The Ocean Cleanup's mantra: Start simple and iterate relentlessly

Simon: I was gonna say, but who’s counting, but clearly it’s important to count.

Boyan Slat: That’s right.

Werner: Well, you were quite young when you started this, 18, at Delft, I assume you were still there. So tell us a bit about the story. What drove you to get this going at all?

Boyan Slat: Sure, yeah, I think I’ve always been a bit of an inventor all my life. I’ve been very passionate about building things, engineering. Going all the way back to when I was 2 or 3 years old, and I remember building my own chair out of some wood and nails, just because I thought that’d be more fun to sit on than one my parents would give me. And then it went into my next passion was computers, so I assembled my own tower and then I was into chemistry and, it’s buildings of explosives and smoke bombs and one day I almost burnt down the house because I was distilling ammonium nitrate on the stove. I kind of lost track of time and, yeah, I filled the entire house with smoke, which… my mom really loved that phase. And then I was into model rockets, and then when I was 12-13, I decided to set a Guinness World Record, launching more than 200 of them at the same time. So, I’ve never been bored. It’s the short summary there, but it all wasn’t very useful. It’s just sort of having an idea and then making that real. I think there’s just an immense amount of satisfaction I get out of that. But then, yeah, when I was 16, I went scuba diving in Greece and I was hoping to see beautiful nature. I went underwater and I came across more plastic bags than fish. And the natural thing for my brain to ask myself was, why can’t we just clean this up? And once an idea like that or a question like that starts brewing in my head, I really cannot stop thinking about it. So, and then I went to Delft to study aerospace engineering. But, yeah, at the same time, I still was obsessed with this idea. And then after half a year, there’s this point when I said, well, I can’t really do both, so, let’s give this a try. If it doesn’t work out, it can always re-enroll after half a year. But then, a few months later, there was a TEDx presentation I’d given that went viral, was shared millions of times, and then allowed me to build an initial team, raise the first few million dollars, and yeah, it got us going. So, yeah, that’s

Werner: So, talking about funding there — originally crowdfunding — how did you get from crowdfunding to having a let’s say sustainable income for your business so that you can continue to run it.

Boyan Slat: Of course, what we’re trying to solve is essentially, we’re creating a tremendous amount of value. So, when you look at the harm done to ecosystem services by plastic, it’s estimated to be between 500 billion and 2.5 trillion a year. So, and there are not many companies with that level of revenue, if any. But of course, most of that value is not value that’s captured in the GDP of human civilization, right? It’s things like clean air, coastal protection, being able to go to a coast and having clean beaches, having marine life, all of that. So, of course, we tap part of that through tourism, fisheries, etc. but, yeah, a lot of it is not captured. So, I think if something can be a for-profit, it should be a for-profit because then there’s such a beauty in having this alignment of incentives between your team members, shareholders, wider society. But the problem is, of course, when you’re doing something like this, which is really outside of the market, you don’t have that. So that’s why I opted to start a nonprofit when I started this. I really didn’t see any other way to get it off the ground, and crowdfunding, actually the first crowdfunding campaign was $89,000 and then the second one a year later was $2 million. But, that got us started but of course, it wasn’t of the scale that was required to really make this work. But thankfully, over time, I think the way we’ve approached this is almost like investment round. So, basically, we raised some money and then we get results and then with those results, we get to the next level of credibility and yeah, I think your level of credibility has to be sort of proportional to the amount of money you can raise can raise, right? So.

Werner: But you’re also building things, so for that you absolutely need capital to be able to

Boyan Slat: do that. Yeah, exactly. So, I think then over time we were fortunate enough that both individuals and companies stepped up to support us. So you got people like Mark Benioff, Salesforce, Joe Gebbia, Airbnb, as well as literally millions of other people who decided, OK, hey, I want to be part of this. This is like an Apollo project for the Earth. This is really exciting and we want this to happen. And then over time, of course, at the beginning, it was this very high risk, high reward project. But over time as the risk came down and now it’s at this moment, it’s not a question anymore whether we can do it. We know exactly what to do. It’s really just a scaling challenge. Yeah, companies also started to get involved, and there, of course, it’s more than philanthropy. It’s really an exchange of value, right? Because for corporates, partnering with us, it allows them to have this valuable story, increases brand value, increases awareness. So, these partnerships is something I’m really excited about and the journey is a business type of transaction.

Werner: Recently I heard a lot about microplastics, that are inside people and inside fish and things like that. Is there a relationship between what you are trying to clean up and those microplastics?

Boyan Slat: For sure, yeah, the fortunate thing is that only a very small fraction of plastic in the ocean is currently microplastics. It’s in the order of a few percent. Most of the plastic is actually large stuff, and of course what we do is, unfortunately the tiniest pieces, they’re really too small to extract. Fortunately over time, they will wash up on shoreline, so they won’t be there forever. But of course, by removing everything that’s not microplastical, the larger objects, you prevent the creation of those microplastics because they are really coming from the degradation of larger plastics. And then on top of that, by what we do in rivers, we prevent the inflow of new plastic into the ocean. So, yeah, I think what we do is we really prevent this ticking time bomb of the amount of microplastic increasing tenfold, hundredfold in the next few decades if we don’t clean this up.

Simon: So, Boyan, let me take you back to the early, early, early days. And your first system called Wilson, which I understand didn’t last too long before it sort of reached its limit. Tell us about that and what that really, how that changed your thinking.

Boyan Slat: So the original vision to clean up the Great Pacific Garbage patch was to have a giant U-shaped barrier that was passive, that was just free floating. It would be pushed forth by wind and waves and would corral the plastic inside of it, so we’d only have to come by periodically and empty it out and bring it to the plastic to land for recycling, which was a very elegant idea on paper. But in reality, it turned out, it didn’t collect plastic, so we deployed it and then it didn’t collect plastic and really just a few months later, it broke into two. And obviously, we learned a tremendous amount from that. And yeah, after that, we completely changed the approach and then we eventually got to a system that worked. But yeah, looking back, I think what I would have done differently is that, obviously, we learned a lot, but I think we could have learned the same lessons in a cheaper way. We truly believed that that was the system that was going to clean our ocean. It was always like this tunnel and… and then ultimately, I mean, you’re going to fail along the way, right? When you’re doing something new, you’re going to have so many failures, but I think your job as an innovator is really to make sure that you can recover from those failures and that you make mistakes in as cheap and fast way as possible. So, it was great what we learned, but I think we could have learned it with a system that was maybe 1/10 of the scale and maybe close to shore rather than actually in the middle of the Great Pacific Garbage Patch. So, that’s kind of the thing I would have done differently though.

Werner: So you started off with trying to attack the biggest problem there was. Yeah,

Boyan Slat: right, so it wasn’t really this MVP, I would say, and before that we had done scale metal tests and we had done prototypes near shore, but the actual thing of catching the plastic, which is again, quite an important requirement for an ocean cleanup system. We only really put that to the test at full scale in the real environment while, maybe we could have done that with simulated plastic or something closer to shore.

Simon: So these are lessons where there’s a famous t-shirt I’m sure you’ve all seen that says, I don’t often test, but when I do it’s in production, and that’s sort of the experience.

Boyan Slat: Yeah. And I think, yeah, when we started out, I think we went through 6 or 7 conceptual iterations over the years and the way I imagine it is like a landscape full of hills and your goal is to get on top of the tallest hill. And then there’s this dense fog, and you can only look 3 to 5 m ahead of you. And at some point, you’re climbing a hill, but you don’t know yet whether it’s actually going to be the right hill, the one that you actually want to end up on. So, it does take a certain degree of trial and error to find that hill. But again, it’s really just about yeah, trying to limit the cost of that experimentation and I guess it’s always very hard to know, like, am I climbing the right hilltop here. I think one thing that I noticed is when you’re actually climbing the right hill, things seem to get simpler and simpler over time. While when you’re climbing the wrong hill, actually things spiral into complexity. So I remember when we were still trying to make that passive system work, there was this challenge of these contradicting design requirements where on one hand, you want the system to be flexible, to be able to follow the waves so that it doesn’t break under sort of fatigue loads. But on the other hand, you also want to keep the system open because you don’t want it to collapse because otherwise the plastic can’t enter, right? So, then at some point in time we got to the point that we were doing engineering studies on literally an Eiffel Tower-sized steel structure that was submerged below the water level that would act like a spreader to keep that U open. And then at some point I was thinking like, guys, what are we doing here? This is insane. We’re creating a literal Eiffel Tower here, like a steel truss structure and… yeah, you might be familiar with this idea of epicycles before Copernicus figured out that everything was rotating around the sun. There were these other models that kind of mathematically you could make work, but basically, you got these little circles and circles and it just was not simple at all, but you could make it work. But I think that when you see epicycle, it’s kind of a hint that, OK, I’m not on the right track here. I’m climbing the wrong hill.

Simon: So in a lot of the early systems in the sort of starting off point, you were using a lot of sort of off the shelf hardware and open source models for computer vision, etc. and things have changed a lot since then, but what did those experiences teach you that you still apply today?

Boyan Slat: Yeah, so computer vision — general sort of sensing — is really a core part of our solutions. If you think about it, the key to our success is being there where the plastic is. That applies to both what we do in the Great Pacific Garbage Patch in the middle of the ocean, as well as in rivers where, in this Great Pacific Garbage patch, you’ve got an area 3 times the size of France where on average the plastic is super dispersed, but then, when you take a sailboat through it, there are days when you see hardly any plastic, and there’s days when you see tons and tons of plastic around you. So, being able to determine where these hotspots are, which by the way, are dynamic — they come and go all the time in different places, different times. That is really the key because otherwise you’re just basically sieving the ocean. It’s really about pinpointing those places where the plastic is. And similarly in rivers, what we found is that less than 1% of the world’s rivers is responsible for 80% of plastic pollution. So, being in the correct rivers is, yeah, sort of the key to being able to do this effectively. So, what that means is, yeah, really when we go into these coastal cities, it’s deploying hundreds of sensors around the city. Being able to determine what’s the Pareto here, which rivers do most of those emissions and where in those rivers should we deploy. And for example, some rivers, you got vessel traffic as well, right? So you can’t block off the entire river with our systems. So, there we released GPS trackers that mimic the flow of plastic, so we can really again strategically deploy there where the plastic goes while giving enough space for boats to pass. So, it’s all about being at the right place at the right time and even though the clean-up system, the hardware is simple and it must be simple because complex hardware is very hard to scale. It breaks down, it’s hard to maintain, it’s hard to deploy, etc. So you want to keep the hardware as simple as possible. And then, basically all the complexity, that’s really applied to what we call the software side, right? So, really the intelligence of especially upfront in terms of determining where you deploy.

Werner: So why is it, actually, that these 20 rivers are the ones that are causing most pollution? I mean, Is it humans? Is it factories? Is it, I mean, how come there’s only these 20 rivers that actually take

Boyan Slat: 80%, so we are currently deployed in 20 rivers, but the 1% actually represents in the order of 1000 rivers. So, it’s still a significant amount, but I guess when we say rivers, a more accurate word would be waterways. Most of them are pretty small drains. What we see is that these rivers are concentrated in coastal cities and middle-income countries, where you got a combination of a high concentration of population close to the coast. And you have basically very poor waste management infrastructure. These are countries that are rapidly developing economically. People now have enough wealth to buy a lot of stuff wrapped in plastic, but the government basically does not have the money yet to do proper waste collection and disposal. What’s quite interesting is that there’s really no correlation between the amount of plastic that a country consumes and the amount of plastic that it emits to the ocean. Essentially there’s this thing called the Kuznets curve, which is like an inverted U, where the poorest country, they hardly emit any plastic because they don’t consume any plastic. The richest countries, they consume most of the plastic. So, the world’s richest countries, they consume about a third of all the plastic, but they’re responsible for less than 0.5% of global plastic emissions, because here in Western Europe and US and Japan, Korea, we of course have good systems to collect the waste and dispose of. It’s really this middle ground, places like Jakarta, Manila, Mumbai, Accra, a place like that where you have a lot of people, a lot of plastic now getting consumed, but basically no way to collect and dispose of it.

Werner: Yeah, I was very fortunate a few weeks ago in the Amazon, and no plastic in the Amazon.

Boyan Slat: I think what’s quite interesting as well is that most plastic that ends up in rivers never makes it to the ocean. So — we actually tested this with the GPS tracker experiment. So, a year ago, we released, I think about 100 GPS trackers in Manaus in the Amazon. None of them made it to the ocean. And that’s really because it’s so far inland and of course, the slope of the river is also, it’s very shallow, right? It’s like an ocean almost. It’s not like a very aggressive, fast-flowing river. That plastic just gets sort of beached on the river banks and gets stuck in twigs. But that stuff, yeah, it really doesn’t make it to the ocean. When we started out back in 2017, our first global river model actually predicted that the Amazon would be a key contributor, but back then, we didn’t really understand the physics yet. We didn’t know this fact. And now when we take that into account, actually, the Amazon just completely drops off our list of priority. Which is good because it’s insanely big and I’m very glad we don’t have to do that one.

Simon: So, Boyan, tell us a bit more about something the team did using some artificial intelligence where you cut data transmission costs by 99.975%. That’s a lot of cuttage. Can you walk us through how you used AI as a practical tool rather than a silver bullet?

Boyan Slat: We developed something we call AIDIS. It’s the Automatic debris identification System, which are these cameras that we attach to ships. Just merchant vessels like cargo ships, container ships that go around the world all the time and whenever they enter ports, they send a data package to headquarters here and it actually tells us the concentration of plastic along the path in the ocean that they traveled and we use this to better determine the location of the plastic in the Great Pacific Garbage Patch, but also as a global thermometer for how we’re doing, right? Because ultimately, we make it very explicit, we want to help ourselves out of business. But for that, we need to know when we’re done and we really need to be able to track what is the trend in terms of how much plastic is in the ocean. So by having these ships continuously traversing the ocean, getting that data, we are able to have this global plastic thermometer and,

Werner: So these models run on the cameras. So all the processing is done locally at the edge and you basically get the data, the resulting data from that.

Simon: Amazing. So it’s such an impressive way of doing things. Now, one thing you’ve touched on here is the global nature of the work you’re doing, which introduces a whole lot of extra complexity. I mean, we talked about 20 rivers, 9 countries, you’ve got ships going everywhere, like, there’s a lot of stuff going on. How do you design your systems so that you don’t need a specialist engineer everywhere? Cause I can imagine that could get quite expensive if you went down that track.

Boyan Slat: Yeah, so I guess that’s another one of those items for the list of mistakes I made. So the original system that we developed to intercept plastic in rivers was a really cool machine. It was fully solar powered, fully autonomous. And like a trash eating robot essentially. And then we deployed them in places like Thailand, Indonesia, and then you discover, oh well, actually, first of all, it’s very hard to import those things because how do you classify it? Is it a boat? Is it a barge? Is it a, what is it? There’s no sort of lines

Simon: tick box for trash eating robot.

Boyan Slat: Yeah, and then you need the permits to deploy again, same problem. Then installing it requires specialized installation vessels and, it’s quite difficult. Then you need to train people to operate it again. Pretty difficult. You need to have the maintenance, and then you have these PLCs on board, and then like a tiny thing breaks, you have to air freight something from Germany to fix it, and it’s just a big mess, right? So, then we got to the conclusion that, OK, maybe people are underrated and, actually creating jobs in these places is actually also something that is a positive side effect to what we do. So, then we kind of backtracked on that and went to more simpler hardware, simpler ways, using excavators for extraction rather than conveyor belts. And, yeah, I mean, that’s working quite well, of course. Now the key is, so, the technology is quite simple, but now, looking ahead, right now, we’re doing about 1 deployment per quarter. Next year, we want to get to a point where we’re deploying 1 interceptor per week, roughly. So, that scaling ramp, it really requires us to rethink the way we’re doing things. It’s still too much reinventing the wheel every time, seeing everything as a unique project. So it’s all about building this project factory now where we standardize everything from the contracts we set up with the operators to all the individual hardware components to the installation manuals, it all has to be standardized because otherwise, we will not be able to get to that deployment gate.

Werner: Mm. You’re generating or collecting an enormous amount of data, with all the ships and also the things that you have yourself. What do you do with the data? I mean, beyond just running your company and beyond making decisions yourself, is this something that you share with others as well?

Boyan Slat: Yeah, for sure. So actually, we’re just going through a review of some of the next cities we’re going to tackle with our interceptors this morning. And it’s amazing, for basically the entire city, we mapped the entire river network. We know exactly where all the landfills are. We know exactly where we need to deploy the trash flux out of each of the waterways. It’s amazing. And then of course, even post-deployment, we are collecting tons of data because we’re able to see, OK, what’s the trash we’re collecting, the composition, the quantity. So, and of course, we’re using all this data to deploy the best possible solutions and to further optimize their efficacy and improve the next set of deployments. We’re also using it to, of course, convince funders, partners to show, here we go what we’re doing and we have a good plan to tackle a given city. But we’re also sharing it with the local government, because they are actually able to make better decisions with that data. For example, in Jamaica, one of the things we found is that the bulk of the trash was Styrofoam packaging. We shared that data with the government and then they themselves decided to ban those Styrofoam clamshell takeout packages in Jamaica, just because they saw like, OK, actually the majority of trash coming down the rivers is what it is. So, yeah, and that I guess, a broader point there is that what we’re doing, of course, it is not the ultimate solution. Ultimately, we don’t want plastic to even flow down these rivers. We hope one day those interceptors are not necessary anymore. But that’s not going to happen tomorrow, but it’s not either or, right? What we’re doing through the data we collect, through the visibility we generate for the problem, we’re actually able to help catalyze that upstream change as well.

Werner: So do you think you’ll ever be done?

Boyan Slat: Yeah, for sure. Yeah, so, and I think there’s two levels of done, I think. There is the point when the oceans are clean. Which I think — we should be able to express in years, not decades. So, right now, we’re stopping between 2 and 5% of global plastic pollution. We’ve doubled last year, we’re doubling again this year. So, just, mathematically, you don’t need that many more doublings to get to 100%. So, yeah, and I think now with this 30 cities program, we want to tackle a third of emissions in the next few years. So, that should allow us to maintain this annual 100% year over year growth. So, I think pretty quickly we’ll be able to get to the point that, hey, great, oceans are clean again. At that point, however, those interceptors are still necessary, right? And because if you stop operating them, the oceans will get polluted again. And I think that will be true for a while. I think before the world, the entire developing world is as pristine as Singapore or something, I think we’ll take a few decades and of course, we need to make sure that the interceptors will keep operating during that time. Of course, what we do envision is that after a few years, the government can really step up in essentially integrating our interceptors into their waste management infrastructure. So, it’s basically just like they have garbage trucks in the streets, they need to operate interceptors in their rivers. But, so yeah, I think clean oceans very soon, but then the day that we can take out all the interceptors and it’s truly done, I think that will be sort of decades away.

Simon: Now, you spoke about the growth rate and sort of how much we need to double, etc. and obviously you wanna maintain cost control to make sure you can grow in terms of the collection, and you’ve often said that cost per kilogram of plastic removed is one of the KPIs you really most value. Tell us about how you apply that metric to your technical decision making.

Boyan Slat: Yeah, of course, the unit economics are very important. So we use this to really prioritize where we deploy. And it’s also a metric that we use to drive continuous improvement, both in terms of initial investment, operational cost. It’s something we use to judge the performance of our operators. So the local contracting, contracted company that actually runs the interceptors. So it’s definitely a key metric. It’s not the only metric and I think one nuance that we’ve recently started making is that it’s really not cost per kilo of plastic, but it’s really cost per unit of impact, because in some places, you can imagine, say, two hypothetical cities, one city that emits 1000 tons a year, but where it’s basically just sort of mud flats around the city. And then there’s another city that maybe emits just 100 tons a year, but those 100 tons go straight into a coral reef with a tourism hotspot, where, of course, so the social, environmental damage will be much greater than in the first scenario. So, we’re now able to actually put a dollar value to the ecosystems around those cities where the plastic goes. So we’re able to better, again, make better decisions in terms of where we should prioritize our deployments.

Simon: That’s amazing. Where does the plastic go? Like you’re collecting this plastic, like, what? What happens to it all?

Boyan Slat: The places where we go to tend to be the places where, of course, where the biggest leakage occurs and where the greatest leakage occurs tends to be the places where the poorest waste management infrastructure exists, right? So, it is always quite a puzzle to figure out, OK, what do we do with this waste. And in most cases, we are able to find suitable, responsible destinations for this waste. Of course, there’s this hierarchy of waste destinations. So ideally, what’s at the top is recycling. So if in some places there’s quite a large PET fraction, which is the type of plastic that’s most valuable, easiest to recycle. So, there you have a big chunk that gets recycled. And then below that, you said you got landfill and incineration where of course we audit those destinations to make sure that those landfills don’t leak, that the employment conditions are responsible, and, yeah, to really make sure that that waste never ends up back in the environment and is staying there in a responsible way. Where, sometimes we actually have to decide, OK, there’s no good solution here yet. However, we can’t, there’s just so much pollution, we just have to go deploy. And then we actually ourselves invest in improvements of the infrastructure to make sure that ultimately we can guarantee that none of our waste ever goes back in the environment. So that could be investing in sorting centers. It can be investing in something as simple as fencing around a landfill to make sure that the landfill doesn’t leak into a river that’s next to it, is really, yeah, like we believe it’s our responsibility to make sure that everything we collect never ends up back in the ocean. So that’s the story for the riverways, which is actually the more complicated story than for what we take out of the Great Pacific Garbage Patch because there actually we’re able to recycle almost everything. And together with our partner Kia, we’ve made components of their electric cars out of our plastic. And Coldplay’s latest record has a special edition made of our plastic, and, yeah, and I think, with more and more partners coming on board, yeah, we’re doing kind of fun and exciting things together with them to really tell the story of the ocean cleaner.

Simon: So Boyan, one last question, could be an easy one, could be a hard one. What’s the most important thing that you’ve learned or something you’ve changed your mind about since you started the ocean cleanup?

Werner: Don’t do it.

Boyan Slat: Actually, I keep a list of things I changed my mind about in my phone, so let me pull that.

Simon: Well, there’s a tip right there, a podcast listener tip. Keep a list of things you change your mind about, cos one of the important things is to be flexible enough to change your mind. What was it, when the facts change, I change my mind, what do you do?

Boyan Slat: I personally heard Jeff Bezos say the same thing at a conference where it’s like you have to be very stubborn about the goal, you have to be very flexible in terms of how you get there, right? And the vision, flexible on the

Simon: details.

Werner: Well, I mean, the way that you solve this is you have a lot of hardware and hardware is always way more difficult. than making software.

Boyan Slat: It’s a long iteration cycle, so I think throughout my life I think the connecting thread has been that I get an immense amount of satisfaction from having an idea, having a vision, and then seeing that become reality. And I think in the first few years that the mental image that was super crisp and sharp, and I could see that like a movie, that picture in my head. It was always about seeing that first cleanup system in action or seeing that first river system in action. And of course, I was able to make those pictures a reality, together, of course, with the team and everyone that all the parties, etc. But actually, the lesson there has been that it was the wrong picture that I had in my head. I shouldn’t have dreamt about this particular machine. I should have dreamt about a clean ocean, essentially. And yeah, I think as an inventor, it’s very easy to get sort of an emotional attachment to your ideas, to your inventions, and that can stand in the way of being flexible enough when it comes to how you get to the goal. Because the goal is not having 1000 interceptors on Earth. The goal is to have a clean ocean and that’s a subtle difference because of course, we need one to get to the other, but it matters a tremendous deal.

Simon: Amazing. Boyan, thanks so much for coming on and telling us about the journey.

Werner: Yeah, thank you, it’s great, great story, great company, and you guys are doing amazing work. Thanks so much.

Simon: Absolutely, and Werner, thanks for co-piloting again as we roll through hearing some of these great stories. I mean, it just shows that frugality affects the world in which we live in, if applied properly. And of course, we do like to get your feedback. awspodcast@amazon.com is the place to do it. And until next time, keep on building.