In this episode of Environment Variables, host Chris Adams sits down with Mark Bjornsgaard of Deep Green to explore a transformative approach to data center design and sustainability. Mark shares insights into how Deep Green reimagines traditional data centers by co-locating them in urban areas to provide heat reuse for facilities like swimming pools, district heating systems, and industrial processes. They discuss the challenges of planning and policy, the rise of high-density computing driven by AI, and the potential for data centers to become integral components of community infrastructure. Tune in to learn about the intersection of digital innovation and environmental responsibility, and how new business models can turn waste into opportunity.

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TRANSCRIPT BELOW:

Mark Bjornsgaard: The government does need to legislate. There is just not enough structure and there's not enough impetus for people to do the right thing. But the also, and particularly in the UK, what the government needs to do is planning is a huge, huge hurdle. I never really understood that until we'd be working with Deep Green for, you know, building data centers.

It is breathtaking how Kafka-esque the planning system in the UK is. It's just,

It's beyond insane.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams. Okay, Mark, a few years back, when people were asked what a data center was, if they knew what one was at all, they might talk about some kind of thing, room, cupboard full of a few machines, maybe in a rack inside a unused room inside a building, for example. But these days, in the 2020s, people are more likely to talk about a warehouse full of hyperscale kind of data servers in a building, which is maybe the size of a football field or larger, for example, the kind of things that are run by massive firms like Google, Microsoft and Amazon, for example.

Now, as I understand it, you work with data centers, too, but they can take a rather different shape and interact rather differently with the built environment. So for those who've never heard of Deep Green, or how the stuff you're doing is different, give a kind of brief introduction to like how your approach to like building data centers is and how that has an impact on how it works with the surrounding area, for example, communities.

Mark Bjornsgaard: Yeah. So, as you say, most data centers are built in the middle of nowhere, and the vast majority are built without heat reuse. So the vast majority simply eject the heat that comes out of the computers. Data centers, we know, two to four percent of the world's electricity supply, and computers themselves are incredibly efficient electric heaters.

So 97 percent of the electrons that go into a computer come out as heat. So you've got us as a species, us in a climate emergency, taking two to four percent of the world's electricity supply, converting it into heat, and then ejecting it into the atmosphere, which 10 years ago, that might have sounded kind of plausible or even sort of necessary.

But in a world, as I said, in a climate emergency, that doesn't look so clever. So the difference between Deep Green and every other data center, most other data centers is we are building the data center where the heat can be reused. So very hard to transport heat, but relatively easy to transport electrons to take the data center to where the heat's required.

So that's what we do. We build smaller data centers, co-locate them where heat's required. Now that might be a laundry, it might be a distillery, it might be food production, it might be antibiotic production, it might be a swimming pool, but more often than not, it's what's called a district heating system.

So these large centralized heat networks that through super insulated pipes supply heat to large areas of different cities. That sort of principle, that district heat systems and heat networks, we're not very good at them in the UK specifically, but we are, the government is certainly planning for us to get a lot best them in the years to come.

So, that's where we're anchored. We, you don't build them in the middle of nowhere, you build them where they're required. There's a further, there's a further caveat and a sort of, a kind of context to this, I suppose, if you'd like. Up until the point where AI started to become part of our everyday lives, those normal data centers aren't on very much.

They're only on 20, 30 percent of the time, and they don't actually generate very good waste heat. So you can certainly forgive the great, the good of the data center industry for not necessarily trying too hard to reuse heat in the old world. But in the world that's coming where we've got these incredibly dense racks of NVIDIA and other chips, where, you know, she utilising a massive, huge amount more energy than previously the datasets had.

That, it's at this point where those are on 70, 80 percent of the time, and they're generating an enormous amount of heat, and the heat's relatively high grade. It's not high grade heat as class within, but it's good low grade heat. So at this point, then the ability to reuse heat becomes a real thing. And that's why we exist.

Chris Adams: Ah, I see. Okay, so there's a couple of things I'd like to unpack if I may. So the first thing you said was, okay, so there used to be data centers if they were going to be built in a kind of hyperscale thing. You're looking for kind of cheap land and then that's why they're often kind of miles away and probably maybe near things like say a grid connection or fiber connection or something like that, all right?

So that was like one of the previous approaches, but the downside of that is that, well, you've, you might have all this heat, but no one's able to use it, so you just vent it into the sky, so it's basically wasted in that way. So the other, another way you could do this is you can actually build these, where they kind of interact more, where they're kind of more complementary to the kind of urban fabric, as it were, and then you can use that.

But the thing that we've seen, one of the reasons that's been stopping that before is that essentially the data centers might have generated some heat, but it wasn't enough heat. So, you said low grade, and when you talk about low grade heat, that's like maybe 40 degrees, 50 degrees? Like, maybe you could expand on that, what that might mean, because I think for people who've never heard of the world of heat reuse, they don't know what high grade heat or low grade heat might be or what some of these uses might be, for example.

Mark Bjornsgaard: Yes. Yeah. No. It's so as you say, low grade heat in industrial settings can be as high as a couple of hundred degrees. So when you say a data center is going to be producing heat at 45, 50, 55 degrees, then that doesn't sound very warm at all. That said, 30 percent of all of the economy, 30 percent of all of the industry can use that very low grade heat.

So for example, a swimming pool very reliably loses a degree of temperature every hour. And it only needs to be 30 degrees. So if you've got, if you're trying to push heat from a, from one side of heat exchanger into another, if you've got kind of pool temperature water at 25 degrees, one side of that's the heat exchanger, and you've got, you know, our heat at 55, the other side, then heat flows the right way.

When it comes to district heating systems and heat networks, the old ones, actually, again, they weren't very, it was quite difficult to plug data centers into them because those old heat networks were quite high heat. They needed heat at 80, 90 degrees. So if you were a data center and you said, I'll give you heat at 35 degrees, it really wasn't that useful. Now, fifth generation district heating systems, the ones that we're building in the UK and the ones that are beginning to be built elsewhere in the world, they can use very much lower temperature heat because the buildings themselves are better insulated. So the whole, the kind of what we think of as ecology, industrial ecology, the kind of ecology starts to, to make sense because lots more offtakers can use this relatively low grade heat,

Chris Adams: Ah, I see. And you also said one other thing about, this is kind of one of the kind of flip sides of massively more dense compute. Here's one thing we've spoken about before. People talk about, okay, there is like worry about data centers, basically, or like AI data centers being massively more dense.

Like the examples, I think I saw you share a link on LinkedIn, which kind of blew my mind. Like, some of these new racks from Dell can have like half a megawatt of

Mark Bjornsgaard: half a megawatt per rack.

Chris Adams: and like, I couldn't really kind of picture what that was. I know it's about 30, it's around 30 times minimum, or around 30, more than 30 times what you might have for an enterprise data center rack.

So like, that's quite a lot of energy there. But like, can you maybe just like, what does half a megawatt even look like for most people, because it's really hard to

Mark Bjornsgaard: it's really, yeah, it is, it's really, it's sort of so vague, it's very hard to get your head around, isn't it? So, I always like to think of it in terms of your boiler on your wall at home. So that's going to be about 10 to 20 kilowatts, right? Your boiler at home. So that one Dell rack is, produces 50 times the amount of heat on the basis that on the basis that 97 percent of the electrons that go into it come out as heat.

That 500 kilowatt rack is producing anywhere between 30, 40, 50 times more heat than the boiler on the wall of your house. And so, an unfathomable, you know, amount of kind of heat. Then if you look at it in the context of a normal data center, if you go into a conventional data center now, you might have rack densities of between 7 and 12 kilowatts a rack.

So when you're talking about densities of again, kind of, you know, 20, 30 times. the density of compute in a single space. Now for us, we love that because we have the opposite problem of every other data center. We're space constrained, not power constrained. So if we can go to a swimming pool and we can heat a very large swimming pool with only two racks of gear, like a megawatt of, that for us is amazing because we spend much less money on building a data center, fencing, security, containers, all the other gubbins, fire suppressant systems, all the other gubbins that you'd have around a data center, when you compress them and you squidge them down, you make them much easier to deploy in the fabric of our communities and society. And then you get this really crazy kind of stats where I was in a data center in Sacramento, a couple of weeks ago, and you got this massive data hall,

it's meant to be one and a half megawatts. It is one and a half megawatts of power, but the whole hall is empty. There are just three or four racks just at the end of the hall because those racks are 130 kilowatts a rack. And so they've built a data center. The physical shell of the data center is built for those rack densities, but they don't need all of that space.

So actually what's going on at the moment in the data center industry is we believe is this sort of giant misallocation of capital where people are building data centers in the old way, when they actually should be building them for the world that's emerging, which is this really high dense, these rack densities that look nothing like conventional data centers.

Chris Adams: So you, okay, that's interesting, and I'd like to come back to some of the things you said there about what the implications of massively more dense compute might actually be. But you also said a few things interesting about this idea of saying, you know, community involvement and things like that.

Because one thing that I've never heard anyone else talk about in the data center industry or even the kind of like tech IT industry talk about was this idea of a, borrowing the idea of a social license to operate. This is an idea that people talk about in say fossil fuels and oil majors and stuff like that.

And you said, well, this is one way that we can actually essentially keep that social license to operate by actually offering a much, much more kind of equitable deal with the communities we're kind of trying to integrate with rather than having this kind of like standoffish approach. Maybe you could like talk a little bit more about that, because I don't really hear people saying that much about data centers.

They usually say, "well, you should be grateful because without us, you wouldn't have your cat pics without and and and..." It does feel like it's kind of missing a huge power of why people might push back against data centers or why they even talk about why they, you know, whatever the deal is when someone comes in and says, "Hey, can we build a bunch of digital infrastructure in your part of the world," for example.

Mark Bjornsgaard: Yeah, I mean, as you say, we talk a lot about a social license to operate because, and we believe that in the future, you will get more and more pushback from communities around having data centers in their backyard,

because you've got these huge sheds which are hogging and clogging transmission grids.

So these transmission grids to be built by public money and then their commercial enterprise, yeah, dumps down there and says, "well, I want 100 megawatts" and then suddenly you realize that half the streets in the area can't put in heat pumps because there's no more grid capacity in the substages or they can't have electric cars. So, we think that social license to operate will be increasingly important in the future. No doubt. But the also the other, I guess the other on the other sort of flip side of this is that datacenters don't really employ anyone, right? I think the datacenter industry is a bit naughty when it says, "oh, you know, we're going to build a datacenter, we're going to employ 4,000 people."

It's like, that's actually not true. You might employ 4,000 people while it's being built, but the reality is once a datacenter is up and running, the number of people who have to be employed in the actual vicinity are very low. But if you build a data center and then you say "I'm going to reuse the heat with a aquaculture park or a distillery or a laundry," suddenly then you then produce genuine net new jobs in a local area.

So not only is the kind of the environmental bit of the social license talk very important, we think increasingly data centers are going to be looked on as having to be good citizens in terms of, you know, employment and doing the right thing with the community and we've already seen a lot of this, right?

We've had moratoriums on data centers in the Netherlands and in Ireland and Singapore. We think we're in this sort of grace period in the transition. In the next 3 to 5 years electrons, then the amount, the number of electrons are going to become very constrained. We're not actually yet in the bottleneck, but in the next three to five years, we're going to start going to that period of time where they just genuinely are not enough electrons to go around.

And we are going to have to make genuine choices about what we do with scarce electrons. And at that point, we believe, that if you're a data center and you're not doing the right thing, then, you know, you're the very least your operations going to be severely curtailed. Stroke, you're going to be in the midst of a full scale culture war, which you just don't want to go anywhere near.

Right?

Chris Adams: Okay, so you said a couple of things which I think might be worth exploring or kind of diving into there because a one of the key things I think I'm getting from you is that, yes, you might be able to kind of force some changes through quickly or you might say like, okay, well, I think one of the key things is that we need this transition itself to be sustainable and if you are able to kind of maybe push through some changes now you'll end up with so much pushback that you won't be able to sustain that state of changing as we end up like essentially moving away from fossil fuels a society based on electrification in many cases.

Mark Bjornsgaard: That's exactly. Yeah, exactly. So, yeah, I think what we see is that we see that. We are energy and software folk and we're venture capitalists by trade. We see, we don't see the data center industry as a, we don't take it as sort of face value. What we see is 70 percent of the UK's total energy budget being the heating of spaces.

So what,

we're looking at from the other end of the telescope, we're saying, well, how could we, how can we best, what's the fastest, quickest way of heating all our shops and offices and factories? And the reality is, the quickest, fastest way of doing that is using computers as electric heaters.

The fact that they happen to be there as data centers is almost, you know, that's kind of just a happy circumstance for us. We're solving what we see as a, as the meta problem, if you like. And just seeing what tools and capabilities we have to be able to solve that problem.

Chris Adams: Okay all right so this is actually one thing that you...

Because I think this is the thing that some of us forget about when we just think about IT like okay there's other transition, other changes that need to take place and before we, before you came on to this, I remember I saw you did a talk about these kind of for the wicked problems related to climate.

And I wonder if you might get a kind of maybe kind of expand on some of that because I think it's quite a useful context to help people who are thinking about their role as a technologist. But, okay, like, why would you even care about heat reuse, and why would you care about anything other than just the efficiency of your code directly, rather than this kind of wider, more systemic view, for example?

Mark Bjornsgaard: Yeah. Of course, we are. We all see our worlds in kind of what's in front of us, and that's completely understandable. As you say, we frame heat reuse and the electrification of heat, as you say, in context of what we think of as four wicked problems. So and these wicked problems make out make up roughly about 50 percent of the entire transition.

So if we solve these four problems, then we will be somewhere around 50% of the challenge of the transition take place and those problems are the heating of, of spaces, so all of our homes and offices, the industrial use of heat, so all industrial processes need to be de decarbonized and kind of electrified, and then we think of, controlled environment agriculture

and what's going on with how we grow stuff, the sustainability movement is rapidly kind of moot, sort of casting its eye across agriculture is realizing that actually how we feed 8 billion people on this planet is actually kind of some like 70 to 80 percent of all of our food is intensively farmed and based on fossil fuels.

And then the fourth wicked problem is carbon sequestration. So how do you, actually sequester carbon out of the atmosphere? That is also a problem around heating. If you take those four wicked problems, they can all be somewhat or completely solved with data center heat, with low grade heat on it. And so we're sitting there saying, well, look, if those datacenters are going to be built anyway, if we already need to spend between 10 and 20 percent of our entire

electricity budget for our country on data centers, then all logic says you build those data centers where you can use the electron twice. The electron can do its funky thing in the data center. We can have all that utility. And then so long as you've done in the right way, like we're doing it, you can just pass on 97 percent of that electron in the form of heat for it to then be used in those four wicked problems. So to us, that is, there's sort of a beautiful, immutable logic there, particularly in a world where you haven't got enough electrons. If you had bountiful, you know, fusion, fission, whichever the good nuclear bit is, if you had a bountiful electricity supply, then you might not be that bothered.

But the reality is in the next 10, 20 years, we're going to be so constrained by the amount of electricity that we have, we're going to have to get really good at being as efficient as we can.

Chris Adams: And I suppose it's actually, I mean, in the I mean, I'm calling you from in Germany, where most of our, almost all of our heating is still coming from basically combustion, burning like gas and stuff like that, for example, which is expensive. And even when you look at the UK gas again is one of the, what was the, I think it's the largest source of heating in the UK by quite a long way.

And these are two things which are volatile and where you're exposed to all kinds of changes in prices and things like that. And this is one thing that we probably do need to move away from. So that seems to be one thing like you're kind of, this is one of the approaches that you're looking at doing here, I suppose.

This is one thing I should ask you about then, because we spoke a little bit about this being a thing that we, that is valued and this is like a shift in how the role that digital infrastructure plays in kind of like the wider societal role. We've also spoken about in the UK, there is this goal to get entirely off, essentially have like some as close to as possible as a fossil free grid by 2030, which basically mean getting rid of a bunch of this heating from burning fossil fuels, right? Now that's a really ambitious goal. And like, as an as someone who grew up in London or grew up in the UK, I'm like, "wow, this is really cool."

This is like, I'm really impressed by that kind of ambition. And it's also one thing we've seen where a number of larger providers have basically said, "well this 2030 goal, it was a nice idea, but the moon has moved," to quote president having Brad Smith at Microsoft saying, "Oh, yeah, we were not pushing for 2030 anymore."

And I kind of feel like if there is this goal of 2030 in the UK, for example, and we have very similar goals in other parts of the world. Like what needs to happen at policy level to actually make this possible for the actual data center or the kind of digital infrastructure there because right now, I'm not aware of the kind of support or how policy kind of values this kind of different way of thinking about the role that digital infrastructure plays.

But we have seen with new government, basically in the UK, they do seem to be very keen on having a massive rollout of infrastructure. So. what's the deal here? Is it gonna be, how do we make, how do we square this circle basically?

Mark Bjornsgaard: It's not,

the declaration of data centers as critical infrastructure isn't quite as good news as it looks. So the, so that is that predicated on regulatory capture and if you declare data centers as critical infrastructure, you can then basically run ride roughshod over any local objections.

So the fact that the labor government announced that isn't necessarily a good thing. It's probably the opposite. In Europe, we've got the EED, we've got the European Energy Directive, I think it is, and by an

Energy Efficiency Directive, which is, which effectively says that certainly in Germany by 2028, you won't be able to build a new data center without reusing 20 percent of the heat. So there is a, there is already a, some sort of regulatory framework out there that's saying "you've got to do the right thing.

You've got to have, you've got to use green electrons. You've got to reuse the heat." So that's good. The reality is, as we all know, governments probably have to use carrot and stick. So you probably have to do a little bit more stick and a little bit more carrot. Those people who are being good citizens and reusing heat should get some brown points and should get some economic benefit from that.

And those who aren't, increasingly should be penalised. I mean, now you'd expect us to say that because obviously we're on what we think of as the right side of history. So I think the short answer is the government does need to legislate. There is just not enough structure and there's not enough impetus for people to do the right thing. But the also, particularly in the UK, what the government needs to do is planning is a huge, huge hurdle.

I never really understood that until we'd be working with DeDeep Greenor, you know, building data centers. It is breathtaking how Kafka-esque the planning system in the UK is. It's just,

it's beyond insane. it's crazy. So you've got regulations like, because you're leased of a council on a district heating system means that you only got that lease because you said you'd use green energy.

If you put a data center within the environment of your district heating system, because we've got generators that kick in if, you know, for redundancy and resiliency, that then means that you're in contravention of your lease. So instead of somebody just going, "yeah, that's a shit idea, let's not do that. Put across through that. That's an unfathomably complicated year long process."

We've had to put one pool we're trying to qualify, we've had to resubmit planning seven times. So this is just, I mean it's beyond rank stupidity, it's just a madness in this country, in the UK at least, around, we hate success in this country. We just hate success. This will be the third business that we develop in the UK and then scale in the US because in this country it is, yeah, we just can't get out of our own way.

It's really sad. And, you know, everyone says, "oh, we'll try and change." It's like, it's very simple. It's like, you either want people to do this or you don't. Do you know what I mean? Like no amount of meetings or nice coffees or platitudes or strongly worded emails. Do you know what I mean? Like, it's very fucking simple.

Can I build a data center or not? If I can't, then I can't. You know what I mean? Like it is, yeah. So this country is, it's very difficult to do here. And I suspect in a lot of Europe it is. So we need government to get out of its own way and clear a path for us.

Chris Adams: So you said a couple of things that I think maybe we could just go into a bit more detail before we move on from there. Because you said one of the things was, things like the, there is one like regulation, the energy efficiency directive, which is It's one of the ideally one of the drivers of transparency for organization for people operating digital infrastructure, like they'll, you know, as a result, you know, for you to comply with this, you need to be able to listen information like the carbon intensity of the power, how much your, you know, how clean the power is, for example, how much of it is coming from, say, fossil fuels, how much water you're using and things like this.

And presumably, like, these are some of the metrics that you might be able to kind of look good on, as it were, or this kind of way of building infrastructure might look a bit better, for example, like, if you're reusing some of the heat, I suppose, then does that have an implication on maybe how much water might be used, for example, and things like that?

Mark Bjornsgaard: Yes. And you've got to be very careful that it's not whack a mole that you don't, you know, you don't drop your PUE, but then you raise your, so you use evaporative cooling, you might drop your PUE or your, the energy use, you know, the Power Utilization Effectiveness of your data center, but then you massively increase the amount of water you use.

So there is a balance. There is a balance to be struck across all of these metrics. That's why there isn't one perfect kind of measure, if you like. Certainly in our case, we don't use any water, so the way that we cool, the way that the direct chip cooling and, the types of cooling we use, we don't use any water and, you know, there really isn't, as far as I understand, and I'm not an expert in terms of a techie expert in this area, but, really using water is a question of just how much margin you're prepared to sacrifice, you know, it is perfectly possible to cool the data center without using any water.

It's just you make a small amount more money on each data center if you use water and people again, the great and good of the data center industry are always be good environmental citizens. They could choose to use no water and just spend a little bit and make a little bit less money. Okay.

Chris Adams: You, ah, so you said something quite interesting there about how So you're using essentially liquid cooling as one way we can, as I understand it, liquid cooling in cars is way more efficient than air cooling in cars, which is why we've moved over. Presumably it's the same kind of idea here. So that's, that would result in a more efficient system that you'd be looking at using here.

Okay. And that, okay. That helps me understand how that might actually fit into heating a swimming pool or something like that. So if you've got an efficient way to move the heat from one place. to another place and like the whole point about you know people use water for heat storage and stuff like that it makes total sense I can see why you'd have like a nice chunky kind of like sink I suppose and if you if these are the things that you're doing then I suppose there's a chance to be more transparent, I suppose, with the kind of figures you're using for this.

So this might be, okay, that's, okay, that's interesting. All right, so if I could, I'd like to ask you a little bit about this AI question, because the approach you're describing here, of having lots and lots of distributed, having series of smaller data centers, like, built into the kind of fabric around us, that seems quite a bit different to the massive, centralized, gigascale data center, kind of paradigm that people talk about so I want to ask like if this is, I've always assumed that you need to have massive centralized data centers to do some of the kind of. AI workload stuff because you need to have these things network with each other. The way you're describing it sounds like that might not be the case.

You know, the things not being in the same building might not be the showstopper that people initially thought it was. Could you maybe talk a little bit about this? Because this suggests like a kind of post cloud way of thinking about computing, for example. And I want to ask, like, do you actually need a data, a mega cluster?

Or is there a, an alternative that you're suggesting here?

Mark Bjornsgaard: The truth is at the moment you need the mega clusters. So we, when we think of training large language models, those need to be done at the moment, those mega clusters need generally need to be all in one place. The trouble is, as data centers grow bigger and bigger, and as you build gigawatt data center campuses, and even larger, when we get, when we think of the trillion dollar cluster, the amount of compute we're going to need to, kind of enable artificial general intelligence, I think we're going to need something like 100 gigawatts of power, right?

100 gigawatt data center, which is, now, when you build, start to build data centers in these sizes, You Actually start to have a distributed problem anyway because you physically can't each sort of node running a version of the model has, it's so far away from the other node. You've got a distribution problem almost by default by size.

If that make if that makes any sense. So we've certainly got to be better at networking the architectures around large language models. And, there isn't very much academic research on this, there is a bit. We're doing a lot of work with NVIDIA and Nokia around this. The Chinese, we think, are doing a lot more work around this than other people, which is in itself interesting as we see a race to AGI emerging. So certainly the networking between data centers is going to become increasingly important. See, in the last six months, you've seen Microsoft spending billions laying massive fiber pipes between its AI data centers because it's trying to use these, you know, even 100 megawatt data center needs to be kind of physically clustered with another 100 megawatt data centers.

But that's also all in the world of training. Now, of course, when that, and that's where the models are learning, and that's great, and that's going to go on. The world that will emerge is obviously mostly going to be inference. So when you think of a world of AI in 10 years time, actually 90 percent is going to be inference, 10 percent is going to be training.

So we are, at DeepGreen, we're not necessarily trying to win the large language model, massive cluster game. What we're building is, the compute substrate for the future, where there will need to be thousands of megawatts of smaller data centers, smaller cluster sizes, much closer to where we all live and work.

So we're, this substrate, this compute substrate will be required in the future.

Chris Adams: Okay. All right. So, so basically, what I think you're saying, or what I'm kind of taking away from that, is that it was almost like a typology of different kinds of digital infrastructure that you might think about. So rather than just being one model, which is inherently better than the other, you probably would need to have different setups, depending on the different kinds of roles that you might actually be having.

And it's, you can kind of see people talking a little bit about this with the whole idea of like edge computing, but it sounds like for certain things you do need, you may, there may be a world where you do have big box Walmart-style out of town data centers doing certain things because, and you just, and you may have to accept that there's, you're not able to use some of the waste heat or you may need to like co locate things to use that and like have some kind of clusters and I guess China's, you can see some examples of people co-locating energy generation with industry and things like that.

But then there's this other kind of like other end of the scale, which is a more distributed thing. And that's something that you're looking, that you're looking at building, like, the kind of data centers that might actually integrate with, say, cities and things where they're closer to where it's actually being used.

But the, you're trying to go for a more kind of integrated approach by making as many of the outputs, the waste outputs, something that can be reused by other people for example because presumably there's a cost to like heating a swimming pool like it's non zero if you need to do that and if you've got the heat coming from what you're using then that's something economically benefit that's something that you might write into like currency benefits agreements and things like that.

Mark Bjornsgaard: Yeah. If you think about some of the inference work use cases that are already emerging, whether that's, you know, you integrating, you interfacing or chatting, maybe your kids are talking to a chatbot and they're trying to learn about they've got some visualization, some rendering visualization, which takes a lot of GPU compute.

That will be, those GPUs will be, it is better that they are co-located, or they're located somewhere closer to where the user is, particularly in the US, where they'll see, or other countries, and not just the US, but, you know, across Europe and other large continents, large land masses, you want the compute to be physically closer to people.

So, you know, where they're living and working. So that that is very important. But of course that world is just emerging. So at the, but that said, there are already a, there's already a lot of refining training. There's already a lot of people who are taking the outputs of the very large language models and then applying their own data to them and then refining, training them.

And then there's a whole bunch of other use cases around medical science and fluid dynamics and all the other stuff that the robots are gonna do for us. That world is now, as we know, emerging fast. That's the world that we're really building for smaller compute clusters, much closer to where people live and work.

And then, as you say, then you start to change the economics about how society works. You know, in the UK, we're spending 1.5 billion pounds heating our swimming pools every year. Really, we shouldn't be spending anywhere near that. Because those, pools should be being heated by recaptured heat. If we allow ourselves to build the data center infrastructure in the right way, the interesting thing about the UK particularly and other countries is that there's lots of fiber in the ground.

So when we first started building a data center, we talked about them following the fiber. Now, data centers don't really need to do that. There's plenty of fiber around. You can pretty much build a data center wherever you like. Now you have to, now people are saying they're following the heat, sorry, the power, but the third generation, the third phase of data center development, we see is people following the heat.

So first of all, you went to where the fiber is, then you went to where the power is. that's the era we're in now, but very quickly you're then now going to build data centers where the heat's required.

Chris Adams: i see where there's presumably like someone who like an offtaker who would use that and then be in favor of something being set up in their neighborhood or in as part of their project, they're getting a bit set up. Okay, so you said one thing that was, I think, quite interesting from there about, okay, there's loads of fiber, there's more fiber than we thought, like all this kind of dark fiber from 20 years ago, the last boom and bust, there's people might reuse some of that.

And some of this has, this could feel a little bit kind of academic or maybe not, it might feel a little bit like, "okay, what's happening in the future?" But As I understand it, some of this stuff is like, what if I'm a, if I'm a developer, I think, "oh, this is kind of cool." I like the idea of actually being able to run infrastructure, run kind of the code or run my applications in somewhere like this, in this kind of environment, because I think it's maybe more interesting.

Or, and if I can have the same convenience and same, the same kind of experience as a developer deploying code, as then why, you know, I might try this out. Is it something that people can use? Like, is there like. I mean, if I'm used to, like, deploying things into, like, virtual computers, I mean, virtual private servers or Kubernetes, is there something like that?

How do I actually try out some of this or use some of this stuff, for example?

Mark Bjornsgaard: Yes, it's because we're we are just a dumb datacenter operator. We are making our capacity of our datacenters available. Then that's the physical space in our datacenters for people like Amazon and Microsoft and Google and loads of other people to come and put their kit in our datacenters. So the minute you put your kids in our datacenter, then it will be doing something useful with the heat.

So as you say that there are a few cloud providers who already partnering with our main partner who have been incredibly supportive to us for years is a platform called Civo. So yeah, again, a UK business paying UK tax. If you as a developer want to run, you want a cloud service that is every bit as good as AWS or Google or Amazon or Azure,

and you want it to be green, then just go to Civo. And then you will be, Civo are using our data centers. So you as a developer, you shouldn't have to make any compromises at all, right? You shouldn't have to worry about any of this stuff. This should all be abstracted away. And in time will be where you can just be assured that when you're running code, it's running in the most environmentally, you know, it's being run in the most sustainable way possible. Now, part of the problem with the large clouds is that their reporting, their ESG reporting, their sustainability reporting is pretty shunky, stroke, complete bullshit. So I think that's part of the problem that I think a lot of cloud services at the moment aren't really taking this very seriously.

And what is certainly very hard as a developer or as an end user of a cloud platform to know how green or not your cloud is. The reality is any cloud platform that's claimed to be green just by using green electrons is ignoring 90 percent of the problem, right? 90 percent of the carbon in a data center is in the kit itself.

The scope, what's called scope three, the carbon that has been used to manufacture the computers themselves. So however much you jump up and down and say, "I'm doing really well because I'm buying green electricity or I'm buying" that's pretty much. I mean, it's not

Chris Adams: 10 percent rather than the other,

Mark Bjornsgaard: exactly so really, as, we all get better at this and as reporting becomes better and as greenwashing gets, people start to come down on greenwashing, as developers, as a whole community, we will have much, much better visibility about how green our clouds really are, but the reality is a green cloud, it comes down to the carbon in the compute and what you're doing, what you're doing to mitigate and reduce and remove that carbon.

Chris Adams: Okay. Alright, so maybe this is one thing that, so, there's one thing, there's one project that we work on in the Green Software Foundation that may be relevant for this. There's one project called the Realtime Cloud Project, where there is an effort to basically work out the carbon intensity for on a kind of per hour for every single region that we have.

If this is something that, I mean, it would be wonderful to have groups like Civo or people like that share something like this. Because the whole effort is to have some standardized data sets, some standardized numbers that you can trust and you can optimize for. And if what you've described is basically saying that yeah, running stuff inside infrastructure here is essentially somewhat fungible compared to running in other infrastructure here.

But if the number, if you're able to kind of reflect that in a lower carbon intensity or lower embodied energy or lower water usage then or any of the any other metrics that are available then that feels like a useful thing to actually allow people to be able to do and it sounds like that is something people can do today rather than having to this being a conversation about 2026 or 2027, by the sounds of things.

Mark Bjornsgaard: Well, to be clear, we're still, we're bringing our capacity online now. So we'd be a year in sort of designing since raising the money from Octopus designing building and now getting shovels in the ground and actually getting our data set the first wave of data centers built. So we've not done, we deliberately not said anything about this because we didn't want to be kind of part of the problem.

We want to be very much part of the solution. Whatever we will be reporting next year will be, you know, we'll be holding our hands up saying this is. This is as good as it gets the moment and we're going to improve it. But I think it's incumbent on all of us to be very transparent about that. I think that's it.

No one's trying to be perfect. No one's going to get kind of shot down for not being perfect. I think it's much more about the attitude you bring to it as a business rather than being, you know, "this is the law and I'm telling you it's like this" when we all know that's not true. But I think it's much better to be more tentative about it and say, "look, we don't know everything, but, you know, we think our scope three is this, and we are removing it using these removals."

And if somebody says, "I don't like those removals, I think they're nonsense." And whilst you say, "well, okay, but we are paying, you know, $250 a tonne for that carbon, so they're not complete bullshit." You know what I mean? I think it's in the, in this next phase, it's all about hopefully not giving each other too hard a time, but actually getting a bit more transparency and a bit more kind of clarity on where we are, because only then can we then start chipping away at it, right?

Chris Adams: Yeah. And like in the UK, we have very, clear targets for the very least like 2030 to get there, for example.

Mark Bjornsgaard: Quite, which is incredibly short

Chris Adams: It's very, it's like, it's almost tomorrow, isn't it? Yeah.

Mark Bjornsgaard: I'm so old that the years pass like days these days, but yeah, five years doesn't feel very long at all, frankly. Yeah.

Chris Adams: I could definitely sympathize with that because we are a non profit focusing on a fossil free internet by 2030. So that is very, acute for us as well. All right, Mark, I've really enjoyed chatting with you. And I've learned a bunch from us, like wonder or wandering through the world of digital infrastructure and stuff, we're just coming to the end of the time.

So I want to ask, like, is, I mean, if you,

are there any projects or things you want to kind of point people's attention to, or people, if people want to find out more about the work you're doing, where should people be looking, for example?

Mark Bjornsgaard: Yeah. If you're a developer, go to Civo. They're amazing people. It's an amazing platform, as I said. And the fastest, quickest way of supporting us is by using Civo. Buying Hewlett Packard Enterprise, Hewlett Packard GreenLake AI. So we're landing whenever you buy HPE kit in the UK and hopefully the US, you will have the option to land it in a Deep Green data center now.

So increasingly, developers and businesses can make green choices just by searching out our partners, you almost certainly never come to us directly. You're going to be consuming cloud services by a third party, but asking your cloud service providers to land that kit in our data center is the fastest, quickest way of helping us.

Yeah.

Chris Adams: Brilliant. Well, in that case, I'll speak to other friends to see if there's a way to filter any kind of like cloud providers for heat swimming pool as one of the kind of like features when I'm looking for my cloud computing in future. Mark, this has been fun. I really enjoyed it. Thank you so much for making the time, especially given like getting hit with COVID last week and everything like that.

So once again, thank you again for this and yeah, this is great. Take care of yourself and have a lovely week. All right, Mark.

Mark Bjornsgaard: Thanks very much for having me. Thank you.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.