Technology, Connected - Data Centers Use Water to Cool Air, Not Chips

Episode Date: September 28, 2026

Data centers use water to cool air, not chips. The water chills the air that gets blown across the racks, and that is where it evaporates. Remove the air and you remove most of the water.Simon Jesenko runs Iceotope, which builds cooling with no fans and no air at all. Fifteen to twenty litres of refined oil circulating inside a sealed chassis, touching every component. His point about the headlines: they describe air-cooled facilities, and the industry is moving off them. Once a site runs fully liquid-cooled, he says consumption drops immensely.He explains:- Why direct-to-chip cooling only solves 80 percent of the problem, and what stays hot- What the dielectric liquid actually is, where it comes from, and why Shell and Exxon make it- Why early liquid cooling installs leaked, and what that did to the industry's appetite for risk- Why the power supply unit, not the GPU, is where his technology wins- Why crypto miners proved immersion cooling years before data centersPlease enjoy the show.--Chapters(00:00) Introduction to data center cooling challenges(01:07) Water usage in data centers compared to agriculture and other industries(03:00) Basics of open loop and closed loop cooling systems(04:18) Guest introduction: Simon Jesenko of Isotope(05:02) Misconceptions about data center cooling technology(06:08) Evolution from air cooling to liquid cooling in data centers(07:31) Direct-to-chip cooling technology explained(08:40) Water consumption in traditional vs modern data centers(10:29) Market transition towards fully liquid cooled data centers(12:23) Airflow management and chip-level cooling techniques(13:34) Environmental factors influencing data center placement(15:50) Challenges of integrating liquid cooling into existing hardware(19:02) Future-proofing with system-level liquid cooling(22:02) Immersion cooling history and applications in crypto mining(23:25) What is dielectric liquid and its environmental impact(26:50) Adoption and market opportunities for Isotope’s technology(30:56) Optimizing power distribution with liquid cooling(34:15) Industry trends and next steps in liquid cooling technology(37:24) Capacities and limits of current cooling technologies(40:26) Guest question: How has AI replaced daily activities?--Learn more about Iceotope: https://www.iceotope.com/Thinking on Paper:◼ Choose your own technology adventure: https://www.thinkingonpaper.xyz◼ Running a tech conference? Book us to host: https://www.thinkingonpaper.xyz/tech-conference-host-moderators/◼ Listen on Spotify: https://open.spotify.com/show/00volKqMsQntToeho35W47◼ Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/thinking-on-paper-technology-considered/id1713227258◼ Follow Mark: https://www.linkedin.com/in/markfielding99/◼ Follow Jeremy: https://www.linkedin.com/in/jeremygilbertson/

Disruptors and Curious Minds. Welcome to another episode of Thinking on Paper. My name is Jeremy. This is Mark. We are back in the realm of data centers today. Very controversial topic in a lot of ways, but it's also the infrastructure that powers a lot of the stuff that we do and how we move through the world, not just AI, but all the other stuff.

We've got an interesting guest today. We're going to dive deep into some alternative solutions that provide cooling to IT infrastructure in data centers that kind of make the whole equate equation of data center cooling a little bit more interesting. So I want to start, Mark, if I could, just from the high level and kind of say, all right, what does cooling in data centers look like, right? So water usage and data centers and that sort of thing. I did a little bit of research.

Right now, data centers are kind of a bad guy. Could data centers do things a little bit better? Sure. In number of ways, they are listed as a high water user, right? So I did some research and did some comparatives and actually found a, you know, a lot of the a few more things that use water as much or more than data centers. And it isn't what you would expect, Mark. Do you have any guesses?

Agriculture. It's probably not far off there. I think you're on a right track. So let's level set. So Lawrence Berkeley Labs, Lawrence Berkeley National Labs, pretty reputable data source. Right now has data center water usage at 17.4 billion gallons per year. That was 2023. That's projected to rise to anywhere.

to anywhere from 38 to 73 billion gallons by 2028, Lawrence, Berkeley National Labs. Let's talk about some other usage. Mark, you said agriculture. Cows. That is correct. So cows were brought up too, but let's talk about agriculture. So California almonds, California almonds, 1.5 to 1.8 trillion gallons per year. And this is according to California Water Impact Network, study done in September 2024. Sea went December 2024.

Wow. Alfalfa. Alfalfa. Yeah. Even bigger. Or actually right around the same. It looks like the water usage there. But according to the Pacific Institute shows this water usage for alfalfa as more than almonds.

Beef is up there as well. Golf courses. up there as well. So before we, before I dive, do you have avocados? Because I was, so we've got to remind the listener that this is,

in a week of very doom ridden horrible news about AI, we're bringing the good news today because we've been talking about water sources and water resources, but we actually have a man in a company that our, their aim is to limit and change how water is used in cooling data centers. And it's some good news. But I like how in today's show, We can kind of be positive and great about data centers, but now we've annoyed all the farmers and the golfers.

That's right. Well, someone's always got to be mad. Right before we bring Simon on, I want to talk about just the systems, how cooling systems technically work in a data center. You have, let's just keep it really simple. You have open loop and closed loop systems. Open loop system is basically think of like a shower. When you get in a shower to cool off, cold water comes down, hit your body, goes right out the drain, right? So you're losing the water.

You're losing nearly all the water that's going in the system. You have closed loop systems, which is more like how a radiator or a car works, how a refrigerator works. Cold water comes in, goes around the hot stuff, gets hot, comes back out, and goes in to get recooled. Those are the two kind of systems. We're going to actually going to talk about cooling on the chip level. We're getting down into the IT equipment and not just into the rooms that are housing the IT equipment. So long diatribe, Mark. Who are we talking to today?

Let's get into the weeds and figure this thing out. Our guest today is Simon Gisenko, CEO of Isotope and Isotope are, well, I'll quote their website, precision liquid cooling that solves thermal bottlenecks in AI infrastructure. And we are going to learn more about that today. So Simon, thank you for thinking on paper with us today. And Jeremy's shower analogy, does it work? Yes, definitely it does. Well, first of all, thank you for invite me to the show. Jeremy Mark, pleasure to be here and talk about cooling and talk about the issues the data centers have today, especially when it comes to water consumption.

What do most people get wrong? What did the general public mostly get wrong about the data center story? I would say, you know, the perception of what data centers were before when they were air cooled and the air cooling technology was used is what everyone thinks is going to happen. as this data center crazy rollout is happening is going to continue. But I can tell you there's a lot of technologies that are being introduced into those data centers today that solve a lot of those issues. You know, the two main issues with data centers is energy consumption and water consumption. And if you think about those two issues, you know, there's different technologies being introduced into those data centers to combat those two, I think, very important things when it comes to how people perceive data centers. centers and how they operate. So the new data centers of tomorrow are going to be way more

efficient and build differently than the old data centers having. We started with casting just super basic high level, the types of cooling in general. I mean, I'm not going to go into the difference between air handling units and computer room air conditioners and all of those things. But in general, closed loop, open loop systems. And now we're talking about the IT equipment itself that lives in these racks that lives in these air-conditioned rooms, we're now able to get precision cooling down to the potentially chip level. Some people are out there doing it. You're doing it a little bit differently. Give us a little history about precision cooling and then what your new take on it is. Sure. And I can give you a little bit of history of what sort of liquid cooling is, if you will,

because it's important to capture that. So traditionally, data centers have always been air-cooled, which means a lot of air being blown across and over the equipment to take the heat away from all the hot spots, all the components. And that technology has reached its limits with the AI, if you will, evolution and all the new chips that are being introduced now into the space. So what's happened there as a result is that industry had to move to a different alternative way of cooling that compute. and liquid cooling was the natural shift.

Now, where you look at the, let's say, the components that get hottest today, the focus of the data center world is on the chip itself. That's the hottest component that is in the system today. So the technology that's been introduced into those data center is something that's called a direct-to-chip technology, which is basically a plate that's put on top of the chip, there's copper pites attached to the plate, and there's water, or dielectric liquid floating into the plate and extracts the heat from the chip.

But that means the rest of the components inside of that system are still air-cooled. So there's still an element of air cooling, which is this highly inefficient way of cooling. Now, our technology basically is a system-level technology. So we use a system-level approach. So we cool all the components inside of the system. And we do it a little bit differently to the technology that I just described, which is the direct-to-chip technology, if you will. We basically remove all the fans, all the air components.

There is no air components at all in the system anymore. And we use the electric liquid, which is this highly refined oil that can touch IT and is very efficient in terms of how it captures heat. And that basically liquid gets pushed around with pumps that we design and control around the system and all the components, not just the CPU and the GPU, the hotspots, but also all the other components, memory, storage, etc., and cools the system as a whole.

Now, this is highly, highly efficient when it comes to heat capture, which the current liquid cooling technology direct-to-chip is not. So if you think about it in simple terms, direct-to-chip, which is a technology that's being rolled out today, captures 80% of the problem, our technology captures 100% of the problem

when it comes to cooling. So that direct-to-chip cooling that you spoke about, so the water goes onto the place directed to the chip to cool it down, is when I open a newspaper and I read about the extravagant amount of water that data centers are using, does that refer to that direct-to-chip cooling? Or is there something else that that water usage is referring to? So when GROC or Open AI or Anthropic are building and have built these huge data centers, is that where that water consumption is pointed?

Depends what the references are there. But I would say most of what's written in the papers today about water consumption really reflects to your point earlier. I think Jeremy, when you mentioned the closed and open loop, right, is that open loop system with air, which you have to have cold water inside of the data center to basically be able to blow cold air over the chip. So it's still air-based technology that's being used when this is talked about because that technology really uses huge. amounts of water. When you introduce direct to chip technology and you still have a bit of water there, still have to have a bit of air cooling there in that sort of that technology, but it's much, much more reduced versus the traditional air cool data center where, you know, this usage of water is astronomical. So when you talk about, when you, when you're reading about this today,

the transition is just happening. So a lot of data centers are still air cooled and there are combination of liquid cooled and air cooled. So it's not fully liquid cooled. Once they're fully liquid cooled, that water consumption is going to drop immensely. It's going to drop by a huge amount. As a percentage of the hyper-scalers at the moment, where they are in that transition?

This is early days still, I would say, and the data center roll out. I wouldn't have exact numbers for you. I wouldn't want to speak at the top of my mind on that, really. but I think it's a transition. It's a transition. And it's going from, you think about it also, it's going from changing some parts of the data center

to liquid cooling while still some other parts remain air-cooled. So this is not like, you know, you don't have a lot of data center that are built from the ground up completely liquid-cooled. Right? So it's introducing liquid cooling gradually into those data centers. There's still some parts of compute that is able to run with air cooling.

And, you know, you have to understand that data center ecosystem is very risk-averse. So they would like to use air cooling for as long as they could because they trust the technology. It's been around for many, many years. Introducing water into a data center or liquid into a data center is counterintuitive in a lot of ways because it's sort of, okay, you have IT and liquid that doesn't normally mix, right? So everyone is thinking, I need to do this gradually, slowly, right? So before pushing the bottom on everything, risking my job while doing so, et cetera, right?

So I want to be very, very careful as I introduce liquid cooling into my data center. So it's going sort of gradually is being built up. But there will be data centers completely liquid cooled in the future. So, Mark, just to give you a little bit more of a look into this stuff, kind of from the basic version of it. So think of it as like room-based cooling. So you have like a giant room. that you're trying to cool. And you set up your racks to where the front of the servers

or the front of the IT equipment are facing in one direction and the rear of the IT equipment are facing the other direction. So you have what's called a hot aisle and a cold aisle. So a hot aisle is where the cool air. So the cool aisle is where the cool air gets pushed into the server, sucked into the fans that Simon mentioned, cools the equipment down and exits on the backside in the hot aisle to where the hot air comes.

kind of is and managing the difference between hot aisle and cold aisle is how you get efficiency. But now we're talking about actually bringing that down to the device level, to the chip level that will. And there's like four different ways, I think, under my research that you can do this direct-to-chip or precision liquid cooling. And we can kind of dive into that a little bit. Does that kind of cast how the airflow works? And you're basically putting all this cool air into this giant room, designing it.

hopefully it gets it in the right spot. Works, thank you. You have to have a lot of cold air to be able to extract all the heat from this air-cooled components, right? And that's where the water consumption come in because you need cold water to basically push through the pipes

so you can have that cold air blowing, blowing through. And there's a lot of water that's being evaporated. So you couldn't build them out in Antarctica because then you've got the latency problem or is that just it's not cold enough even that air is not cold enough? Or is it a latency problem?

Well, like, why? There are the environment of one. Yeah, there are data centers that are efficient, that are being built in colder environments, for sure. That is a, that is a benefit. You can use those environments, you know, even Elon Musk has been talking about building data centers in space. You wouldn't have the problem of heating, of overheating in space, right? So there is an element of external temperatures that impacts what kind of a data center you need, for sure. So that could be a positive in those, in those sort of climate, in those climates.

I'm not saying we should build data centers in the Antarctic, Jeremy. Yeah, Phillips already got them going in Leo, so we're in. That's another myth, though, too. When you think about putting data centers in space, like, oh, space is cold, you still have the heat exchange. You still got to get the heat out. And so you've got to put these giant radiators up there too. Still would have to deal with that somehow.

I don't know how we would deal with latency, but I guess that's, you know, I know that they've been sort of thinking about how to do that. as well. Some companies have some interesting ideas that I've read about. But yeah, that's a different problem altogether. I think we're we'll stick to Earth for now. Let's stay on. I'll stay on a firm up for a minute. So all right, well, let's let's talk about, you mentioned risk aversion. And I can definitely echo that, you know, in my time in the space. It's definitely, hey, this is tried and true. It keeps things up. Down time is is death in data centers and the whole nine yards. That's not unique to data center world. That's the

human condition. Potentially. I don't know. That's a whole, we could go philosophical on this point. We, you know, people need to create space for themselves, but that's a whole another. Simon, we're going, we're going hard left. Let me bring it back here.

Bring it back. We're looking at the risk of urgent piece. The way I understand how your stuff works is you don't make servers, you don't make network appliances, you don't make any of that stuff. You have a technology to bring cooling to more precise levels on that equipment. So herein lies the challenge. you have to go to the Cisco's, the HPs, the NVIDias of the world and say, hey, I'm going to weave more infrastructure in on your box to make it better,

but it's got some liquid in it, it's got some stuff in it. That's pretty tough. How do you approach that? And how is that going? It is tough. It is tough because it should shift, right? A shift in the mindset, a shift in the way also this sort of, I would say, this OEMs, ODS operate that we are working with.

Right. And rightfully said what you said, Jeremy is correct. We are basically a liquid cooling technology provider, if you will. We're experts at liquid cooling. We have a special way of how we cool any form of IT, not just servers, but other forms of IT as well. So we need to work with the IT hardware manufacturers designing systems from the ground up with our technology embedded in. That's the whole model that we are pursuing.

So it requires a lot of proof, I guess, in the first. instance, right? So you have to prove that your technology is superior to any other technology that exists and we are being compared to direct-to-chip today as a technology provider. So first of all you need to basically convince the other party that your technology is superior in terms of performance. Because at the end of the day if it's superior in terms of performance, performance is converted into a commercial outcome. We talk about we talk a lot about tokens per watt. If you can let's say safe power that goes into cooling and push that power into compute, you get more tokens per

watt, you generate, let's say, more revenues for the operator. So that is something that's important to do in the first phase. The second phase is convincing the other party that immersion or, if you will, liquid inside of a box, which is what we have, right? we have inside of a closed box, we have liquid floating around the components is reliable, and it can last for years and years, which is what a lot of these operators worry about, is reliability of these new technologies, even with direct-to-chip, for that matter, right? A lot of the initial direct-to-chip deployments have had leaks.

That is something that is a problem. So it is going through them a lot of testing, a lot of work around, you know, the design, the mechanics of how it all works, a lot of work. in terms of testing the data, which then brings them and convinces them that this is the technology and the solution they should go with. And, you know, what's interesting, you asked me about how is this going. So if you ask me that a couple of years ago, I would say, we've been, you know, developing, perfecting this technology that we have today. But we weren't able really to push it into the market at scale. Now the market is coming to us.

we see more and more opportunities for this technology coming to us through the likes of OEMs, ODM, because they know us, because we worked with them in the past on certain, let's say, development R&D projects, just showing them the benefits of our technology. They know what it can do. Now they're saying, oh, can you guys cool this device? We haven't found a better way to cool it. It needs to live in very extreme conditions. It needs to be operational all the time.

It needs to be cooled properly, et cetera, et cetera. and we're seeing opportunities coming our way. So this is now starting to open up more and more, and we see, you know, there is a place for this technology. But I would say in this point that it is something that as a technology play, it's something that's future proof that lives beyond the direct-to-chip technology in the future, what we have. This is a very important point because, you know,

as these operators think about what comes next after direct-to-chip, it will have to be some form of liquid immersion, which means using liquid to basically cool all the components inside of a IT device. So that's where we're heading for sure. So Mark, for context, the industry has been putting IT equipment in liquid for a long time. I remember 10 years ago there were these racks. So normally you have like an 84 inch high rack, you know, 24 by 30. or whatever it is, these were laid instead of standing tall, these were actually laid down and the servers would get dropped into this liquid, which I'm guessing is pretty similar to this, this dielectric liquid that you're doing. And is it all rooted in how transformers, electrical transformers were initially cooled?

Is that the same concept? Is that where the stuff came from? I believe so. You are correct. And the first sort of, if you will, instances of where this liquid cooling way or way of cooling, which is called immersion was successful was in the crypto mining space. That's where the first successes sort of started. And what you've described there, Jeremy, I think you're talking about the big tanks, right?

So this is what we call in our world tank immersion, right? So these were big tanks filled with the electric liquid. You would drop servers inside, cool them, super efficient in terms of cooling. Of course, you have the server inside, then you would lift it up and you would drain it. And they had initial successes. This technology had initial successes in the crypto mining space. And it tried to push itself into the data center space over the years, worked with several hypers and OEMs.

But it changes. The problem with that technology is that it changes the structure of the data center. It's no longer egg-based anymore, right? So suddenly you have these baths that you're introducing in the data center, these tanks that you're introducing into the data center, which means you have to. to completely change the way you maintain the data center, the way you sort of organize yourself, you have to have a crane there that leaves the equipment up, et cetera. So it is quite complex to operate. So it hasn't been successful in terms of large-scale adoption. And our sort of solution

is different from that perspective that it uses the same way of cooling, which is immersing the components into liquid, but we don't use full immersion. We use a small amount of liquid. That's where the precision work comes from, because we precisely target components inside of the system with this same liquid. It's super efficient in terms of heat capture, but it doesn't change the form factor of the device or the structure of the data center. It's still rag-based. So, each individual chassis that has a server, has its own liquid and its own loop that it circulates in. So it is different to what you've just described. And that's where we see sort of, you know, our benefit as well because we

basically don't change the way the operator is used to maintaining and operating a data center. It'd be interesting to do a show on the importance of Bitcoin mining in the development of AI data centers because it was responsible for a lot of the

transition to GPUs. It was used early days in that and here as well. You both keep using the word liquid and then immersing your chips in or if it's precision directed liquid, what is this liquid? How can non-tech people understand what this dialectic...

Dialectric liquid is? Dilectric liquid is. And where has it come from? Think of it as a highly refined oil, which is environmentally safe, human safe, and it's manufactured by all the oil and gas companies of the world. Is it a highly refined oil then? think about it as a highly refined oil because it is a highly refined oil? Yes, it is, it is exactly.

What's it made out of? Well, you have now different versions of it. Oil. Some of it is, yeah. Some of it now it's it's it's it's, it's, it's, it's, it's, it's, it's, it's actually starting to make this sort of oil which is completely sort of natural, which I, you know, I don't know the specifics of it really, uh, not being an expert in this field, but there are there are some now some options of this that are, that are even more environmentally friendly than the, you know,

normal sort of oils that are, you know, that all these companies are making. How much would a, give me a, give me a power, so how much, a 10 gigawatt, is that right, a 10 gigawatt data center, how much would it need? How much oil would it need with our solution? Well, yeah, you're both. Maybe look at it by rack. I would tell you by sort of on a server level. So we use approximately between 15 and 20 liters.

of that oil per server. So then you can multiply by the number of servers you have in the rack, etc., etc. But by chassis, it's around 15 to 20 liters that we would use of this oil. And this oil doesn't leave the chassis, by the way. It's constantly circulating in a loop. And it's taking the temperature away, and it's basically connected with the infrastructure,

the water loop of the infrastructure. The water then takes the temperature from the oil away and into the infrastructure. So that oil is constantly circulating. And we've seen years and years of this oil being operational with no degradation, no issues from the units that we have installed. Here's a question. So if it's kind of an output of like the exons of the world, how does that factor in to like if we were to look at it holistically, not just its use in the data center, the actual use of that as a piece in the equation of things? Yeah, I think you can look at it as, you know, they are the polluters of this world in a way.

And they're giving back some of those credits, if you will, by producing this sort of type of liquid that helps save energy and save water consumption. So it's a, you know, it's a, from their perspective, policy perspective, if you think about it's how many carbon emissions do they save by doing something like this. So it's an important, through all of these fluid vendors that we've talked about, and we've worked with a lot of them, the likes of Shell, Exxon, Petronus, etc. It's important for them to have a positive impact on the environment, considering the bad reputation that they're getting in terms of what they do in principle, right? So for them, this is an important part of their strategy, for sure, introducing those types of liquids,

helping the data centers be more efficient in terms of the consumption of energy and the consumption of water, that is for them also an important part of their sort of ESG, if you will, policy and how they look at things, right? Yeah, so it's not like an extra output over the traditional refining process. It's a totally different, totally different thing. Got it. Okay. All right. So you mentioned the HP thing was a long time ago.

Do you have any more recent examples or could you talk to us about how the adoption is going? Because you have to go to these OEMs. They have to believe in support. And they also have to convince the people that are buying it that it's the right move too. So give us an example of a couple of new ones that you're working with. I can't name names in terms of the OEMs that we're working with because we're under NDA, but I can tell you a couple of examples. So what we found that is that our technology has a benefit in when we looked at the data center,

structure and data center world. And I mentioned before that data centers, when it comes to liquid cooling, are moving into direct to chip technology first, because it's the most comfortable technology, and it's something that they've settled on. But when we looked at the data center and the whole sort of IT that sits inside the data center, we've identified the power architecture, the power rack to be a focus area for us and our technology. And why is that?

Because certain components, certain IT components that sit inside of a power rack, are very complex in terms of cooling, how to cool them. So you can't just literally apply a coal plate on those components. You can't get the benefits of the coal plate as you do with a GPU or a CPU. So we're focusing on the power rack as one segment or one pillar with our technology and more specifically on the in-rack power supply unit. So those are the units that basically distribute the power to the compute. And what we're seeing there is because of the device complexity is we're getting a huge benefit,

using our technology versus direct to chip. And what that's going to do from a business case is it's going to basically unlock that extra power that normal traditional PSUs use when they're air cooled and is going to release that power into compute, which means more dollars per kilowatt for the operator. So it's a very, very good example of where our technology has an important play today. And then we are looking at the other elements of the power rack as well. The battery backup units are one, which we believe have similar issues in terms of how to cool them efficiently or how to cool them with the direct-to-chip technology. So when we are looking at where we play and our technology plays today, it's always comparing ourselves to direct-to-chip.

So where do we believe our technology has a benefit versus direct-to-chip? And this is sort of in the data center, that is the area. that you're focusing on power. And then outside of the data center, and this is becoming more and more apparent and more and more important, is the edge deployments. Edge deployments where people want to do,

want to basically do AI inferencing at the edge, they want to process information at the edge and they need power for more powerful compute. They don't have the infrastructure needed to basically bring that power to the edge is our sweet spot. And then there's other. elements at the edge that we solve for, things like noise, if you want to have compute in the office,

because if it's running and it's air cooled, it's going to be super loud, whereas with our technology is completely silent. If you have a sort of area where you're trying to deploy compute that is very dusty or humid, again, you know, all these air ventilators bring in that dust and humidity and it destroys the, the IT. So again, our solution is completely sealed. is able to operate in those environments. The power piece is interesting, Mark, for this reason, just like in data centers, water's coming in and running through these entire systems, powers coming in and running through these entire systems.

It comes in from a utility, goes through a generator farm, likely. It goes to UPSs. And through all of these things, you have losses. And then the ratio is like how much power the IT stuff is using versus how much power the building itself is using to support the IT system. So you're talking about power distribution, which is down along the chain there. Focusing on the power rack is the idea to make that more efficient so you can actually use more power to power more things. Like talk me through exactly what you're doing to solve at the PDU level.

Correct. It's it's the PSU level. Correct. It's basically to make those more, those components more efficient and use more less power to cool them. and more power can be then distributed to compute. You know, so it's a numbers game. When you look at all the technology that's being deployed today, it's all about speed.

And then the second phase that's going to come in those deployments is going to be efficiency. So this is an efficiency game, right? How do you make the deployment you have as efficient as possible? How can you get as much revenue per kilowatt as you can as an operator, as somebody that has that compute sitting there, and you have the power distribution and everything else connected to it. All the elements matter.

Even if it's a small difference in terms of that power efficiency, it basically accumulates when you look at the full deployment, you know, from a data center perspective quickly, right? So that's what we're looking at. Those small gains equate to big, big numbers when you look at the data center as a whole. So that's the focus for you. Is it removing heat from the PSU or is it actually making? It's removing heat from the PSU but in more efficient way.

So similar to the problem that we talked about earlier, you know, we have PSUs that are being air-cooled today. Those PSUs are absorbing significant amount of energy in order to be air-cooled. So you want to make sure that you don't use that energy for cooling, but you want to distribute it to compute. So we're pulling the fans out? Yeah, correct. Exactly that. You're pulling the fan out. You're putting a pump in using our liquid.

And then you're cooling it and it's very efficient. And you can then transfer that power that you use to cool that device to compute. That's basically the game. My question was part of what you said, Jamie. I had a very basic question that was based on that. Yeah, I was thinking of my computer overheating and cooling it down, make it more efficient by using this. Is there a limit?

So how much more powerful? As the chips get more powerful, they need more cooling. Can this method, does it have a ceiling? We haven't actually, it's a good question. We haven't actually reached that ceiling yet. We've done a lot of tests in terms of the GPUs that are available on the market today and all those tests have passed. So we don't really today know what the ceiling

this technology is. But we believe, you know, it has definitely longevity in this sort of, if you will, future proof in that respect because it has, because it's based on the system as a whole, you know, it's not, you're not just talking about the chip. You can, you can really sort of get the most that you can out of it. Now there is another element to what, to your question that I would like to answer if you allow me to what we've also been developing is, you know, from a system cooling perspective is a hybrid where you have direct to chip technology sitting on the chip and you have our technology for all the rest of the components. And we see that potentially as being also very useful considering where the industry is going,

which is direct to chip first and our technology second. So we have that option as well for the user to go into if they want to. So we have thought about what the next steps of, let's say, the least. liquid cooling sort of curve, development curve is going to be and where the industry is going and how we can, how we can accommodate. Are the power OEMs like the UPS OEMs, the PSU OEMs easier, is it easier to integrate your stuff into that versus trying to integrate it into the IT systems? And if so, why? Well, it's easier, yes. I would say, yes, it is easier to integrate.

I think just the complexity of the IT system of the server, right, is much more complex. If there's many more components, it is much more difficult to, I would say, build up with our technology. Of course, we can do it because we've done it across a number of different platforms on the server side. But the power supply units are more, I would say, similar when it comes to sort of the inside and the components that sit inside, although they can be allocated slightly differently across the PSA. unit, they're much more similar than versus a server. So it is easier to cool. It's easier to adopt and it is easier to cool.

Plus the electrical engineers understand the cooling. 100%. When it comes to electronics and when it comes to different components, the PCB and everything else, it's much easier to do it in those units than it is on a server level. Mark, he should talk to Danny Andrev about the power circuits he's putting up in space. That could be a fun follow-up. Well, there's many links and threads and common commonalities between every show on thinking on paper, Jeremy, as you know.

So, yeah, electronics in space matches this. Maybe our episodes on StarCloud and data centers in space or our moon infrastructure programs, or maybe our quantum computing and that energy consumption and how they are using cooling, there's some very connected ideas to think on. It's the time for the handover question. So every week we ask our guest to leave a question for the next guest and ask them to answer the question from the last guest. And I think you'll like this question from last week's guest,

Nathan Silvernail, former SpaceX engineer who turned his back on the space industry to make wood out of grass. as you do. And his question for you, his question for you, Simon, was, what technology do you see that is antiquated

and that we could absolutely make better if it was not for capitalism or whatever other structure that is propping it up? That's a good question. What technology

And you know what I would say to answer this question? I would say because we're talking about liquid cooling and we're talking about what we have, right, and how it changes the world and how it changes all this sort of the impact it has, I would say, you know, we should be really doubling down on liquid cooling as a technology of the fueling, future, not just for the reasons that I mentioned just now, which is saving on energy, saving on water, saving savings when it comes to, you know, the space that this data centers and all these sort of installations use.

It's also, you know, using it for capturing heat and reusing that heat for other applications like heating homes, heating facilities, etc. This technology really is something that provides so many incremental benefits to our everyday lives that we are maybe not aware of or have not been aware of, that it's something that we simply cannot, I would say, avoid anymore. And I would say this would really needs to be adopted at scale because it has so many secondary benefits on top of the primary ones that I've mentioned before. you know, heat recapture and all this heat that's being generated by these data centers, if you think about it, what a waste, right? What a waste that is just suddenly just absorbed and goes into the ambient and it's not reused for anything else, right? And we could use a lot of that heat and do a lot with it, especially considering where we are

today, where you think about where the world is and how expensive certain things are and how they are moving, right? So I would say, you know, liquid tooling, if I'm a little bit, you know, biased in that answer, is definitely the technology that should be adopted today and should be scaled fully and implemented in full. I'm going to reverse that question for you, Jeremy, and say, what technology are we using today, which isn't as good as an older technology? A technology is that replaced an infinitely better technology. I was thinking of MP3s.

Skateboards. Skateboards. What's we play skateboards? E bikes. Dude, the e-bikes drive me crazy. E-bikes drive me crazy. No one pedals anymore. Why don't we pedal anymore?

I think it's indicative of the world's problem at large that nobody pedals anymore. Actually, I think he might be on to something there. Simon, do you have a question to leave for next week's guest? Sure. I will use a question that I think is relevant in today's day and age. And I would say, which activity in your day-to-day life or action in our day-to-day life has been replaced by AI? And to what extent?

And would you go back? Right. Would you go back to how it was before? Would you go back? That's an interesting part of that question. Go back to peddling. Yeah. Thank you. We will ask it to our next guest.

And if you want to know who our next guest is, then you'll just have to tune in next week. But it's a good one. Thinking on paper. XYZ. Spotify, YouTube, Apple, IHeart Podcast, wherever you're listening, like, subscribe, share it with three friends who need to hear this conversation.

And until next time, be disruptive. Stay curious. Keep thinking on paper.