Speaker 3: you know, batteries, automated factories. We're talking you know, all
Speaker 3: the different elements of green energy that you know require
Speaker 3: solar panels, but robotics, all of this advanced manufacturing. Now
Speaker 3: there's an effort to bring it back here. Guess what
Speaker 3: that uses more energy and that you know, we'll have
Speaker 3: an additional industrial footprint besides data centers, and they will
Speaker 3: use data centers to run them.
Speaker 2: That's man.
Speaker 1: That's the thing I always think about is I used
Speaker 1: to work on this theory and I never got it
Speaker 1: worked out good. It was kind of like an environmental nationalism,
Speaker 1: and it's it's full of holes. But this environmental nationalism
Speaker 1: I envisioned would be that it's as immature as it
Speaker 1: might sound, would be this idea that our play. Our
Speaker 1: play would be to harness resources like environmental degradation that
Speaker 1: other nations are comfortable doing, and that we would reap
Speaker 1: the benefits of that, but leave our stuff clean in pristine.
Speaker 1: I never got all the details worked out.
Speaker 2: But I was trying to do that.
Speaker 1: We do do that, we do do that, and it
Speaker 1: would we do that to quite a degree, and it
Speaker 1: would be the thing that was brought up all the
Speaker 1: time when people were I was talking about your heart
Speaker 1: burning on your kids to turn the lights off and
Speaker 1: be like all these things in the US around being
Speaker 1: efficient with energy and clean coal and all this, and
Speaker 1: you look, but you're like, but there's still India, still China,
Speaker 1: and be like you can do all this stuff. It
Speaker 1: doesn't matter because there's these things you can't control that
Speaker 1: are out there, and so in some way we benefit
Speaker 1: from it. But I think that if you look at
Speaker 1: and said, like, sure, man, maybe in China they don't
Speaker 1: have a movement of people that has the freedom and
Speaker 1: liberty and autonomy to resist the government, right to resist industry.
Speaker 1: Industry is king, The government is king. Human like citizens
Speaker 1: have no voice. They get steamrolled, their stuff all gets
Speaker 1: turned into data centers right up until the point when
Speaker 1: you were, like up until the point where we're fighting
Speaker 1: a war with China, and if we're fighting a war
Speaker 1: with China, even if it's a proxy war through Taiwan
Speaker 1: or whatever, we're fighting a war with China. And then
Speaker 1: we say to ourselves, man, we shouldn't have just let
Speaker 1: it be that they were doing it all we weren't
Speaker 1: doing it, because now we're at odds, you know, and
Speaker 1: it's it's a like, I don't know, it's a tricky one.
Speaker 1: It's a tricky one when I imagine a you know,
Speaker 1: a natural, beautiful landscape with clean air, clean water and
Speaker 1: like healthy wildlife populations and like, you know, just a
Speaker 1: place you love to be and love to look out.
Speaker 2: Verse is this distant threat.
Speaker 1: That that we're going to get bested by another country
Speaker 1: in a way that is going to ultimately impede our freedom.
Speaker 1: And I think that you have to you know, and
Speaker 1: looking at all this, it's like a it's a really
Speaker 1: complicated gamble everybody.
Speaker 2: Has to make.
Speaker 3: Yeah, and you ask, well, can you know, is there
Speaker 3: a way to do that and have fewer regrets? And so,
Speaker 3: you know, I just wrote about this event I attended
Speaker 3: where a bunch of Silicon Valley founders had had rushed
Speaker 3: to Detroit for you know, the sole purpose of discussing
Speaker 3: and showing how we can reindustrialize America using their technology
Speaker 3: right making factories, uh, you know, an industrial basis work
Speaker 3: differently using technology to make critical medical processing cleaner and
Speaker 3: bringing it here. Because if we're a society that no
Speaker 3: longer makes things and just a certain of this economy
Speaker 3: and we're dependent on the powers that do make things,
Speaker 3: that doesn't leave us in a very good position. And
Speaker 3: but what you love and what we all love wild
Speaker 3: America and the the you know scenery just outside of
Speaker 3: this podcast studio is you know, it is what our
Speaker 3: country makes. Is what makes our country so majestic. And
Speaker 3: so what are some attempts to have industry and progress
Speaker 3: and think more about the natural landscape. And there there
Speaker 3: are models that are starting to emerge that you know,
Speaker 3: make better choices. There are AI data centers that are
Speaker 3: being built in you know, desert prairie and Texas that
Speaker 3: will primarily be run off the grid on solar and
Speaker 3: batteries with some natural gas power to kind of firm
Speaker 3: it when it's not sunny or windy. If there's wind
Speaker 3: and some of you know, it's using some kind of
Speaker 3: flexible gas power that uses less water. Does that mean
Speaker 3: that that's you know, the way you can do it everywhere? No,
Speaker 3: like you need certain certain regions allow you to reimagine
Speaker 3: an industrial factory, like a data center, which really is
Speaker 3: an industrial factory. Other places, you know, you might have water,
Speaker 3: but you know, don't have the power and maybe people
Speaker 3: and to build it. You know, you can't put a
Speaker 3: burden on people. What I found so interesting is like
Speaker 3: we've got the richest industry in the world trying to
Speaker 3: take from the power system. And it's also the case
Speaker 3: that there are people living in dire conditions who can't
Speaker 3: run their dialysis machine or their asthma machine, and how
Speaker 3: they can't afford their power bill. Like we're sharing that
Speaker 3: same you know, uh, Mark Zuckerberg is sharing that system
Speaker 3: with that human being who who needs you know, very
Speaker 3: whose very subsistence depends on being able to afford their
Speaker 3: power bill. So are there some some ways that we
Speaker 3: can all fit ourselves onto the planet together, like you
Speaker 3: you would like to hope so, and you know that
Speaker 3: there will be mistakes along the way. But back to
Speaker 3: your point about the way the country allows us to
Speaker 3: be messy and free and you know, do what we
Speaker 3: want with our property rights. It is a different way
Speaker 3: to arrive at the answer than to have it be
Speaker 3: centrally planned from the Chinese Communist Party and so uh
Speaker 3: and it's the way our countries. This is how it's unfolding.
Speaker 3: It's it's where we have opposition, we have proponents. They're
Speaker 3: both trying to make each other more honest. Hopefully they will.
Speaker 3: That's America, I guess.
Speaker 1: Yeah, yeah, if you had to crystal ball it when
Speaker 1: you look at it's kind of a closing question for
Speaker 1: you if you have to crystal ball when we first
Speaker 1: started time we talk about that twenty thirty projection. Yeah, right,
Speaker 1: will opposition if you crystal ball that will opposition two
Speaker 1: data centers block that projection? Or do you think that
Speaker 1: it's like it's like where there's a will, there's a way,
Speaker 1: Like it'll happen. It'll happen, and it might move. But
Speaker 1: but that's going to happen.
Speaker 3: I think it's going to happen more in certain regions
Speaker 3: of the country than others.
Speaker 2: So we'll shift where it happens, but it will happen.
Speaker 3: We'll shift where it's allowed to happen. There will be
Speaker 3: some of these projects built where people weren't aren't happy
Speaker 3: with it, and I think that could make it a
Speaker 3: less happy outcome. But uh so, I think, you know,
Speaker 3: for example, you'll end up seeing more of it come
Speaker 3: to Texas. You're you're already seeing that now, not because
Speaker 3: Texas is rolling over. Actually Texas is an interesting case
Speaker 3: because they are they have their own grid, their own grid, sheriffs.
Speaker 3: You know, they've been very strict saying here's how we
Speaker 3: want it to happen. And but they've always been more
Speaker 3: of a pro development state. But I think it's going
Speaker 3: to take a few years for the mess and the
Speaker 3: dust of building to clear. And some some places may
Speaker 3: seem like white elephants, and others we may just get
Speaker 3: used to them and then start to take them for granted,
Speaker 3: like we have other aspects of our trial and digital
Speaker 3: life already or our energy supply already, and it's up
Speaker 3: to you know, all the innovators to try to do
Speaker 3: it with a better footprints.
Speaker 1: I oftentimes try to explain to my kids the Y
Speaker 1: two K phenomenon, the panic that wasn't meaning there's things
Speaker 1: that like history is full of this American history stols this.
Speaker 1: There's things like this that come and it's like so shocking. Yeah,
Speaker 1: and then later people look and later generations in the
Speaker 1: previous generations have to explain like, no, you don't understand, man,
Speaker 1: this was like when this happened, this.
Speaker 2: Was a big deal.
Speaker 1: It was a big deal, and they're just say huh right,
Speaker 1: like all the like picture picture what we're going through
Speaker 1: in the forties and fifties with nuclear energy, yeah, and
Speaker 1: nuclear armament.
Speaker 3: Yeah, I'm building the plants in the seventies.
Speaker 1: My kids will like, they will never understand the amount
Speaker 1: of soul searching and the amount of public debate, right
Speaker 1: the careers that were won and lost, the books that
Speaker 1: were written about is this is this the right move?
Speaker 1: Should we go down this path? They would it'll just
Speaker 1: be that that's what That's how the world is.
Speaker 3: Yeah. There were debates like that about you know, coal
Speaker 3: mining and you know the early oil boom. A lot
Speaker 3: of it was up in Pennsylvania and it definitely changed
Speaker 3: the landscape and to some degree benefited the cities closer
Speaker 3: to the coast, but it also you know, created communities
Speaker 3: that of laborers and points of pride that led to
Speaker 3: the steel age.
Speaker 1: And I mentioned that that it's a nimbi fight. It
Speaker 1: almost like accentuates it almost it almost makes it. Why
Speaker 1: it needs to be a nimbi fight would be that
Speaker 1: a citizen says, I accept that it's coming. This is
Speaker 1: all inevitable. The only thing I can really do here
Speaker 1: as I can make it that it's not right there,
Speaker 1: Like that's the only you know, If I can do that,
Speaker 1: if I can make it not across the road from
Speaker 1: my house, I accept the rest, and that'll be my fight, yeah,
Speaker 1: you know, and then it'll probably be how this continues
Speaker 1: to play out.
Speaker 2: So like, I get it, you're all gonna do it,
Speaker 2: don't do it right there? Right?
Speaker 3: And who will be happier? It's an interesting question. The
Speaker 3: ones that don't get any of it, the ones that
Speaker 3: get way too much of it.
Speaker 1: You know.
Speaker 3: It's uh, it comes with trade offs.
Speaker 1: Yeah, that was the thing I was gonna ask you about,
Speaker 1: but then I thought it'd just be such wild speculation.
Speaker 1: Is I was going to ask you about do you
Speaker 1: think that some of these cities, states, whatever that make
Speaker 1: it prohibitive to build data centers that in ten years,
Speaker 1: twenty years, they're going to look at it like how
Speaker 1: Portland when Portland made hard drugs legal and then a
Speaker 1: while later they were like, my god, can you believe
Speaker 1: that's the dumbest thing.
Speaker 2: We've ever done?
Speaker 1: Right that down the road, States cities will be like, dude,
Speaker 1: we shouldn't have driven those people away. Now look at
Speaker 1: all the prosperity these other these other cities are have
Speaker 1: and and we like screwed ourselves and now you know,
Speaker 1: I don't know.
Speaker 3: I think it could be a big contrast between the
Speaker 3: communities that did and the communities that didn't. And I
Speaker 3: think you're gonna have different people either feeling regret or satisfaction.
Speaker 3: Like anyone whose job it is to figure out how
Speaker 3: you're going to you know, fund a municipal budget, it's
Speaker 3: going to say, wow, I really could use that tax revenue.
Speaker 3: Oh yeah, you know, it kicks in. You know, there
Speaker 3: have been tax breaks, don't get me wrong, but you know,
Speaker 3: some of those start to uh, you know, expire, and
Speaker 3: then the property value of these data centers could be enormous.
Speaker 3: If you listen to tech and what they think they
Speaker 3: can make off of them, then you realize that the
Speaker 3: tax based of some of these communities could go up
Speaker 3: hundreds of percent, you know, by multiples, and that pays
Speaker 3: for a lot, including helping communities that are struggling.
Speaker 1: Yeah, the human mind doesn't really work that way though.
Speaker 1: If down the road they're like you're closing a school,
Speaker 1: no one's gonna say like, damn it, we should have
Speaker 1: let the data center come.
Speaker 2: You know.
Speaker 1: People's heads don't.
Speaker 2: Work that way.
Speaker 3: Yeah.
Speaker 2: Well uh And Davis Vaughan, thanks for coming on the show.
Speaker 1: People that want to follow this as it plays out,
Speaker 1: and it's happening so fast, there's so much going on
Speaker 1: all the time. And does a column at the Information
Speaker 1: dot Com every two weeks.
Speaker 3: You have a column every two weeks. It's behind a paywall,
Speaker 3: but it's worth it.
Speaker 2: Yep. I and have really enjoyed your reporting on it.
Speaker 2: I appreciate you coming down.
Speaker 3: And I posted on LinkedIn so you can always get
Speaker 3: the gist of what I'm writing.
Speaker 1: Oh perfect, okay, So Ann Davis Vaughan, last name v
Speaker 1: A U g h N and look forward to.
Speaker 3: Vi A U g h a N.
Speaker 1: What did I just say? Yeah, Oh, I spelled it wrong.
Speaker 2: I'm sorry. Spelled again.
Speaker 3: It's v A U g h a N.
Speaker 2: Oh, I'm sorry. V A U g h a n.
Speaker 1: This is pronounce vaughn though, Okay, I did't screw that
Speaker 1: up right and looked for the uh look for the
Speaker 1: book which will hopefully probably be titled Gigawatt and Against,
Speaker 1: the book about the AI industrial boom and how it
Speaker 1: is reshaping the energy industry, the industrial landscape in the
Speaker 1: American heartland.
Speaker 2: Thanks for coming on.
Speaker 3: Thank you so much for having me.
Speaker 1: Stephen Oh Nate Mason's back there flagging me the TRCP deal.
Speaker 2: Just hang titament. This has nothing to do with ai. H.
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