Velkommen til Lørn.Tech - en læringsdugnad om teknologi og samfunn. Med Silvija Seres og venner.

Silvija Seres: Hello and welcome to a LØRN conversation. My name is Silvija Seres and my guests today are Bryton Shang and Thomas Aas. Bryton is the founder and CEO of a company called Aquabyte. And Thomas is the managing director of Kontali. Welcome.

Thomas Aas: Thank you. Thank you.

Silvija Seres: So we are speaking across the web, but also across the world. I'm based in Oslo, and my understanding is that Thomas is somewhere far north and Bryton is somewhere very, very far west. Is that correct?

Thomas: Yeah, a small town in mid-Norway.

Bryton Shang: Yeah. And I'm in California right now, in Silicon Valley by San Francisco. And I was in Bergen at the beginning of this year and hoping to go back as soon as I can.

Silvija: Very cool. As soon as Corona lets us.

Bryton: Right.

Silvija: Very good. So, guys, I'm just going to say a few words about the series so people know what they're listening to, and then we'll get started. So this is the fifth conversation in the series that LØRN is doing with the NCE Seafood Innovation, which is a national center of expertise, a cluster of a special status in Norway, and it's focusing on the aquaculture and the productivity, but also sustainability related to it. And we have spoken with several people before, both about the data platform called Aqua Cloud and its usage, especially applied to efficiency and the fish welfare and health. And this conversation will be with two very innovative companies that innovate on top of data related to AquaCloud. And we'll hear about those companies in a minute. So with that as a background, I'm going to ask you my first standard question, and it is, could you please tell us who you are and what has made you so? And maybe we'll start with Thomas.

Thomas: Again, I’m the Managing Director of Kontali and just finished my first year. I have a quite broad background with being represented in four different industries. So I've been within the investment banking, the oil service industries, the seafood industry and the software industry. So my interest is to try all kinds of stuff and try to learn and get more skilled. It's very interesting to be a part of the seafood industry now because I can use the background from the software company I worked for previously and I'm very excited to develop this industry to become something better. But formerly, I have a masters of technology. I haven't used it one minute, but I learned how to learn and I'm using that now in Kontali.

Silvija: So I will correct you a little bit on that because I'm a mathematician by trade and on one hand specializing in algorithms and logic. And I haven't used that directly, but indirectly I think we use our understanding of technology all the time. And that's probably exactly the reason why you're able to make all these very efficient market solutions that you're making now. So I just like to ask you very briefly. Well, you didn't actually give me very much to go on in terms of weird hobbies. You say running and cross-country skiing?

Thomas: Weird in Norway? No, no, not at all. Sorry.

Silvija: No, sorry. Go ahead. You can ski?

Thomas: I have a very competitive instinct and I played soccer until I was quite old and I like to win with a team. We are a team and we like competition and competition. So in my spare time, I like running and competing and I like cross-country skiing and competing. But that improves my skills also at work to keep focus and start competing and keep competing.

Silvija: Some uphill runs are longer than others and you just have to keep at it.

Thomas: Yeah. You don't give up. You learn how to not give up because you get very tired. And that's also the case for the companies I've been in. You can't give up. That's also with Kontali, where we have 34 years of experience and we're now doing a growth story that's like Aquabyte. They are just founded. They're starting from scratch. It's as difficult to start and turn around the tanker ship with Kontali with 34 years of experience. 

Silvija: I'm an entrepreneur myself here with LØRN. And to be honest, just your reminder that you just can't give up is very useful even now, today, daily. So I think that's what being an entrepreneur is. And we'll get to you, Bryton, in a second. I have one final question for Thomas about his background, and it's really about the description of Kontali. You described it to me like the fish farming and fisheries Rystad Energy. And actually I'll say two more words about that. Rystad Energy is a company that most Norwegians know as a wonderful company that makes macroeconomic predictions about energy prices and dynamics and how that relates to Kontali.

Thomas: Yeah, and we did that with all respect because I respect what Rystad Energy has built up. So when I say that Kontali is symmetric I mean Rystad is displaying information about energy and oil to everyone, and Kontali is displaying information about the Seafood industry to those who are not a part of the seafood industry. We're giving insight to the seafood industry and the basis for knowledge and decisions for the industry. So that's similar to Rystad Energy but we have quite far to go to reach the level of Rystad, but we're working on it.

Silvija: So decision data industrially. What sort of data are you working on Bryton?

Bryton: We're working on data that's of the fish in the pen based on a camera and using machine learning, be able to understand the weight of the fish, growth of the fish welfare. Sea lice counts, different observable aspects of the fish.

Silvija: Tell us about yourself first.

Bryton: I'm not a Norwegian. I come from the US. I grew up in New York and live in Silicon Valley. I actually came to Norway four years ago when I first started the company. I think it was like the first time I'd come to Europe. Prior to that I have just been in the US working on machine learning and other types of startups. I'm a serial entrepreneur. I had a couple of companies before this as well. I had started a number of companies before this, for example, I had worked in algorithmic trading. I had also started another company in computer vision. Machine learning. 

Silvija: So serial entrepreneur. Very cool. But what on earth made you then go into fish?

Bryton: I had heard about fish farming from. From a friend of mine. And as you talked to, like folks in the industry, everyone keeps talking about Norwegian salmon. And so I just had to go to Norway and I first went to Norway for AquaNor in 2017. And I was just convinced the first time I went there. I think you mentioned Boogie, the biographer, and he took me out to a fish farm the first time I was there and it's just amazing to see how the industry had developed. And then I ended up living in Norway and starting the company.

Silvija: And then you use the weather as an excuse to do more in Silicon Valley.

Bryton: Well, I first visited Norway in the summer, so it's actually quite nice weather. But I think it's the combination of Silicon Valley machine learning expertise combined with Norwegian aquaculture expertise is what makes our company special.

Silvija: I actually think that you're into something really interesting industrially. So I think that when it comes to consumer platforms, it would be really hard to build a world leading thing from Norway. But business to business and especially industrial business to business, I think Norway has an incredible strength there and it's because they are very good at deep tech and they are very good at applying that deep tech to very heavy asset, hard industrial problems. And I guess fish farming is a space that they both have cultural and historical strengths in. And also I understand they are an early mover in terms of infrastructure. And so it's really interesting to see how we could do the best of Silicon Valley and of the Norwegian fjords in this way. 

Bryton: I absolutely agree. And I think in some ways it's actually been easier to start the company in Norway than anywhere else. The reception for innovation was a lot of farmers welcoming to let us try the technology out at the farms. The fact that you even have an innovation cluster, many countries don't even invest in these types of services. And so them helping us to get set up was critical. And I think in Silicon Valley there is this innovation spirit and similar innovation spirit in Norway as well. So I think it's been great to work across the two countries.

Silvija: So both of you are examples of using the AquaCloud platform. Could you please help me understand how it can be useful to you? And where do you see it being applied first? Maybe we can start with Bryton.

Bryton: I think AquaCloud and the initiative overall to be able to have data and be able to use machine learning and A.I. to analyze the data. It really represents the future of fish farming. The fact that you're able to use this data and mine it for insights to understand how sea lice infestations are going to happen or or understand growth and what's typical in the industry, I think is a really important initiative. And I think you could do this on a one by one basis, each company themselves analyzing their own data. But I think the initiative to bring all these types of data together and the power of big data to be able to create new analyses is actually similar to what Kontali is doing by bringing data from the whole industry together. I think you deliver a new level of insight. And so it's great that NCE Seafood AquaCloud has been able to organize this because I think this will then in turn allow other entrepreneurs in the industry to start using this data to start their own businesses and push the industry forward.

Silvija: I want to ask you, Thomas, the same question. But before that, I always mess these conversations up with personal remarks and memories. And about three years ago, I was on a jury for a hackathon in Norway. And it had to do with using public data from different data sets. And one of the companies that almost won was making something I think it was called Save the Cow. And basically they were trying to optimize the supply and demand curve for beef in Norway because apparently the farmers don't get good enough information about supply or overproduction and then too many cows are slaughtered and then you end up with low prices anyway. And so are there a similar dynamics in fish farming? Is there a way to kind of optimize production for future market developments, or is it the other way around? Tell me about the problem you're trying to solve.

Thomas: That's a good point because in all markets, you have to find a balance. You have to produce at the right moment and sell it in the market when you have the highest prices. And to do this, you need to aggregate data from the start on the production side. And on the other side, you need to know where the demand for the products is, what kind of markets are out there. And you also need to know where it is produced and how many fish there are in the sea for the seafood industry. And that's where AquaCloud comes in, because they can tell us how much fish is there and see how much at each time. And we had these initiatives ourselves in 2010 where we established what we call Managua to get together with, among others, Sintef. And our purpose was to try to get a better picture of how much fish is produced and to help the farmers to get a better insight of the stocks available. So for us, AquaCloud, we have to give up because there's a heavy investment to get this in place and aquaculture. They have invested a lot to get there where they are today. And they're not completed yet. They have to compete with more information, more data and more farmers to add. But this is important for us to get a complete picture on the production side. We spend a lot of time gathering data manually through farmers today. And if we can do this to aquaculture, we can spend more time on doing analysis and to show results and given insights and to provide more useful information for the farmers and the market in general.

Silvija: So I've heard about farmers in Africa texting each other and figuring out about tomorrow's fish price on the market, etc.. And what you're trying to do is bring this to a global level, and there's far more automation in this information flow.

Thomas: Yeah, we have quite come quite far on the salmon needs in Norway. If you look at the warm water shrimp, they are left behind compared to what we are in salmon Norway. So even though the markets are similar in size, both in volume and trade. So we have come quite far in Norway, but still we are lagging other industries like the cows and the meats and so on. The meat industry, they are quite further on in mapping stocks.

Silvija: So you need to map the stocks. But I understand also that maybe there are some advantages in doing this for fish farming versus fisheries, because I guess knowing the production numbers on the fish that's caught in the wild, you know it only from the reported numbers and they might not be as reliable and they might not be as useful as predictions either.

Thomas: Yeah, but it's more about the fisheries because it's quota based, though it's not exactly. You can estimate it based on the quotas and the fish registered in. But on the production on the farmers side, it could vary a bit more, even though it's regulated to.

Silvija: So now I'll try to repeat what I understand and please correct me then if I'm wrong. So both of you are working on data based fisheries or fish farming related products. And on Bryton's side, they are using some sort of camera and AI technology to understand the production aspects of these fish pens and fish welfare. And you, Thomas, you're using production data and consumption data to predict and optimize the price and the production patterns. And for both of you, it's a big advantage to have an automated data collection platform. But also the more standardized the data between these different suppliers, the better for you. Is that correct? Maybe start with Thomas.

Thomas: I would say that we provide more information that would provide insight which the industry requires to do their business. So just on the production market side, that's part of it. So we do consultancy on what the market would like us to look into and that will of course include both the production demand, but we have to develop in the same line as the market will. So we will follow what the market needs and so what it provides of information that's also relevant for us and the knowledge which is built up through Aquabytet. That's interesting for me and our clients.

Bryton: I would also add that the data itself, like where does the data come from? Like how does the data of the weights, the slice counts, the welfare, it needs to come from somewhere. And so we're providing the original source of the data. So imagine you're at one of these fish pens. It's like 160 meters in diameter and 35 meters deep. Like, there's no way to know how the fish are growing unless you have a camera or some system that's measuring the weight or the sea lice. And so this is the data that then powers the rest of the industry in terms of insight and decision making.

Thomas: And I also would like to add that we need reliable data because there's a lot of data out there. But we spend most of our time with our analysts washing or harmonizing data to make it clear for analysts analyzing. So if we can get reliable data at first, we can spend more time on analysis. We can set up data, start scientists working on data, which is not harmonized, and watch as we double it then. So we need reliable data and then it's much easier for us to do the analyzing afterwards.

Silvija: So, Thomas, how does data lead to innovation?

Thomas: Data in itself. It just prepares us for doing the innovation part. You have to know what the problem is before you can do innovation and before using the data. So we are using biologists to interpret the data foundation. And if it's reliable and we know the picture of the case, we can do innovation. We can start thinking about new elements, new things. So that's also the aqua biotech. They are preparing for the innovation through tools which are useful for us. But we see that the more clear the picture of the industry is, the more innovation we are prepared to do. So we get a lot of ideas when we see the full picture of the industry.

Silvija: What do you think, Bryton?

Bryton: I mean, I think it's the difference from having an idea like the farmers in Norway have been farming for so long, they have a very good intuition of how the fish grow. And I think that intuition combined with actually knowing a scientific standpoint, from an objective standpoint, how the fish are growing. The insight combined with actual quantitative data is what makes the insights so powerful because things that they had an idea before, they can actually validate that that's actually what's happening in the pen. And so you're kind of going from these qualitative assessments of: I kind of noticed from the feeding cameras, the fish are eating in a certain way and the fish are actually getting fed properly, to actually calculating, okay, like what is my real time FCR and SDR? Like what's my growth rate and feet conversion and and actually knowing to to use that data in combination with the farmer's insight to be able to make better decisions.

Silvija: And somebody was giving me an example that, before you would go out and throw the same amount of food according to a certain chart. But now you can check how deep the fish are or you can check how much they're moving. Do they recognize if they are not fed enough or I mean, can you find mistakes in your usual processes? Can you optimize your processes if you have the right data? I'm just trying to look for examples that are easy for us that have been on a fish pen to understand. You want to start, Bryton?

Bryton: I can give a couple examples for example, what I had mentioned. So there's this notion of a feed conversion ratio, how many kilograms of feed turns into one kilogram of fish. And so previously there was no way to measure it unless you have to go through an entire production cycle. You harvest the fish, okay. How much of the fish grows? How much feed did I actually give? Now, in real time we can measure. Okay, I fed this amount in real time. It actually grew that amount and we can calculate these in real time to allow the farmer to understand the best feeding strategy. This allows them to adapt and optimize a lot quicker and ultimately get to a lot more efficient fish farming than they were able to do. Before I give another example, our first product was sea lice counting. And so instead of netting ten or 20 fish every week by hand, now the camera can count like via camera the number of sea lice on a fish. And this is allowing farmers to understand when is the best time to treat the fish? Because you don't want to treat it too often and you don't want to wait until it's a full infestation. And so this data is allowing farmers to make better decisions and it's allowing them to have more efficient operations. So, for example, last November we got dispensation from Montalcino so farmers can now use automatic lice counting without needing to do manual counting. And so this is reducing fish handling and enabling farmers to be more efficient to use that time for lice counting for other purposes.

Silvija: So, Bryton just a dumb question now. I don't know what this fish lice looks like. I mean, how close does the fish have to come to the camera for the camera to see these lice? And is it a hard problem?

Bryton: If you just had a camera, you could see the lice with your own eyes. The camera is not doing any magic. If you can see it yourself, you can detect it. I mean, the lice itself. The lice itself is very small. It's like a millimeter in size. But yes, we can detect it in water. And it's really the power of machine learning that's able to detect very small objects and be able to identify them with a certain level of accuracy. 

Silvija: What about you, Thomas? Do you have examples of how data has changed some processes?

Thomas: We can see if we bring it further on the value chain of what Bryton talks about. We can see when is the optimal timing to bring the fish out of the stock, out of the farmer farms. So if you need to know about the market, when is optimal pricing and we need to know what kind of size is it on the fish and what condition is it in the sea? So you have multiple factors here deciding when it's the optimal timing to bring the fish out of the sea. So if you know this better than the neighboring company, you have a competitive advantage. So it's quite important that you drive the innovation further. The one having the best insight will have the best competitive advantage, get the best price of the fish, the best quality and the best production and so on. So it will be a competitive advantage to be a customer of both Aquabyte and Kontali.

Silvija: And I'm just thinking also about it being kind of certifiably sustainable because I guess you can also give these guarantees about fish welfare if you can see them through every phase of their lives.

Bryton: I would say so. I mean, we launched our third product, which is the fish welfare product. It can detect wounds, quality, other aspects of fish health and actually quantify that for a farmer to report. And this is something that has actually been a trend in the industry. So previously you had qualitative analysis of fish, but now you can actually quantify that like in the different stages. And this is done in conjunction with research institutions like the Institute for Marine Research, where they have standards and locks where they can classify it into different stages. And so this data is really important to kind of make sure that the fish are grown sustainably. And I think also just in general, I mean, more automation, the less you can handle the fish is just better overall for fish welfare as well.

Silvija: Thomas, can you connect sustainability to pricing market developments?

Thomas: Sustainability is a multifactor term because it's not just about the environment and about the fish health. It's also about optimizing your costs and operating for a long term period without having costs on the outside of the external and having any external effects. So those being able to produce sustainable products compared to the other ones, will have a competitive advantage compared to the others. It's profitable to have sustainable production. So we're looking to share the knowledge from the Norwegian salmon farmers to other farmers around the world, because currently we have the best practice compared to other species. So we're looking to share this as best practice on sustainability to other species.

Silvija: I noticed that you are a fan of Elon Musk, actually a neighbor of Elon Musk as well. What would Elon Musk do if he was into fisheries and fish farming?

Bryton: I mentioned I live like 5 minutes away from the Tesla headquarters, and so I can almost run there. I mean, fish farming in some ways is even more difficult than rocket science. I mean, you're dealing with the ocean environment, which is very challenging, very rough. Understanding fish like the biology of the fish, but also creating a device that senses underwater. I think there's a lot of challenges. I mean, just to even take the latest innovations happening in farming and on land, I mean, that's almost like a SpaceX space shuttle for the fish. You have to have triple double redundancy to make sure the fish are alive. And so I think any of these challenges are more than enough for even him to be working on. I mean entrepreneurs working in industry are all kind of facing these similar types of challenges. And, if it’s not like rocket science, it's even more difficult.

Silvija: And you, Thomas, what do you think he would do if he was you?

Thomas: Yes, I would lift our heads and look forward 5 to 15 years ahead and invest heavily. So I think that's what we should do.

Silvija: So you think there is huge growth potential in the industry and I've seen some numbers and perhaps you can help me a little bit with those. I can only focus on two or three numbers at a time or per topic. And the ones that I remembered from your industry and then I'm referring to fish farming and especially Norway, is that we are currently at 1.1 million tonnes farmed salmon per year. I think that’s exports, I don't know if that includes total production and we are looking at 5 million tonnes of farmed salmon, and I forget whether it was 2035 or 2050 or some such. What will it take? And do you think that growth can be done in a profitable way?

Thomas: You can add here that land based farming is coming in as part of it, and it's becoming more global compared to what it is today, that has to drive the growth. And with more sustainable production, we will also be able to increase the production on each site. So those two elements will be quite important for reaching this 5 million target.

Silvija: But is there really a market for 5 million tonnes of Norwegian salmon?

Thomas: And just look at the effects from the COVID 19. It opens up new markets. The American market closed, but the demand was still kept quite high. So the consumer market replaced some of the lack of capacity and the lack of demand from the American market. The hotel, restaurants and canteens. So we are expecting to see now after this COVID 19 effects and the opening of the restaurants and hotels. Again, maybe just by looking at this, we will see that more demand is coming up. And we have at the moment have 7 billion people around the world. We are about to feed 10 billion in a couple of decades. So we need to feed the world with more proteins than we do today. So then the fish, then the fish and aquaculture, fisheries and aquaculture need to take it apart.

Silvija: So, I have one generic question not really related, I guess, to your company directly, but I'm thinking of the need for protein and then protein from the sea as the only kind of really scalable source of proteins going forward. And can we look at maybe Norwegian salmon as one of the top products, top end products there, but that there is more space to grow in all kinds of other proteins, including algae, etc.. I mean, are there areas that you would recommend people to look into growth for? Bryton. You want to start?

Bryton: I would say just to add on to what Thomas was saying. I mean, kind of growth in lab based. Also you have a kind of ocean farming that's happening further out where the industry can expand. Also increasing productivity of existing farms. I think it's something that I mean, the earth is 70% water, yet we only produce 5% of our protein from the oceans. And so there's a tremendous opportunity to be able to increase production and to be able to do that. I mean, we need to find ways to more efficiently produce, ways to produce kind of deeper in the ocean. And that all requires more data and automation and kind of brings it back to this topic we're talking about. And I think Norwegian salmon's leading that. There are other species as well. And I think that even if you combine all these different sources together, you still need more protein to feed the world. I think they're saying we need to double fish seafood production by 2030 to meet demand. So there is more than enough demand. We need to produce all different types of fish, including Norwegian salmon. It's exciting to see how it develops. Now it started with heavy investments on the salmon needs and some other species. But try to look now on what kind of species will have a joy within these farms on land based and live well for and develop on the production side. Because it may not be that the salmon needed is the best fit for doing the land based part, but other species are better fit and you can have these land based yards in different parts closer to the markets. So you change the market balance completely. And if just look at how much land based is planned on the salmon needs at the moment, and if they succeed with these production plans, it will change the market completely.

Silvija: Everything's pink. Bryton, I want to ask you. We're heading towards the end of our conversation, but I'm just fascinated about your both reading and viewing recommendations. And then we'll go to Thomas's recommendation after that. Can you please tell us what you could give us as a little present, as an inspiration to read?

Bryton: Sure. Yeah. So the book I recommended was Essentialism, which is more like a management book in terms of how to focus on the right things. I mean, the last book I read was Working Backwards, which talks a bit about how Amazon grew from being a small company to being like this huge company. I think for those who haven't seen it, we were able to participate in a TV episode where the CTO of Amazon. We brought him to a Norwegian fish farm and showed him the technology. And so that was part of their series. Now Go Build. And so that's on YouTube and Amazon Prime video. But like it was really I think it was they were saying it was the first time a makeup artist had ever been to a fish farm.

Silvija: Were they impressed?

Bryton: Yeah. I think they were really impressed. It's just an industry that, being in the US, not many people are aware of how these fish are produced, but it's amazing to see it at that scale.

Silvija: I can only imagine. I'm thinking about all the logistics, software and infrastructure that they have in their warehouses, etc. If there are any, I don't know, any ideas that could be transferred one way or the other.

Bryton: I think again they acquired Whole Foods and I think Whole Foods is a customer of Norwegian salmon. And they also want to make sure their food is sustainable, that they're going to all different types of industries.

Silvija: Yeah, very cool. And Thomas, you like Rosling?

Thomas: Yeah, I like Rosling.  If I were to be honest, I would say my cartoon Pondus because I like comedies. Rosling because I'm a statistician. I like working in math and data. He tells us the real story and what's behind the figures and tells us not to take statements as they're given, but to think twice. So I like this. Rosling, the way he is thinking, I was thinking.

Silvija: Have you heard about Rosling too, Bryton?

Bryton: I haven't.

Silvija: No, he's a very, very cool Swedish statistician. I don't even know what his background is, but he has a very, very nice way of visualizing stats, but also helping us think better statistically.

Silvija: So if we were to leave a bit of advice to people who are looking into working with anything fish related. What do you think? How do they get connected to being either an AquaCloud or on other data platforms? And where do they start? Who wants to start?

Thomas: I have to think about answers. 

Bryton: I would say, if even someone like me, who had no experience in fish farming can come to Norway and get acquainted with the industry. I think that just goes to show that there's opportunity and a real pathway for the kind of entrepreneurs who want to work in fish farming in Norway through Seafood Innovation, but also other organizations. I think there is just an amazing group of folks in Norway working on these types of problems. And there's lots of hard problems to solve and and definitely to come and participate and help kind of bring aquaculture A.I. to the industry.

Thomas: Yeah. I think I have too little overview to answer this question correctly. But we are using Seafood Innovation in Thailand. We are pleased with the network we are having from Seafood Innovation. And so to my knowledge, Seafood Innovation is a good way to start to get our network both for the students and up to seniors.

Silvija: I think you both are into something really important because let's say I'm a fish farmer and I don't feel very acquainted with digital technology and all things digital. I still think I could go to colleagues and listen to stories like yours, like Kontali Aquabyte, and try to understand what’s what, what have other people done that worked? And then see if I could try at a small scale myself.

Silvija: But my last question I like to ask people. We started with a personal question and we are going to finish with the personal question. And it really is about how you deal with difficult times. How? How do you build grit? How do you develop your own growth mindset in order to keep going when things are rough? You want to start Bryton.

Bryton: I think it's kind of working back from the future. I think we're going to look back years from now and wonder how we ever farm fish without knowing the weight or the growth or the lice on the fish just like this basic information. And I think when you're in the day to day kind of building and refining the technology, it's tough. I mean, it's really kind of looking back from the vision you have of this is where the industry needs to go and that provides inspiration for the day to day keeping your head in terms of challenges. And I think in some ways reframing those challenges is part of the experience of learning and growing. I think that makes the tough times a little bit easier. 

Thomas: I would like to add that management is about to solve challenges when things are good. It's not ending up in my table or Bryton's table. It's challenges that are solved. So my suggestion is to keep things in perspective. What we're doing here is important for the industry, but it's still a small part of the whole world and what we're building. And for me, I keep focused on the family side and prioritize the family. And I'm not here to work 70 hours a week. I try to spend normal time at work. And then I also am more focused on the challenges and challenges ahead. And they use my family to support during the toughest times.

Silvija: Very cool. I like both ideas. I think I always steal a couple of ideas from these talks and I think applying these working backwards principles not only on business and strategies but even on personal life would be really, really helpful sometimes. And I think also, Thomas, as you were saying, keeping things in perspective always, always helps when we I think we only get really stressed when we lose perspective. Thank you so much for inspiring and teaching us in this learned conversation about aquaculture, aquaculture and Aqua Cloud.

Thomas: Thank you for inviting me.

Bryton: Yeah, thank you.

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