Tobias Sodoge - NeoCarbon

00:00:01: Welcome to the Rooted in Change podcast.

00:00:05: Hey everyone, my name is Jan and you're listening to the Rooted in Change podcast.

00:00:08: This is Sophie, the European Clean Tech Champions and their solutions to tackle the climate crisis.

00:00:13: Today's guest is Tobias, CEO at Neocarbon.

00:00:16: Neocarbon is a carbon capture company and their technology captures CO² from ambient air using the low-grade waste heat already generated by industrial sites such as data centers.

00:00:26: The captured CO² can then be reused in water operations or converted into fuels.

00:00:30: We'll learn more about how the tech works in just a few minutes.

00:00:33: Welcome to BS.

00:00:35: Hi, Jan.

00:00:35: Thanks a lot for having me.

00:00:38: Super happy to be here and have this conversation.

00:00:42: Yeah, it's a pleasure.

00:00:44: The first question to my guest is always, who are you as a person?

00:00:47: So tell me, what's your background?

00:00:49: Yeah, sure.

00:00:50: So professionally or education wise.

00:00:54: So I'm a mathematician by background, although that feels a very long.

00:00:59: time ago by now.

00:01:01: I studied pure mathematics actually in Zurich at ETH, then Masters in New York at Columbia, and then my PhD in London at UCL.

00:01:15: Never really felt like a mathematician, but yeah, it was clear to me that I kind of wanted to have a broader impact, also not just sit by myself with a pencil and a piece of paper in a room, but speak to people, work with people, make things happen in the real world.

00:01:31: So after that, was working for McKinsey for five and a half years, mostly on topics of the energy transition.

00:01:42: So kind of across the full value chain, renewables.

00:01:47: Which was probably a good training in general, right?

00:01:49: You sort of have that consulting background get exposure to all the different stakeholders industries.

00:01:55: I love the work there and the people.

00:01:57: Yeah, as mentioned, kind of what emerged for me were kind of two things.

00:02:01: One is that I, by working on the energy transition, I really saw a lot kind of across the full value chain in generation, in transmission, and kind of also on the demand side, how, what happens when we bring new technologies into existing value chains?

00:02:17: So what changes when you suddenly have something that, that, you know, comes there?

00:02:22: So that was clear that this kind of interface of existing industries and new technology and also, you know, the interface of technology and business.

00:02:33: So how can you make a new technology also a worthwhile business case was what I wanted to be.

00:02:39: And secondly, kind of that I at some point no longer wanted to be a consultant and say, Hey, you guys should really do this.

00:02:49: But actually say, yeah, we're doing this and kind of build stuff myself.

00:02:53: So yeah, that's it kind of on a high level professionally before a new carbon.

00:03:00: And then on a more personal note, I think sports is extremely important for me, has been all my life, has been kind of a source of renewal and lots of joy.

00:03:14: was very much into everything that had a ball when I was younger.

00:03:17: So field hockey, football, now shifted to things which are more in nature.

00:03:25: So, you know, hiking, climbing, surfing, kite surfing, skittering, you name it.

00:03:34: Full range.

00:03:35: Yeah,

00:03:35: yeah, yeah.

00:03:35: No, but mainly also cycling.

00:03:38: Right.

00:03:38: So, yeah, those are things that I very much enjoy.

00:03:42: and Yeah, that kind of connects a bit to the second part, maybe a bit about myself.

00:03:49: I think I'm very broadly interested and love to kind of just share and create experiences with people that they might otherwise not have or I might not have.

00:03:59: So it can be in nature, it can be playing music as a DJ, it can be cooking together or something like that or going to a theater that moves you.

00:04:07: So, yeah.

00:04:09: Maybe that's

00:04:11: it.

00:04:12: That's a very nice intro.

00:04:13: And maybe that broad range of interests sort of from McKinsey, but also what you just shared about your personal background, I guess, then let you at one point to your carbon.

00:04:24: So maybe tell the listeners what sort of spark that idea to found the company.

00:04:30: And obviously sort of you probably identified a problem.

00:04:32: And I guess the problem is quite quite broad in a sense that we need to draw down emissions and carbon capture is a great source of it.

00:04:39: Yet there are already a number of carbon capture companies out there.

00:04:43: So what's the specific angle that you identified and where does new carbon fit in there?

00:04:48: Yeah, no, great question.

00:04:51: So I think our core belief and I think that as you mentioned that differentiates or is kind of our approach is that we live in a world where We should not, in our opinion, build kind of gigafactories for direct air capture into the middle of nowhere and compete with AI data centers for green electricity to produce carbon credits.

00:05:21: So we are kind of convinced that this is currently definitely not the world in and that also that that's not the right way to go.

00:05:31: Our belief is that there is a lot of industrial infrastructure available.

00:05:37: So those are exactly what you mentioned.

00:05:39: So AI data centers, desalination plans, e-fuels, production sites.

00:05:47: But basically it's every industry that has waste heat of a very low temperature from fifty to a hundred degrees Celsius.

00:05:57: that this is actually a source of energy that we can leverage to draw down carbon.

00:06:04: So I think that's one core belief and that, you know, there is a better source of energy available for our purposes, which is by the name already kind of a waste product at the moment that is just...

00:06:14: Which is otherwise going to waste and no use at all.

00:06:17: Yeah, exactly.

00:06:18: So it's just being vented to the atmosphere.

00:06:21: And then kind of the second conviction that we have is that, you know, In order to maximize the climate impact, we need to have a business case.

00:06:32: And to have a business case, you need to have a customer with an actual problem that generates value for them.

00:06:40: And generating value that is either lowering costs, increasing revenues, or ensuring regulatory compliance.

00:06:49: So kind of this combination of saying, You know we want to create value for our customers and capture carbon.

00:06:58: Together with what what what energy source is abundantly available and kind of unutilized.

00:07:04: I think those are kind of the the two main things.

00:07:07: Right and what sort of?

00:07:09: what sparked that?

00:07:11: I guess invention is sort of.

00:07:12: where did you get that.

00:07:15: Or how did you turn that inside that you were the insides that you just described into the actual technology.

00:07:20: because based on your background you know you described and it's math ultimately that you that you studied and you know.

00:07:29: Yeah,

00:07:30: yeah, no, that's very far from that.

00:07:31: Definitely.

00:07:32: Right.

00:07:32: And normally, sort of when I speak to people on this podcast, they're like, you know, I spent my, I did a bachelor's and a master's in sort of an engineering degree and then worked in a lab afterwards at my PhD in that field.

00:07:44: And I sort of, I found a pattern.

00:07:46: I realized something and that led to the invention to the technology and ultimately they've spent what, ten years or so working on that specific piece of technology.

00:07:54: that doesn't seem to be the case in your field and your history.

00:07:59: So what sort of, what brought you to new carbon in terms of building that hardware company?

00:08:03: When Rene and Sylvain founded new carbon, these two ideas were kind of the starting point.

00:08:11: And so, you know, creating value for customers and capturing carbon using an abundant source of energy that is kind of readily available.

00:08:25: those ideas were at the core and then kind of very strategically and structurally we analyzed what would be a technology to enable.

00:08:35: that went through all the possibilities kind of and came to our approach.

00:08:44: So it was a very kind of structured process coming from these kind of two Yeah, main assumptions or theories of how this should be done.

00:08:54: So it was, I think, very different to what you mentioned, right?

00:08:58: Usually it's exactly listen to the great podcast from a few weeks back on Stockholm Water.

00:09:07: So that is kind of more the classical path, right?

00:09:10: You have a professor that says, yeah, you know, we have this.

00:09:14: And then you work on it on the lab forever and at some point we're ready to go out and found exactly.

00:09:19: you try to scale it and you know put on.

00:09:22: I read an interesting comment about that recently.

00:09:24: There was a sign of, yeah, this is kind of the, you know, German engineering where there's this genius of engineering and then there's a new idea and everything is easy and we work on this forever and then we come out.

00:09:34: Whereas in China, it's exactly the other way around.

00:09:38: People are like saying, okay, let's learn from what is there and let's do exactly that.

00:09:44: Find a business case, make that profitable and then kind of start to innovate from there on from having kind of something.

00:09:52: And I think we're somewhere in the middle, right, where we kind of identified the problem and then looked for a good solution to this specific problem or technology to enable a solution to that.

00:10:03: And that has been kind of the core DNA of us as well, to always look for the right people to help.

00:10:11: And so we kind of found the scientists to work with us on that.

00:10:18: And that could, you know, in the down selection of the technology help and enable and then at some point we found what we believe is a breakthrough.

00:10:26: Right.

00:10:27: And I think it's a very good description of what you know, sort of.

00:10:31: it's a good description of the problem that you that you highlighted there to say, look, there's one way to do this in research and over over years and scale it from well, very small to small to slightly larger.

00:10:45: But not big, right?

00:10:48: And in terms of the climate crisis and the impact of the speed that we need, it's a valid approach, but it's not one that gets us to results fast.

00:10:56: Whereas I guess with the DNA that you pointed towards, I guess you get results faster, because here you focus more from the business of the problem side of things.

00:11:07: And I think that when you initially stated, look, we don't want to compete on the energy, for example, with AI data centers, let's just use a waste product that's already there.

00:11:17: And that's going to be the input stream for our carbon capture technology.

00:11:23: That's a very smart approach instead of sort of building something in the middle of nowhere, as you pointed out.

00:11:28: So I think that's really inspirational, really

00:11:34: forward thinking.

00:11:35: Maybe one thing to add here, I think also that What really is going to be the next value pools of the future, which is something that's also kind of close to my heart, they will be created in collaboration, right?

00:11:51: That means that we will look at complete systems.

00:11:56: So for example, an AI data center and the surrounding industries sector coupling or, you know, a region that has both agriculture and desalination.

00:12:08: or any type of water treatment industry and that we will more holistically look at these kind of complexes and find solutions or those solutions will excel and create the most value.

00:12:22: that kind of look at the whole system and optimize the whole system.

00:12:26: Moving away from, you know, I have a thousand things that work by themselves quite well, but more looking at the broader picture and kind of taking a completed approach, taking everything into account to make the whole system work better, also inter-connectedly.

00:12:44: And you already talked about partners and collaboration now for quite some time.

00:12:51: So maybe tell us a bit more about the applications of your technology, because we mentioned data centers in the intro as well, but maybe give us the broader overview of where and how you draw down carbon emissions.

00:13:04: At the moment, we're one hundred percent focused on data centers, and there is kind of two sides to this.

00:13:13: First of all, data centers have massive problems at the moment to get the electricity that they need and the speed that they need, right?

00:13:21: So you're not only lacking the build out in renewables, but in particular the grid, you know, transformers, switch gear, everything is lagging in The permits and everything so that there's a big problem for them to to get the electricity.

00:13:39: and of course everything that says electricity is also pure pure money for them pure value.

00:13:44: Secondly and that really changed over the last three years but we've really seen it come to life over the last year is.

00:13:55: With the advent of AI, we have much higher cooling requirements, much higher fluctuations, both on a millisecond to an hour scale, which really pose challenges for cooling the data centers.

00:14:12: Where you could get away with just venting some air, almost everybody is now moving to liquid-based cooling systems.

00:14:25: Secondly, so that's kind of the one thing that's the pure operation side of data centers, power usage, efficiency, water usage, efficiency.

00:14:36: On the other side, you have kind of the sustainability angle.

00:14:41: So who's buying carbon credits at the moment?

00:14:43: It's Microsoft, Google, Amazon, and of course a lot of other types that I'm not mentioning, but the biggest buyers are coming from that space.

00:14:54: They do care a lot about sustainability, abide by their sustainability goals.

00:14:59: So for them, CO², of course, is a topic.

00:15:02: Then water is a topic.

00:15:04: And in Europe, we have regulations on, yeah, our requirements on reutilizing waste heat for something.

00:15:15: So, and of course, the Germans were the strictest in implementing this.

00:15:19: Of course.

00:15:20: Yeah.

00:15:22: So from twenty twenty six on ten percent of all waste heat from a data center needs to be reused.

00:15:26: from twenty twenty eight on will be twenty percent.

00:15:29: So there's really these two angles right.

00:15:31: there's a pure kind of customer value case and there's a sustainability angle.

00:15:36: And now what what we do is that we kind of solve all of these problems in a nutshell.

00:15:42: So our system helps reduce the electricity you need for cooling.

00:15:49: It helps you to deal with increased cooling loads by acting kind of as a thermal buffer.

00:15:57: Then, of course, it does capture carbon from the atmosphere.

00:16:00: It does capture water.

00:16:03: And all of this is powered by the waste heat.

00:16:06: So what we really see here is that we kind of have a very complete solution to a lot of the problems that the data centers are facing.

00:16:19: Boom of the AI data centers.

00:16:22: I mean because it feels like you have the perfect solution for the problem that you just described right and that they're experiencing.

00:16:27: So they need a lot more energy.

00:16:30: They need to cool the data centers.

00:16:33: And as they're using energy and building one more data center is the carbon emissions.

00:16:38: Will it are expected to rise which sort of counters their their ambitions.

00:16:42: so they need to draw down those missions and they're actually building those discover markets for for a big part as you described.

00:16:47: so it feels like you have the perfect solution.

00:16:50: there.

00:16:50: are you experiencing that in in business performance as well in business uptake and sort of inbound inquiries and so on.

00:16:56: how does that look.

00:16:58: Yeah so.

00:17:00: We have a lot of conversations with a lot of people from that ecosystem and we definitely get that feedback that this is very exactly kind of what they're looking for.

00:17:11: Of course, nobody in their right mind puts a new technology right onto a smoothly running AI data center.

00:17:20: So there is a lot of kind of education and technical discussions to be had.

00:17:28: And I think what's really important is to go in steps.

00:17:31: So we always say, well, let's do a joint feasibility study, exactly understand what you need, because you can also imagine that a data center in the Nordics is very different than a data center in the Middle East.

00:17:46: Absolutely.

00:17:47: So they have different, and then also either a hyperscater, a scaler, or a... co-locator, they have kind of different requirements, so there's a lot of kind of small variations in this, and this is kind of what we then find out with our customers, and then kind of say, okay, good, so let's pilot this to then kind of show them that it works, also that it has a positive impact on the cooling system and so on and so forth, in order to then say, okay, there is value here.

00:18:25: And now let's take one megawatt of the one hundred that you have and show you what value we can generate to then kind of further scale up.

00:18:34: So the big vision is really for me that in the long term future, we can turn all of these kind of sources of waste heat, so AI data centers and all the others, into solutions that create value and capture carbon.

00:18:51: And in particular, in data centers.

00:18:54: The scale is just so gigantic.

00:18:58: Basically, we can solve a large portion of the five to ten gigatons per year just by capturing carbon from data centers.

00:19:11: So, you know, it's kind of relatively simple math that gets you there.

00:19:18: Yeah by by the growth right so you have a terawatt hour of year per year of growth roughly.

00:19:24: So when you when you think how much you need to optimize the cooling and and capture carbon then you you quickly get to very large numbers.

00:19:32: let's put it

00:19:32: that yeah I can imagine which is I guess quite exciting for you as a company and maybe that's more out of interest.

00:19:39: it feels like that.

00:19:42: use the company has.

00:19:43: I've also made that transformation towards data centers right because it feels like there you have the perfect product market fit before.

00:19:50: I mean I also talked about the e-fuels and in the beginning and so on which makes a whole lot of sense.

00:19:56: I guess it's still part of your business model but not the core focus.

00:19:59: and what you're saying now is look there's this massive potential and it's a market that's just.

00:20:06: exploding right now.

00:20:08: it's growing so fast.

00:20:09: so for us this is sort of.

00:20:11: this is where we need to focus as a relatively small company still need to focus all our resources to get this right and then we could focus all other adjacent markets as well because I would assume there are other industries that where you can apply your technology also.

00:20:23: I mean with low temperature waste heat.

00:20:26: And that's sort of any industrial process, more or less.

00:20:30: But in terms of impact and speed to market, which we talked about before as well, data center seems to be the easiest and fastest and most impactful, I guess, from the outside.

00:20:40: Yeah, absolutely.

00:20:40: So I think there's again, kind of two parts to this answer.

00:20:44: So first of all, kind of, as you say, right there, they have the biggest problem.

00:20:49: There's tremendous growth.

00:20:51: And however, there's also, as you mentioned, very other very relevant industries.

00:20:57: So for example, desalination, right?

00:21:00: So I think what's again, zooming out a bit, right?

00:21:04: So what we always say is like humanity needs infrastructure upgrades.

00:21:09: We can provide them.

00:21:10: So we need compute data centers, right?

00:21:14: So we talked about that, then we will need with increasing climate crisis or accelerating climate crisis.

00:21:22: We will need more drinking water to be made from from seawater.

00:21:26: There is no way around it.

00:21:27: I was recently or last year quite shocked when I heard that the UK is actually building desalination plants.

00:21:36: So yeah, there's definitely a need for drinking water and then of course transportation and this whole aspect of sovereignty.

00:21:46: When you can produce your e-fuels in Denmark, Germany, or wherever you have sufficient renewables from basically air and water, then you are much less dependent on, let's say, geopolitical developments.

00:22:02: So I think those are really the things that we kind of see as a very big picture.

00:22:09: second aspect, I think, and happy to talk more about desalination, why I personally find it extremely exciting and so on.

00:22:18: The second aspect really is what has shifted for us as a company and also for me personally is that, let's say a year ago or two years ago, everybody was like, yeah, but what do you do with a CO-too?

00:22:32: What do you do with a CO-too?

00:22:35: I actually, the more you think about it, you realize so that A is a problem that is solved in some sense.

00:22:43: So I mean, Linde, Ehrlichied and other companies, their business model is basically, I know it from the brewery next door, shout out to our neighbors.

00:22:52: They go to a bigger brewery, they take the CO-II from the brewing process and then put it in a truck and bring it to the other brewery that is close to us.

00:23:03: And they pay a very high price for that.

00:23:05: because of the Reinhard's Geburt, the CO-II can only come from a brewery.

00:23:09: Or you have waterworks where you have very soft water where you bring tens of thousands of tons of CO-II per year to waterworks waterable.

00:23:24: Then you have all the other industries.

00:23:27: you know this when people say yeah but what you do but like once you dive deeper into it, you actually find out that there is a lot of uses.

00:23:36: Somebody once even said carbon is the new gold, so I think that problem is not only solvable but actually is not so much the core problem.

00:23:48: And it links back to what you said before, right?

00:23:50: When you talked about sort of the existing infrastructure that's there, That is true for carbon.

00:23:57: I mean, if you look at sort of all the infrastructure that we have in Europe and globally, you're rightfully pointed out there, companies that just work with gases and that's sort of their core main business model.

00:24:10: So as you're rightfully, yeah, as you're rightfully say, sort of, I think the problem on the issue is more capturing the carbon, what to do with it afterwards is secondary.

00:24:19: There's markets and infrastructure for that.

00:24:21: Yeah,

00:24:21: exactly.

00:24:21: And I think that's really like The core thing and that also kind of part of the bigger vision.

00:24:27: right.

00:24:27: ideally go to a way data center take the waste heat can use some of this you to directly for them on site to improve their operations.

00:24:36: But then maybe there's a desalination plant close by where we can a use it for producing the drinking water and be.

00:24:45: produce building materials from the brine and thereby also you know reduce the environmental impact of their operation.

00:24:52: So this is kind of this holistic picture.

00:24:55: and then maybe you have you know farming or greenhouses close by that need that or there's an e-fuels plant because where there's a data center there's renewable energy and so on and so forth.

00:25:03: So I really see these kind of industrial clusters emerging where I think this overall system gets better through us.

00:25:13: It's more like building blocks almost right like where you provide the very specific solution for The problem that you're best at solving.

00:25:20: and then there's others that come in and you know take the block that you've created and then use it at their input stream again whether it's them for as you said, right?

00:25:29: Yeah, and this is how to see fields and so on.

00:25:30: This

00:25:30: is kind of the thing that I also really enjoy when you kind of you know when when we speak to partners from from any of these industries and you have a lot of smart people in the room and suddenly there's this this magic that everybody brings.

00:25:44: their expertise, their knowledge and their background.

00:25:46: And they all look at the problem slightly differently.

00:25:49: Suddenly you're like, oh, wow, this actually solves this problem and this problem and our problem.

00:25:53: Wow.

00:25:53: So let's do it.

00:25:54: Right.

00:25:54: So I think that's extremely exciting and inspiring to me.

00:25:59: Yeah, I totally get that.

00:26:02: And that I guess leads me to the next question is sort of how far have you come on your journey?

00:26:06: So I mean, new carbon is a couple of years old now and feels like you right again, are at this intersection of data centers, boom, and so on.

00:26:17: So what we say, maybe in toddler ages, so sort of, where are you on this journey?

00:26:22: You started walking, running, or are you able to do all the crazy sport activities that early in the interest of?

00:26:31: where are you in your personal growth journey as a company?

00:26:34: That's a very nice way of phrasing this.

00:26:36: So I'd say we're kind of Starting to walk probably.

00:26:43: So we will, in the next year, do a couple of pilots at data centers to really kind of show the technology.

00:26:55: We kind of went through the, to kind of stay in your image through the kind of toddler aid.

00:27:02: where you kind of crawl around the floor when we kind of had our kind of the very first generation of our technology out.

00:27:08: Also did already pilot that for a couple of months at a partner site to kind of prove the main idea.

00:27:15: So we do have a positive impact on the cooling system.

00:27:18: We do capture CO to capture water and so on.

00:27:20: The underlying

00:27:21: fundamentals work in that place.

00:27:23: Exactly.

00:27:23: So now we're very focused kind of on bringing the the patent technology that we have into a pilot product.

00:27:34: I don't know if that matches your understanding of where we are in this stage, but keep to

00:27:38: hear.

00:27:40: I know, I think it's a good summary.

00:27:43: If I were to say this from the outside, at toddler age, you need to learn a lot in the early phases in order to perfect the small skills, but then it's about sort of Doing this over and over again practicing it and I think this is where you are at this stage that you know.

00:28:02: now it's time to To do the pilots with the data centers at I guess a larger scale to really prove what we discussed earlier the product market fit there and Then I guess the case for you will be very easy to well relatively easy I guess to say look it works.

00:28:18: You know we've proven this on a small scale now.

00:28:20: Let's up it up and do it replicated with all the data centers that you have.

00:28:25: And I guess that just is very repeatable and scalable business for you ultimately.

00:28:29: Yeah, no, no, absolutely right.

00:28:33: I think what's important in general, kind of in the direct air capture and the carbon capture market, I think there has been a big learning and there's currently a big shift towards from staying in the lab forever and then immediately building a gigantic factory.

00:28:50: Yes, to what we call learn cheap and learn fast by building more smaller machines without spending a lot of money on on cupcakes, but really trying to minimize or like be very capital efficient in the sense that you you you learn more from smaller machines and.

00:29:14: the, you know, the scaling and

00:29:16: able to bring this faster to your customers.

00:29:18: Yeah,

00:29:22: absolutely at a lower price and faster.

00:29:25: And yeah, that's again works well with not going to the middle of nowhere and building there something gigantic.

00:29:34: You know, after having started that.

00:29:36: So I think that's that's a conscious choice as well.

00:29:38: to um, you know, goes as you say, like, you know, start walking for get up again, um, to sustain that picture instead of, you know, trying to, uh, I don't know, write the Tour de France right away or something.

00:29:52: But,

00:29:53: and how do you see that market sentiment overall?

00:29:57: Because, you know, the big players ultimately, I guess, shaped that market, created that market in terms of capture was not a thing.

00:30:06: fifteen years ago, maybe sort of on a lab scale but not in terms of Global media attention and global customer attention.

00:30:14: It just didn't it wasn't there.

00:30:16: now it feels like People know of direct air capture know of the principles that you can do suck out carbon out of the atmosphere.

00:30:26: and yet There's what I see sort of when we talk to journalists is a bit of a skepticism that the promises that were put out there We're just not fulfilled in terms of.

00:30:37: and I guess the reporting that we've seen earlier this year was you know do the big Facilities actually fulfill those promises Right now.

00:30:46: I guess the energy demand is higher and they really emissions are higher than the actual.

00:30:52: See you to.

00:30:52: that was removed.

00:30:53: and so this is sort of that.

00:30:54: there's a bit of criticism building up around the the actual tech there.

00:30:58: How do you see that with your potential customer conversations and investors when you talk to them?

00:31:03: What's their take?

00:31:04: No, I think you've quite well summarized that.

00:31:07: And I think there's a good discussion on this topic going on currently that there were very broad promises made.

00:31:17: And you know, this was like, yeah, yeah, we just build this and solve it.

00:31:21: It's like a, I don't know, B to B SAR solution, basically, where this is actually really, really hard material science.

00:31:30: So it's, you know, it's probably closer to fusion than to be to be AI SaaS lead companion.

00:31:38: You know, if you had to put it on a scale.

00:31:40: So I think that it's really important to to manage these expectations both on a kind of customer side and also on an investor side.

00:31:50: I mean, just to, you know, put some data to what I'm saying.

00:31:55: That's basically I think over two million tons of direct air capture carbon credit solds of which one thousand two hundred something like this have been delivered of which nine hundred are from Climeworks.

00:32:07: Right.

00:32:07: So there have been a lot of sales and kind of not that many deliveries yet.

00:32:13: Don't get me wrong, right?

00:32:14: Like I'm hoping.

00:32:17: I guess we all are, you know.

00:32:18: Yeah,

00:32:18: yeah.

00:32:19: Exactly.

00:32:19: Like this, I'm hoping that this really like, you know, goes through the roof.

00:32:24: And that that would

00:32:26: be great for the ecosystem, right?

00:32:27: Like we're all looking for those success stories.

00:32:29: That's exactly the case.

00:32:30: I think just sort of as a younger company and maybe with a second, third generation approach here, learning from what the others have done, I think, and sort of from our end, when we talk to the journalists and receive that skepticism, I think it's important to carve out the need to be open about and say, look, we've learned.

00:32:49: This is the pattern that we've seen.

00:32:50: I think this is what you mentioned before.

00:32:53: We're a lot more capital efficient.

00:32:54: We're fast.

00:32:55: We're not trying to build something for a number of years in the middle of no bear, but we go to where our customers are.

00:33:03: Fast, easy to implement, prove the value, and then we can scale it up.

00:33:06: I think that's just a more sensible approach, maybe also in the economic times that we're currently experiencing, where the money

00:33:11: is,

00:33:12: has a price again and so on.

00:33:15: I think you said it perfectly.

00:33:17: I think that's really also what kind of differentiates us that we have this kind of approach that does rely on this kind of overall view.

00:33:31: Maybe just one thing to add is also I think really important to always manage everyone's expectations.

00:33:37: So both in terms of investors that Don't spend as much time with a problem as you do, but have a great pattern recognition.

00:33:46: And that, you know, this is really deep tech, right?

00:33:50: And people have kind of, I think, not always kind of managed those expectations in the best possible way.

00:33:59: And I think that's kind of what we need to do now, right?

00:34:03: We need to tell them, look, I mean, we can... You know to use that example we can fly to moon we can probably fly to Mars at some point we can recapture rockets we can.

00:34:13: you know we can do a lot of great things as humans as long as you.

00:34:17: Throw enough money and smart people and time on it.

00:34:20: but I think it's important to to really.

00:34:24: Make clear to everyone that this is an extremely hard material science problem.

00:34:31: that.

00:34:32: requires a lot of thinking and trying and learning and that we are convinced is the better way to, you know, learn foster in small things together with partners and customers to make this thing a viable business case and to have a positive impact.

00:34:52: So I think that is really the core and the sentiment that I get is kind of like, yeah.

00:34:59: Yeah, we've we've set this for a long time and suddenly people are like, okay, you know, it's it's maybe not not so stupid.

00:35:06: Yeah.

00:35:08: And then I mean, looking ahead, because you just described very well, sort of a glimpse into the future, right to sort of say, look, it's ultimately a if we just throw enough money and resources that we can basically solve any problem.

00:35:21: So if you could look ahead three to five years, where do you think new carbon will be?

00:35:28: where you as a company, as a team.

00:35:31: Yeah, so three to five years is of course a short time horizon, right?

00:35:38: No.

00:35:39: Given the problem that you're describing, yes.

00:35:41: And you know, others, if you look at AI hyperscalers, I think we just recently celebrated the open AI to TPT anniversary.

00:35:50: And I guess that has changed quite a bit in three years.

00:35:53: No, no, absolutely.

00:35:54: No, no, but that's what I say with managing expectations, right?

00:35:58: I think what we want to do then is kind of have established ourselves as a solution in the data center space that does provide the benefits that I mentioned, having deployed there at multiple styles in a relevant scale, generating value for both us and the customers.

00:36:20: I think that's where we want to go.

00:36:22: And I think then two things will happen.

00:36:24: So first of

00:36:25: all,

00:36:27: It's key to really, as I mentioned, think these systems holistically.

00:36:32: So we haven't talked at all about the technology yet, but kind of the idea is that you plug our system in as an add-on to an existing kind of cooling system.

00:36:42: And then our system does provide all the benefits, but it also learns, right?

00:36:47: It learns.

00:36:48: So, oh, you know, now it's, I don't know, ten and Jan and Toby are.

00:36:54: asking chat GPT questions on a on a Saturday morning about what they could do.

00:36:59: And then there is not so much load.

00:37:01: But then, you know, it's there's a scheduled inference training at night.

00:37:05: And that's when we really need cooling capacities else it will be very expensive for us to provide the the chillers and so on.

00:37:13: So the system will will learn how that works and will also be linked to, you know, people scheduling the training.

00:37:20: So It will be able to learn from that and optimize the overall cooling system.

00:37:26: So that will even generate more value in the long run.

00:37:31: So that's one side, right?

00:37:32: So we will deploy and we will learn about the overall system and make that continuously better, in particular also because we will have machine learning, AI, however you want to call it to do these improvements.

00:37:45: Secondly, I think what people also... you know, there's a lot of talk of, you know, AI enabled material science and so on, which I think will become very relevant in that, that timescale that you mentioned, because at the moment there really is not a lot of data.

00:38:01: Right.

00:38:01: So, I mean, I think Climeworks is now starting to deploy machines everywhere in the world to learn, which is also something that you learn in water treatment, you know, water is not water and air is not air.

00:38:14: You know, the air at a cement plant in the Middle East is very different than the air in, you know, Norway or Germany or Italy, you know, the air in the morning is different than in the evening, like all these kind of things.

00:38:30: So what I think is once we have more data on both kind of the materials that that work as a sorbent that do capture the carbon and about kind of, you know, how the air composition affects these materials, then I think we will kind of we always call them the you know in this gigantic multi-dimensional space in which you need to optimize for the perfect carbon capture material.

00:38:57: Then we will start again enabled by AI to find those islands of happiness where you know there's a gigantic sweet spot.

00:39:06: And those are basically zero-dimensional in this gigantic space.

00:39:11: There are little dots somewhere that you can approach, but often there will be a long walk in the desert, and then you will hit this tiny oasis.

00:39:21: I liked that description and it's great that your math background finally came through as well that we can talk about multiple dimensions towards the end of the podcast.

00:39:31: That's very enjoyable.

00:39:33: And that brings me also to the last question that I have to you, which is, you know, we started with your personal background.

00:39:40: I just mentioned the math and science training there, as well as, I guess, your your love for sports, passion for sports and experiences.

00:39:52: I think it's quite an unusual journey that you have behind you and that you probably have in front of you as well.

00:39:57: So the question that I have is, what is it that keeps you going?

00:40:03: Because there could be other problems that you'd be interested in solving, yet you've chosen this one.

00:40:08: So there must be something extremely exciting about this and we'd love to know what it is.

00:40:13: Yeah, I think... It's the learning.

00:40:18: I've always just enjoyed learning about new things, exposing myself to them, seeing how it makes you feel, what it does to you when you try something new.

00:40:30: So you try meditation and suddenly you're like, okay, wow, what's happening here?

00:40:35: Or when you go into a new kind of industry vertical, then you learn a lot about Yeah, as I mentioned, cooling systems and AI data centers.

00:40:45: that wasn't my pastime exactly when I was fourteen or twenty or twenty five or something.

00:40:50: So this this aspect of of always learning and then looking at complex problems from from a kind of new perspective and contributing something to the solution of that or saying like, ah, look, here's a connection that, you know, We haven't made before, but if we make that connection, then something interesting happens.

00:41:11: So this whole learning about problems and trying to solve them in new ways or making connections that nobody has seen.

00:41:22: Between everything like business, technology, then kind of more... more personal things like you know your view on life or quantum physics and spirituality like all these kind of things where you suddenly see connections from different angles.

00:41:38: this is something that definitely fascinates me and where I think I'm at a great spot to experience at the moment.

00:41:47: and secondly it's quite simply and that has also been kind of a constant in my life is the people and the teams that I am humbled to lead and to work with.

00:41:59: and that's kind of what you cycle for thirty minutes in the grey Berlin in winter and it's raining and snowing and then you get to the office and there's your three colleagues that went through the same journey and then you.

00:42:13: just it's super nice it's motivating and you You share experience with the people, you learn together and you're there for each other and just kind of enjoy the journey and everybody has their specific skills and view and you can learn something from everyone.

00:42:33: We have a very diverse team.

00:42:37: I think at some point we had more nationalities than employees or something almost.

00:42:44: No, that of course doesn't work, but you get the point.

00:42:47: Well, if you give dual nationalities.

00:42:49: Yeah, true.

00:42:49: Actually, I think that's how we got there.

00:42:52: Yeah, but no, I think that's super nice to work with all of the different people with their really unique abilities and their drive.

00:43:03: So I think those are really the key points, the people and the learning.

00:43:07: Yeah,

00:43:08: which I guess the perfect... conditions for you to thrive as a company, right?

00:43:15: If you have the right people and sort of the right environment to grow together, then I guess anything is possible, which I really hope for you.

00:43:24: I guess this is a really high end to Anderson or high note to Anderson, which is, you know, I'm looking forward to seeing the tech deployed everywhere.

00:43:34: It's going to be pretty cool to prove to the world that, you know, modular Direct a capture is as possible.

00:43:43: It works does have an impact.

00:43:45: It's a great business case.

00:43:47: So and you know coming out of Germany and local patriotism.

00:43:50: I'm rooting for you.

00:43:51: So and fingers crossed.

00:43:53: Let's let's do an update in a couple of years.

00:43:55: Maybe the three to five years span and then see how you've come be lovely to see your journey.

00:44:00: So yeah, thank you so much for taking the time today telling us about your your journey your ideas and then fingers crossed that all of this comes true.

00:44:09: No, thank you very, very much for taking the time and for having me.

00:44:12: It's been a great pleasure and yeah, it could go on forever with you, Jan.

00:44:16: So let's find another opportunity.

00:44:20: Thank you.