How Much Water AI Data Centers Actually Use. And What Can Be Done About It. — With Christophe Beck

0:00 How much water and power do AI data centers actually use and how will they handle the incoming spike in demand? Let's talk about it with Kristoff Beck, the CEO of Eolab and a conversation brought to you by EOLAB. And Kristoff is here with us in studio. Kristoff, great to see you. >> Yeah, good to see you as well, Alex. >> So, I'm excited to speak with you because you know what's going on in the AI data center buildout, right?

0:22 We hear all these rumors about how much water and how much power an AI data center actually takes to run and you're actually working in the field and maybe you can help enlighten us in terms of when a company goes to stand up an AI data center. What is the lift of power, water, the consumption that they use and are they this looming environmental disaster that some people claim they are? It's the revolution of our times. AI started in big ways four years ago. It's like electricity suddenly got invented again like 150 years ago when Thomas Edison invented the light bulb. Well, it's happening right now and it's going to happen not in 150 years but in 10 years probably this is the really good side of it. At the same time, you need huge natural resources to your point in order to power AI. We estimate that in the next four or five years by 2030 AI will need the incremental power of the whole of India and the incremental drinking water of the whole of the United States. That's what's at stake. And when we know that we already have a gap in terms of how much water nature can supply versus how much we need, we see that everywhere in New York City, in the US, anywhere around the world. Look at Europe right now. We know we have a problem. We had a problem. we have a bigger problem today. So when we think about the impact on natural resources, it's going to be huge. If we don't do anything, we're going to have a problem. We can dream about AI. Well, the physical infrastructure won't be able to follow.

2:02 And today 60% of the data center projects are delayed mostly because natural resources are not here or because communities are pushing back. >> That's wild. So you said that it's going to take the inc an incremental basically India and power and US and water. That's right. >> And that's per year. >> That's per year. Yes. >> So Okay. >> And it's growing. It's exponential. It's an AI story obviously. It's not linear. It's something that's moving every week.

2:28 It's booming. >> And now you work in water cooling of AI chips within data centers. and so you're going to explain to us a little bit about the solutions here. But I I want to tell you I'm struck a little bit because when you hear folks on the pro AI side talk about the power and the water consumption often times they make it out like it's not going to be a very big deal but then I hear you talk about this incremental India and power and US and water per per year and it seems like actually that is a very big environmental impact. It is a big deal and the fact that so many of those projects are delayed. They're going to happen at some point but not in the time frame that we were all hoping well is an indication that there's an issue.

3:11 it's a natural resources issue but at the same time communities are reacting. And when we talk about communities well it's you and I, it's our neighbors. It's our families. It's our employees. It's not people living on a different planet. obviously people are saying well you're going to take my water. My power bill is going to go up. I don't want to have that data center in my backyard as well. So when we think about the last few years, it's an innovation. AI is something that didn't really exist 5 years ago. So we had to try new ways.

3:41 Well, they're imperfect at the beginning by nature. It's innovation. Well, it's to recognize that the way we've built them so far, the way we've operated them so far, well, was maybe not the ideal why. And once we recognize that, well, we can embrace new solutions. And for us, Azolab, we've built the world's water company. over the last 103 years, actually, we serve three million locations around the world from data centers to fabs to hospitals to schools to breweries, you name it, in 40 different industries. The way we've approached the water challenge has always been, let's do it the same way as nature does. We always use the same water for millions of years. We've always used the same. we can't think too much where it's coming from because ultimately well every water that you've been using today well you'll be reusing it at some point as well. So down the road our approach is to say then let's do the same in a data center in a brewery in a hotel. Let's reuse the water. But that's hard to do because it's effluent water. Obviously nobody wants to reuse effluent water. That's a little bit of a hard thing to fathom.

4:54 obviously, but if you use the right technology, the right data technology as well, well, you can use water in a closed circuit, which is what nature's does through the clouds, the lakes, the rain, and so on. And that's what we're doing with data centers. So, when we're looking at how data centers are being cooled today, well, it's big AC air conditioning in a room where you have a bunch of computers that keep getting hotter and you need to use water in cooling towers in order to cool the air. This is gone. This is not the way we're going to solve it tomorrow. That's why we've developed solutions that we call direct to chip cooling technologies where you can bring a water-based product directly to each chip. You cool it again, you bring it back and you can get power, I mean compute power and at the same time you need no incremental water. So you get in a place where you can get AI at the same time not using water. the way we share it with politicians in our areas for instance to say well the new data center are not going to use more water than a car wash do you have a problem with that maybe not and the discussion changes >> why do the data centers take so much water and power to operate >> it's different reasons so first if we look at the the chips themselves the way the technology works well you need power you need electrons in order to get the system, the logic system work in a chip. And the more of those chips you have, the faster they are, the more data they can ingest, the more power you need to make them compute ultimately. So the higher the compute performance of the chip, the more power you need at the same time. And that's the tricky component. Well, the more heat you generate, you have almost a direct relationship between how much power you use and how much heat you create. So that heat, you need to remove it because if you don't remove it, well, the chip is going to melt. It's going to die. Not good things are going to happen. And when you cool the chip, well, so far we've been using water to cool those chips through a cooling tower like you have in an air conditioning in a normal building that uses a lot of water.

7:18 >> So, they're immersed in the water or >> they're not immersed in the water. So, today the way it is is that you have computer racks in a big room that's air conditioned and your air conditioning unit is connected to a cooling tower like you have in your buildings. Well, that cooling tower uses a lot of water and that's how the water is being used. >> So far, and that's what's changing. But at the same time, Alex, what's important to know is that when you power the chips, well, the second largest user of water in the world behind agriculture is power. So to power the chips, you need water. To cool the chips, you need water. And to make it even more extreme, to produce the chips, you need water because they're produced in ultra pure water.

8:05 >> And so when people talk about the water consumptions that AI data centers use, often times they'll be like, well, they're just using new water and it's coming in and they're they say they're wasting that water and it's just this constant supply of water coming into the data centers. But you said that the plan is to actually use all that and use the amount of a car wash. So how much of the data centers AI data centers that we have today, how much of them are this like more wasteful version? How much of them end up using the amount of a car wash and how do the data centers that are currently, you know, more wasteful end up moving to this more car wash volume version of a data center?

8:49 >> So that's the good news and the bad news. since AI was kind of truly invented four or five years ago most of the data centers that have been built are not using that direct to chip liquid technology. So 10,000 data centers around the world today one is being built roughly every week as we speak. So it's a lot >> mostly air conditioning that they're using to cool >> most of the ones that have been built so far. So we're in a place where 95 97% of the data centers that are existing out there are cooled by air the air conditioning approach. The newer ones are liquid cooled and the very newest ones are liquid cooled in a closed loop circuit that doesn't use any water.

9:41 So >> and that's what you're working on. >> That's what we're working on. So in a way so you can look at the not so good news. Well, 97% of what we've built, well, not that great. Lot of water, a lot of power, not always built at the right places. The very good news is that the latest ones that are being built with the erect to chip circular water cooling technology, well, ultimately are using less water than a car wash.

10:04 >> Okay. So, then talk a little bit about the technology progression from the air conditioning style version of this to what you're going to do. How how does the data center change physically when you go from like let's just you know fill a cooling tower with water, blast it through ACs and hope the chips don't melt to what you're trying to do. >> So the change is quite dramatic. and interestingly enough, Alex, the technology got invented 20 years ago for GPUs, for video games. Interestingly enough, and we know the whole Nvidia stories are based on GPUs more than the CPUs which were related to graphics to games back then because we knew that those chips were super powerful but using a lot of power and creating a lot of heat and needed to have a different way of cooling them. Hence the direct to chip cooling. You fast forward 20 years later, Nvidia and others coming with those super powerful chips, creating a lot of heat that needed to be removed. Air conditioning didn't work anymore. So, the chips would have been melting or disappearing while they were processing the data. So, the idea was to say, okay, if it worked for those GPU, those graphics processing units in the past, could we use them for the latest generation of chips? How does that work? is ultimately with the difference of an air conditioning. Well, you blow cool air on computers. That's not enough anymore.

11:41 What about bringing water directly on a chip? They're not immersed. That could be a solution as well. You just have some technology challenges. Just imagine, so you need to fix the computer. Well, you need to remove all the liquid. You need to dry it. Kind of a crazy thing obviously so to do. So why don't we do something which is more practical where you bring the water directly to the chip through a small radiator. So where you have thin tubes that are coming on top of each of those chips but it can be thousand millions of times in a data center. You get that liquid close to the chip. You bring it back to a cooling distribution unit.

12:21 It's like a big fridge in a way a bit more complicated obviously than that. You reprocess the water. You make sure it's at the right temperature. You make sure that it's clean to get back as well. So to the chip and you keep doing that over and over again. And that's how you get higher performance of the chip and ultimately less water than a car wash. So there could be just a closed circuit of water that's recirculating through this system that goes onto the chips, cools the chips down, when it heats up enough, goes back into the center distribution tank, and then comes back through. That's right. That's the easy part. The only thing is that as we all know as humans, >> water doesn't like to be recycled.

13:04 when you have water that's staying, especially if it's warm temperature, usually. So, the chip operates around 30 C's for whatever reason. We're talking Celsius. for chips, it's roughly what 75 80° something like that. Just imagine water at that temperature staying in that state for a long time. you can think about the pond. You can think about your coffee pot. Well, bad things happen. It turns green because you have biological contamination or you have scaling, the white stuff that you see in your coffee pot as well. You can have corrosion as well. You can have leaks. Water doesn't like to be reused. That's why it's such a big issue. And we need to make sure when the water comes back from the chip, it needs to be standardized again where you remove all bioontamination or risk of scaling and making sure that it's as pure as it can be before it gets back to the chip to get the max performance and that you don't clog anything or create a bigger problem because the whole data center is going to stop. I think something that people don't fully appreciate, at least I didn't know until I started looking into it further, was the water that's used to cool chips needs to be many times pure than even the purest drinking water. It does for the reason we just talked about making sure that nothing bad happens when water is being reused, especially at lukewarm temperature.

14:34 The very interesting thing, Alex, is that we've learned how to treat the most extreme water which is not in health environment or pharma environment when you think that well many of the vaccines unfortunately we went through that so with co so five years ago well you have water with the vaccine coming into your bloodstream. We've learned that the most extreme pure water that's being used on the planet is to produce chips. >> Okay? Because those chips need to be produced in ultra pure water because any impurity that is in the water that comes on the chip kills the chip. And that's how we've learned at Tikolab on how to manage that process which is between thousand or a million times more pure than what you find in a in a drug. So when you think about that type of purity, one of our experts were talking about it. you would take the great lake, let's take Lake Michigan, you would think it's ultra pure water.

15:39 You drop a cube of sugar in Chicago in the lake. That lake is not ultra pure anymore. Just to put it in perspective what it means ultra pure. So that technology well we're going to use it in data centers as well to make sure that it's always the purest water that's getting back so to the chip where you get not only the best cooling performance but at the same time you can drive the performance of the chip as well at the same time and we can talk more about that too.

16:08 >> Hey Kristoff, what happens to the heat? I mean the heat is coming out no matter what. So what do data centers do with that heat coming off of the chips? There's a lot of heat that's coming out when to put it in perspective as well when a company is saying we're going to install one gigab gawatt of compute power out there. One gawatt well generates one gawatt roughly of heat. One gawatt is roughly one nuclear plant. So when a company like one close to us said, "Oh, we're going to build 8 GB 8 gawatt of power out there of compute power. It's eight nuclear plants." Well, you need to cool all that to your point. So what do you do with that heat? well, you have a bunch of options. some are good, some are less good. obviously, one of them, which is the advantage of not using water, well, you bring it back to the air. So you warm up the atmosphere to a certain extent but that doesn't change much from a climate perspective but you don't use any water. A second one it's to warm water that could be used when you have data centers that are being placed in cities for instance which is a new trend that's happening out there. You can use it for district heating or district cooling depending on the physical process that you're using as well. Well, that heat that's being generated by the data center can heat homes or heat any process in a plant.

17:36 And a third one, which is something that we're working on, it's to reuse that heat to produce electricity. And if you produce electricity, well, you reduce the electricity that's needed to power the data center as well, which I think is going to be the future because ultimately you're not only trying so to get zero water being used, but you're trying to minimize the power that's being used as well in the data centers. So, you have many options here, some better than others.

18:03 >> That's pretty cool. So, the heat coming off the water could eventually be transitioned to power that's used to power the data centers. How does that how would that work? >> Because when you think about a data center the power consumption it's roughly 60% of the power is being used to compute and 40% is being used to cool. >> Okay. >> Well cool is not helping any AI application because that's a side a byproduct obviously here if you can move this 40% to 10% well you get 90% of the power being used for the compute which is what we're trying to accomplish. so it's to really drive so the the AI compute performance to your question on how do you transfer the heat into a system that generates electricity. Well that's the core on how electricity is generated in a thermal system today which can be a coal plant.

18:59 It can be a gas power plant. It can be a nuclear plant. Ultimately you heat water, you generate steam, you make a turbine turn which generates electricity and you come back. So, it's to use that heat like you would do in a geothermal facility as well where you bring the heat from the ground. That's what's happening in Yellowstone. We don't have any geothermal plants in Yellowstone. But from a principal perspective, you get the heat out of the earth. Well, you can get the heat out of data data center that ultimately warms a fluid that generates electricity that you can reuse in the data center or elsewhere. You know I want to talk a little bit about what you know you mentioned earlier that this is going to be on an exponential right that the demand for data centers is growing exponentially which tracks what we're seeing about the demand for AI technology and I want to get from your perspective sort of how much demand we're seeing or you're seeing because you're in it in terms of new data center con construction like can you help quantify that for us or give us like a little bit about what you're hearing about like you know there used to be maybe one a year now there's 50 a And it's been changing every year.

20:09 when we started on that journey right before co it was roughly one data center a year. that was being built and today one a week and 50% of them are in the United States, 30% are in China and 20% everywhere else which is kind of an indication as well where the power where the train is going. So from an AI perspective, so that's obviously so generating a lot of new power needs a lot of new water needs and a lot of new space needs which is obviously so creating all the community challenges that we facing well in New York it's pretty clear what's happening right now as well and we can talk about that at the same time well you need to deal with the older data centers we know from all the cheap manufacturers or designers all the famous names that we're familiar with.

21:07 Well, they're coming with new generations. every 10 months roughly now and every 10 months the power is multiplied by 10 and that's becoming 6 months and it's going to be even shorter going forward. Well, you see that those new chips are going to be used in the older data centers to replace the old chips with the new chips. So we're going to have a combination of new data centers with the latest technology and the latest technology being replaced in the older data centers as well. Well, which means that the older data centers will have to be retrofitted with new technology otherwise the power and the water needs are going to explode once again. So it's a combination of new data centers and new chip generation in older data centers.

21:54 >> Yeah. And you mentioned what's going on in New York. Well, we're recording in New York now and there is a moratorum that on data center building that's on its way in New York in New York state. and a lot of that has become has come forward because politicians and community leaders have been worried about the power consumption and the water consumption of these plants >> which is a right worry. I'm totally on the side of innovation of new technology. This AI revolution is an awesome revolution and it's going to add so much to the world.

22:31 But at the same time, the way we've been building data centers the last few years is not the right way for the future. for all the reasons we talked about in terms of water consumption, power consumption, buying piece of lands and saying I'm going to build this data center here. Oh, sorry. I forgot that there was a natural reserve around it for instance. There's no real water around it. We've heard all those stories on social media. I said, well, that can't be the right way. So, I understand why communities are pushing back. understand why our elected officials who are representing our communities ultimately are pushing back while at the same time 900 billions are going to be invested in data center infrastructure in 2026 alone which city which state which community wouldn't like to be part of it by the way we all use it we all have a phone we don't have many of our kids that are saying ourself by the way saying okay I'm not going to use my phone for the weekend for a week because while it's impacting communities and nature. We're going to use it. We love it obviously there, but we need to do it differently. So, it's how do we get both at the same time? The economic revenue that should be true for New York as well, especially this place, this great city at the forefront of innovation, of financing, of great talent, of great people saying we want to have that technology, we want to have that revenue, but let's do it right. So, it's a right discussion. It's a little bit extreme right now. I think that thank we will find ways to make it work for balls.

24:10 >> When you're growing this fast, when you're on exponential, some small things actually have big ripple effects, right? That's kind of where where I'm going with this question, which which is if you're able to take let's say the the power down or the water consumption part of it down from like 40% of the costs of this to 10%. Right? That was the numbers that you shared >> roughly. Yeah. today. So 40% of the power in a data center is used to cool it. Well, that's not exactly the way we want to use the power, >> right? You multiply that by many many times and all of a sudden if you can reduce that, some of those impacts, you know, they they're not as dramatic as some of you know, the fears might make it out to be.

24:48 >> And you get both because you get more compute power because you're going to get to 90% of the power being used to power the chips and not to cool the chips. which is not really useful for anything that we're using. in terms of AI and at the same time we can improve the performance of the chips itself. >> Talk about that because the chips perform better when they're cooler. >> It's a big debate right now. So we've all heard as well Nvidia and others on social medias or in technology publications are saying okay we're going to use chips with much warmer water.

25:23 It's this 30 C's to 40 C's to 50 C's. So you need to cool less because you can afford warmer water. I personally am not sure that that's going to stick because at the same time we see that when a chip gets cooled further its performance increases as well at the same time. So I'm just thinking how do we react as humans? which tradeoff are we going to make? the one that is protecting people in nature or the one that's giving us the max compute performance and we'll figure out the people and planet component later. I've been 30 years in that business and one thing I've learned is that humans have a tendency to go for performance first and to figure out the problems later. So >> I would think that in that case that's probably where we going to go and I see it for a company like EOLAB to find ways to get much cooler environment. So for the chips while we do it in a way that's using zero water because of the closed circuit system that we talked about. So it's a big debate this one. I think that the cooler chips are going to prevail. Is a discussion about the sort of sustainability of the power also something that's appropriate here? I mean, if so, we're talking a lot about the water side of things, right? How can you limit water consumption? If you can limit water consumption and build a system in the way that you're building it, then you know you'll consume less power. but there's also sort of the the power side of this thing. How is power generated? So do you have thoughts on that in terms of is there a way to minimize the amount of power or make the power that's delivered to data centers more sustainable than it is being delivered today >> and it's a new challenge Alex because we've been serving a quarter of the power that's generated around the world for a very long time and we could observe that the power needs of the world in the last 20 years has steadily gone down. M >> so as mankind we were looking at power as okay it's not a real big deal because of power efficiency in terms of LED bulbs and all the different technologies that are making most of what we use much more power efficient well ultimately we were going down in terms of power usage okay we've solved the problem right >> that was before AI came obviously so to the party and changed everything. I was with some power companies so lately and was saying, "Okay, we've been flat for 20 years." Interestingly enough, now it's going to go up 5% every single year. Well, 5% is a lot. AI today uses the power equivalent of roughly 50 nuclear plants. Well, we will need 100 by 2030. We won't be able to build 50 nuclear plants in the next 5 years.

28:34 It takes usually between five and 20 years, probably more 20 years to build nuclear plants. Well, that's not going to solve our problem by 2030. obviously, so how do we get there? Well, there's the right way and there's the less right way. The direct way that's being used today is to say we're going to produce our power close to the data centers because I'm not getting it. from the grid. I'm going to bring my power generator close to the data center.

29:04 Well, it can be a diesel engine. It can be a gas turbine. that's one way to produce it. Is it the most efficient, the most environmentally friendly? Well, maybe not. But to the point before, okay, let's go for performance first and figure the environmental problems later. Well, that's a perfect example of where the world is going right now. There's another way which is the way that we're experiencing in our home state of Minnesota. for instance, the state has decided to go 80% carbonf free by 2030. We can debate whether we love it or we don't. This is not a political statement I'm making here, but we're getting to a place where we can build data centers that are not only water neutral, but if they're powered through carbon neutral type of power, well, you get both water neutral and carbon neutral as well at the same time. And I think that's much more the future. The trick is that who is leading the charge in terms of renewable power? Well, that's the Chinese. And there is an interesting topic here on how do we get ahead of that curve as well in a more competitive world >> how today China produces 90% of the solar panels the same with windmills as well because as a western world we decided that's maybe not exactly so for us and we fine if we buy it from the Chinese well we've helped the China industries to get the scale, the critical mass, the performance that we don't have. This is a geopolitical challenge that we have here. So, we will have to build those capabilities hopefully with the latest technologies here in our country in the United States. This is true for Europe as well.

30:57 But let's face it, we're starting at ground zero here. So, for a while, we will still be depending on the Chinese. So, how do we bring it together? Probably in the meantime, we'll need to find some more traditional conventional ways of producing power while we're building capabilities of more renewable in the future that we can end up in a place where we're water neutral, we're carbon neutral, we're building data centers in places where people are okay with it as well and we can keep growing fast because that's not going to stop.

31:28 >> It's kind of interesting. Do you think the demand for all this power and water in AI data centers is just going to force more sustainable >> absolutely >> approaches? So talk a little bit about that like >> it will because interestingly enough as well so there's this whole discussion about the AI bubble as well it's not going to be a straight line to heaven. We know that as well. No invention so has gone straight. >> I don't know. Some people believe it will.

31:53 >> Some people do. Absolutely. If you take a historic view and you look at the next 10 years or 50 years, yeah, it will. well, that's not exactly the way Wall Street is working. It's more quarter by quarter. So that three months that's going to be a little bit more messy than the straight line that we all hoping. But let's face it, is AI going to slow down? Well, if it were to slow down, that would mean that ultimately as all human beings, we would be using less of our apps, less of all the services that we love. We're going to pause using our phones for a long period of time.

32:32 Do we really think that that's going to happen? I have the chance to have great kids as well at home. Well, we were challenged because of too much phone usage than not enough. so humans well we're going to use way more AI going forward and that's going to be true for companies as well because of all the benefits of AI. So demand is going to keep going up and at the same time the performance of the infrastructure of the chips that are being produced well because we want to be better than the Chinese. Well, it's going to keep going up. Well, you add demand and availability of great services. Well, it's going to keep feeding itself. What's that mean?

33:13 for the natural resources. Well, we won't be able to solve that because when we think in terms of water, everything we have is here. There's nothing that's going to come from Mars in term of water. And to put it in perspective, if you were to put all the fresh water in one sphere, in one bubble, do you know, Alex, how big that bubble would be? >> You tell me. >> 35 miles. >> That's it. >> This is bit bigger than Manhattan. in a way just on top of us this is all we've got all we've gotten for millions of years and all we'll have for the millions of years so coming in the future and we know that already before AI we had a gap of 56% between what we needed and what that bubble is going to be able so >> we were 56% in the whole >> before AI >> pre AAI >> prei so with everything we talked about so with the AI needs today well it just made the problem much bigger bigger. But you're right, it's humans being humans.

34:16 We go for performance. We go for the good first and then we try to figure out how to solve it. So to your question, are we going to be pushing for more sustainable solutions? Yes. Whether it's to save the planet or to deal with climate change, whether we believe in it or not is not the question. There will be no AI if we can't reuse the water. There will be no power if we can't use more renewables as well going forward.

34:45 And there will be no data center if we don't have people in community in democratic countries like the United States that are saying yes this is a good thing for me. So we will solve those problems along the way. >> You're looking at the resources that are required to power AI you know straight in the face. you're obviously very familiar with AI technology as well. you know, looking forward, u do you think it's going to be worth it, you know, all these resources that we're putting in and what we're getting out in terms of the LLM and the agents that we're seeing today.

35:19 Is that is that a trade-off that you think is going to be good for the >> I'm convinced will every revolution in the world has been messy? Just the term revolution usually we don't think in terms of just good. but that's why comparing it to the invention of electricity and when we think how it changed the world did we know exactly how it would impact us that Tesla would come on earth 130 or 40 years later.

35:50 by the way, no, we did not know. But how would we live today without electricity, which is in a way it feels like the new tech for the future. Well, yes, Scott invented 150 years ago, depending on how you want to count by the way here. So, we're going to embrace it because we're going to see all the advantage it's creating. You know, in our home state of Minnesota, we're very close to Mayo Clinic for instance, a fantastic institution.

36:20 >> They use a ton of AI. >> They use a ton of AI like many other great institution obviously around the country. The thing that fascinates me the most is when an institution like Mayo Clinic is saying the whole world is coming to Mayo Clinic when you have the most dramatic the most extreme health situation for yourself or in your family. AI will help us to bring mayor expertise around the world. So the world doesn't need to come to Mayo Clinic in order to be saved by the physicians and the expertise and the data that they have on site. The fact that anywhere around the world you can have on your phone a doctor that can help you, a real one or a virtual one that can help you with your health, that can help your family as well. Well, isn't it a great advantage, a great innovation? The same with education. Well, those are advantages that are going to change the world. It's going to make humans better.

37:21 It's going to make life better. This is AI it core. It's worth solving those problems in order to enable the growth of AI. >> Yeah. Okay. I want to end on I want to end asking you to sort of describe two potential futures. One where AI continues. So the constant is AI will continue to progress at its speed, but one where it goes the bad way and causes environmental damage and the other where it goes the good way and actually leads to you know a more sustainable future in terms of energy and water.

37:53 >> So let's start with the bad way so we can end on the good way which is always more fun obviously because I think the future looks looks great. So if we start with the with the bad way, which is a little bit the path we're on right now, by the way, it's where we invest hundreds of billions of dollars in technology and infrastructure that's being delayed. 60% of the data center projects are being delayed as we speak because of lack of resources, natural resources, water and power and or because communities are saying I'm not going to play game because I don't want to have a data center in my backyard. We can force them. We can force communities. This is not the right way. Obviously, we're going to drain the water out of nature. We're going to create environmental challenges. places will dry out. We're gonna have more wildfires. We're gonna have impact on climate. It's going to impact everyone's life. Is that the right way to do it?

38:56 Well, probably not. AI will be limited by physical limitations and emotional community limitations. On the other hand, well, there are other countries around the world that do not care so much about those question. Well, they're going to get that capacity and those capabilities. They're going to get ahead of us just because we didn't care about it the right way. So, we're going to lose it from an environmental perspective, a community perspective. We won't drive the AI power that we're looking for and we're going to give the pass to some of our competitors around the planet. Well, is it the way we want to drive AI? Probably not. And there's a much better way, which is ultimately doing it the right way, which is building an infrastructure that's reusing water forever, that's not using any incremental water. That we use chips that are so performing that they need much less power for the same amount of data than what we used even a year ago.

40:02 that we build data centers in places that are meant for it. With the right infrastructure away from the communities, in places where they can flourish in ways that are good for communities, good for the natural resources, we will enable the AI technology of this country which is at the forefront of invention as well. We have the advantage of having the upsides of AI technology. We produce it in ways that are good for the environment and the communities and we will lead the world as well. It is competition that we all experiencing right now which is a good thing because it feeds innovation.

40:40 We're going to protect people. We're going to protect nature. We're going to keep inventing. We're going to keep generating returns. That's the better way of building data center infrastructure. Let's hope for that good way. >> We do. All right. If people want to learn more about you and Eolab, where do they go? You can go on our website eolab.com. You can come and visit us anywhere we are around the world. or just give me a call.

41:07 >> Okay. I got to come see one of these data centers. >> I'd love to work with you. >> All right, Kristoff. Thank you so much for coming on the show. >> It's been a pleasure. Thank you, Alex. >> All right. Thank you so much for watching and we'll see you next time on Big Technology.