Imagery provided by: Promare & IBM
In this episode of HxGN Radio, we explore the Mayflower Autonomous Ship (MAS) and its future voyage across the Atlantic as an unmanned and completely autonomous vessel. This ship is poised to revolutionise the maritime industry with its use of artificial intelligence, machine learning and positioning technology. This podcast will explore the origin of the MAS project, as well as take a deep dive into the ship’s future and beyond.
BK: Hello, everyone, and thanks for tuning in to “The Mayflower Autonomous Ship: Now and into the future” on HxGN Radio. I’m your host, Beth, and today I’ll be speaking with Brett Phaneuf, Managing Director of the Mayflower Autonomous Ship. We’ll be taking a deeper look at this unmanned and completely autonomous vessel that is poised to revolutionise the maritime industry with its use of artificial intelligence.
Welcome, Brett. How are you doing?
BP: I’m doing great. Thanks for having me.
BK: Thank you so much for being here. I know this is an exciting time. And we’re quickly approaching the launch of what we will be calling MAS or the Mayflower Autonomous Ship. So let’s jump right in, and I want you to tell us about the origin of the Mayflower Autonomous Ship and when the idea of making the ship autonomous first unfold?
BP: Oh, okay. Well, there’s a lot. So I started drawing all sorts of wild-looking vessels for 25, 30 years in my career and building submarines and other exotic underwater and surface vehicles sort of in my day to day life. And I just happened to also have a nonprofit foundation that we put together with some friends years ago to kind of do this sort of marine exploration, anything that sort of took our interest sort of as a sideline to our day to day jobs, so to speak. It was supposed to be fun, and it has been. And I just happened to grow up near Plymouth, Massachusetts, and I happen to live now in Plymouth, England, and it happened to be around the 400th anniversary of Mayflower. And not only do I have an interest in marine technology, but endo autonomy and A.I. before the Mayflower Ship, Mayflower Autonomous Ship, but also I guess a past life as an archeologist, and my wife’s a maritime historian. So it’s sort of a perfect storm of interests sort of collided around the 400th anniversary.
So, a few years ago, we were meeting with the city of Plymouth here in the UK just on a completely separate topic. In fact, I don’t even remember what it was. And they were saying, well, you know, 400 years is coming up. In four years, we should do something. We’re thinking maybe build a replica ship. And, you know, I grew up as a child going to Plymouth, Massachusetts, and looking at Plymouth Rock and standing on Mayflower II. There’s already a replica. And I said, well, maybe we don’t make another one of those. Maybe what we should do is come up with an idea that speaks to the next 400 years of the maritime enterprise, not the last. And maybe take an inspiration from the original voyage, which, if you think about it, was fraught with unbelievable risk. These people that went on this ship and went off across the ocean in sort of an old leaky boat to an uncertain—I mean, they didn’t even land in the right place. They were wildly off course. Right. They were going to Virginia. So it’s unbelievable risk. I mean, all of them could have died. Many of these people did, you know, from other colonial expeditions. So, I was inspired by the grit that it takes to do that, that jumping off into something new, into the unknown. And I wanted to reclaim a little bit of the name of Mayflower and focus on the future and cooperative research in the oceans and the best interest of everybody. The ocean is sort of the lungs of the planet. Sorry, I’m rambling on and on.
BK: I think it’s fascinating, your tie to both Plymouth, Massachusetts and Plymouth, UK. And so thank you for sharing. Now, in the beginning, how did you start to piece all of this together, the MAS project, as well as identify the technology that was needed for the ship to be successful?
BP: Well, we knew that from what we do day-to-day in the marine industry, we knew that the base technology—sort of we know how to build ships. We know how to build power and propulsion systems. We know that there’s more and more green energy available to us and becoming commonplace technology. We know about automation and robotic systems, which is not the same—so we said, well, all right, we can build robots that are deterministic, meaning you tell them to go do something, they go do it. But they’re not flexible. They don’t adapt. They don’t replan their course. They don’t—and I don’t like to use these sorts of anthropomorphic terms, but they don’t think, right? So we knew we could do something like that, and other people were—the military does it. Some research groups do it. There are some companies that build these sorts of things—but we were really interested in this sort of bleeding edge, next generation vessel that could sort of act as a cooperative partner, either with other vessels or like it or manned vessels or with people onshore and try to drive the cost to do research down by including these sort of bleeding edge technologies. And when we started four or five years ago, we probably couldn’t have done it. So the technology evolved incredibly rapidly over the last five years.
And really the way we got it done was we had great partners come on board who just thought the idea was fascinating. And so how do we make it happen? I guess to answer that specific question is, as you can tell, I can be loquacious. So, I went all over the place running my mouth about how cool it would be if we did this and had some kind of cool drawings and got some early partners. And the drawings went through a period of evolution as we kind of winnowed it down to what was really feasible and what we could afford from the little nonprofit that was going to pay for all this. And then companies like IBM thought, hey, this is a great way to talk about A.I. because it’s sort of the utilitarian contextual assembly of state of the art current A.I. systems, and that’s a great thing for us, so people can understand what it is and what you can do with it and why it’s powerful as a tool. And it’s topical because it’s in the marine and the climate oceanographic space. And then we had companies like Hexagon come along who saw it, and Veripos, really a Hexagon company and said, well, if you’re going to do that, you’re really going to need to know where it is. And we’re the best in the world at knowing where it is, where anything, right, is.
BK: Right.
BP: And so, they started talking to us about some of their state of the art technology and the sort of evolution that technology was on the arc of development. And over just the four years and talking with the Veripos people who’d been unbelievably supportive, like IBM, like so many other people that just came and gave us things and said, would you like one of these? and things we could never afford. We watched the evolution of not only our thinking about how we could do it and what we could accomplish, but the technology at Veripos just underwent an evolution. It kept getting smaller and better, just like everything else in microelectronics.
So, now we’re kind of at a point where we’ve assembled the whole ship and we’ve got all the technology integrated, and now that doesn’t mean the technology stopped evolving. It keeps getting better and it’s accelerating away from the ship now, it’s happening so fast. So we’re going to have to start on a second ship.
But that’s always the way it is. You’re always behind the technology curve when you set something in stone, so to speak. And it’s real. Well, that, you know, then you’re stuck with some of those limitations. But the Hexagon guys just keep sending information, keep sending new equipment, smaller, lower power, more precise, more features that enable, one of the key enabling factors for anything like this is where is it? So if you don’t know where it is, all your data is pointless.
BK: Of course. And you know, outside of the location technology, which I think is key, what other specific technologies would you say are very, very necessary to make this voyage happen?
BP: So many things. The most important thing, and this is the thing that people don’t often say when they talk about A.I., the most important thing is the people that you have who understand what’s actually possible in what these systems do. And A.I. now, in my mind, it’s sort of like Legos in a way, sort of an assembly of programmes either in firmware and software and strong mathematics, combinatorial mathematics, and computer vision and then deterministic systems that aren’t sort of probabilistic but deterministic. So, by that I mean, so, you’ve got great computer vision stuff from NVIDIA and then, well, to make that work, you’ve got to make models. So you’ve got to go out and get millions and millions and millions of images of things, which we did. We built our own infrastructure to collect our own data and then used IBM, at the time it was called Visual Insights to make models that we can push out into little software containers to run on tiny little microprocessors. You know, there’s no single server on the boat. It’s all little, tiny single board computers. It’s ridiculous. You could pick it up and walk away with it. And five years—
BK: That’s pretty incredible.
BP: Yeah, it’s insane. And so, you know, I remember when I was at grad school, when I started my first year of grad school, I had a Macintosh network that I had assembled for our department, for the grad students in our department. And the server was 20 megabytes, and we ran 24 machines on it.
BK: Wow.
BP: Right. So, you think about that, you know, the evolution of it’s so fast. So, we wanted to keep involving all these companies. We get all these little technology. So, computer vision and then marine electronics like radar and automated information systems that broadcast, “hey, I’m this kind of ship going in this direction at this speed” to other ships around it that are listening, and that on radio frequency. But now it’s space based. There’s companies that have emerged that are doing this all on the Earth, orbiting satellites. So, you can see where every ship in the world is at any time for free online. And you’ll be able to see where Mayflower is, the same thing. And it uses that to sort of say, okay, I know where there’s lots of ships, and then it uses its radar. So, I know where the ships are that are far away and near from AIS, and I know where they are from radar. And I’ve got computer vision, so I know where they are when they’re really close.
And then it has to fuse all that data using the models for all those things we developed and figure out sort of, well, I know I move like this and I know those sorts of things, those individual things that I’ve discovered with different technologies. I fuse it so I can have a complete picture of what those things are. And in the metadata, in the models, it knows sort of how those things might move. And it sort of makes a heat map of where it’s safe to be and not be. And then you have to follow the international regulations on avoiding collisions. They call it COLREG’s. And so, well, how do you do that? How do you teach a ship that?
So, IBM was fantastic about it. They said, oh, well, you know, we have this tool that’s been around a long time called Operational Decision Manager. And you just write rules in natural English and it figures out the relationships. You work with it to figure out the relationships. And then it applies those rules to financial transactions. And this runs globally on the cloud, billions and billions and billions of 4X. And these are credit card or credit card processing and loan applications are done like this, right, because when you go in, somebody makes a decision to exchange money. You want a paper trail. You don’t want any ambiguity about why one pound became X number of dollars. It has to make sense. You have to have a record.
So, this cloud driven tool keeps all those immutable textural records in natural language based on the rules you taught it. And you can dynamically update the rules. And they said maybe that would work for COLREG’s. In fact, COLREG’s is pretty simple compared to the global financial structure. And they worked with us to then shrink it all down and get it to work on a tiny little single board Linux Red Hat computer in the boat. So, it’s not in the cloud now; it lives on the boat all by itself. And every time the computer identifies the targets around it, it asks the mission manager, asks the operational decision manager, “here’s where all my targets are, what is my posture relative to them in terms of the law?” And then it outputs that. And the mission manager’s sort of a probabilistic model, then says, okay, it has an optimising engine called CPLEX Optimizer, also from IBM. So, we look at every individual interaction and then the whole corpus of interactions and it says you can choose from the following things that will allow you to remain legally compliant with the regulations you have to cope with at sea to be safe. And then it weighs, well, what’s my mission objective if I’m just going from here to there, I’m trying to get information about a certain type of plankton or if I’m following something, whatever it may be. And it sort of weighs that all up, and kind of like a Kalman state filter, and then picks which one is the most effective at remaining safe and advancing on its mission, whatever that may be. And it does that constantly in a never ending loop to make sure that it never causes or is engaged in any sort of an incident at sea.
BK: Wow. I believe we could, and I know you could probably talk about this for hours and hours because the technology is so advanced and so specific.
BP: Don’t tempt me.
BK: But I know that a huge, huge objective of yours is the ocean and maritime. And so, can we talk about how you foresee this technology and the MAS itself impacting or changing the maritime industry as well as others?
BP: Sure. Well, it’s a big question. So, I’m really interested in the autonomy part, the A.I. part, the sort of “can we really make it do this, and will it be of any use, and will it be reliable, and will it work with people well, will people work well with it?” That’s sort of critical because we’re not trying to get rid of people on boats. That’s not what we’re after.
BK: Hmm.
BP: And economically, the driver for fully automated unmanned vessels in the commercial space, I don’t actually see that yet, right? And certainly not on things like containerships, right? The crew is a tiny fraction of the total value of the vessel. And it’s basically a negligible cost to have them there. And then you go to the far other end of the spectrum, inshore waters, where maybe you want to do a bathymetric survey. There’s lots of boats and lots of talented people, and so, yeah, you could use a robotic system to do it, but you still have to have people engaged in sort of deploying it and making sure it’s being safe and fixing it when it breaks. So, sort of two ends of the spectrum. It’s hard to see the economic argument. And then in the middle, it’s sort of up for grabs.
So, we see it really as a research optimising tool. And we’re not really—because we’re a nonprofit—ProMare is a nonprofit that’s funding it—there’s no return on investment for this. We’re giving all the data away that we collect about everything we do as part of our mission. So, what we want people to do is maybe think about what’s really possible and that you don’t have to spend as much money as you think to do really substantive research at sea about the ocean and about what the health of the ocean as well as fundamental science and the climate in general.
So, that’s what we want as a legacy. And how you do this if we have limited resources. So, we have major states with money, have big research vessels and many of them. But, I say many, but you’re talking about a handful, a dozen, right? Big research vessels that go out and do some of the groundbreaking research about how our planet, the dynamics of the whole planet and the ocean and the climate, work. And we just don’t have enough money to build enough of them to get the data we need to make the information that we can act on, to have a thorough understanding of our environment and to do our best to protect it, to be good stewards of it. So, what we need to do is find another way to get more data.
So, the A.I. side of it building robotic systems that are sort of from robotic, simple, deterministic, fully automated, sort of unmanned and then autonomous is sort of the tiers. That technology is getting very cheap. If we can push that out everywhere around the world, it’s democratising in many ways because more people can get engaged. Just like 20 years ago, there was no such thing as a drone. Now you can go to a toy store and buy one for $99. And some of the things they can do were science fiction 20 years ago, right? Unbelievably sophisticated. You know, I grew up with a phone in my house. I had a rotary phone when I was a kid, right? Yeah. So, I mean, it’s changing fast, but it’s democratising if it’s done well. And what that means is we can get more high quality data that can contribute openly to the corpus of knowledge about our planet. That’s how it will change things.
And then the interesting confluence is we’re seeing the proliferation of companies working in space, not countries, that, too, but companies having access to low cost, near its orbital satellite launch. Well, we’re working with some of them, so that when satellites are zipping around over the planet, we can get data from them about what they see on a big scale in the ocean and they can communicate with their little A.I.s to our little A.I. on our ship and they can collaborate and say, “hey, I saw something weird and you’re almost in that area. Could you deviate? I think you could do it.” And then our ship can go, “oh, that is weird. That’s on one of my sort of board of mission things of interest for my humans. They might want to know about that.” And it can choose, without anybody telling it yes or no, to deviate and understand, well, okay, the weather is like this because I talked to the weather satellite and that means I’m going to burn X more energy while I try to get there. And my primary objective is Halifax. But I yeah, know it’s going to be close, but I can get it. Is the data that important? It is. The satellite zings around again. Says, all right. I’m over here. I’m at that spot. I’ve deviated. I’m here. I checked. You’re right. There is a weird plankton bloom here based on the colour from space. I’ve taken a sample. Here it is. Here’s what I found, using a holographic microscope that’s on the boat.
So, they’re literally collaborating, creating very rapidly, information that then is actionable globally by scientists that have an interest in it.
BK: And the things you’re saying, they do. It does sound so futuristic, but you did in this explanation mention humans. And so, that does lead me into how humans are playing into this monitoring system and what is the response of control of the ship and their role with it?
BP: Well, that’s interesting. So, humans are—so IBM has often said, we really like it. They don’t consider A.I. artificial intelligence. They consider it augmented because the purpose of it is to help us be better humans, right? So, it does the things that are tedious that might take us a lifetime to collate just some data, because we have a huge explosion in data. Well, we need to be able to make information and it needs to be communicable and actionable. So, we need machine learning to do that because as the data expands, our ability to cope with it diminishes. So, we need these sophisticated tools.
But humans are the creative part. Humans are the intuitive part. Humans are the things that—you can get all this information, but somebody has to have that “aha” moment, right, that’s still beyond machines and understand what it—not what it means from a mathematical analytical perspective, but what it means to life on the planet, what it means, how you feel about it, what can we do about it, come up with creative hypotheses. And so, we’re letting humans be better humans because they don’t care about the rudder. The rudder, the computer’s got the rudder. Who cares, right? Why do I care about the rudder? The only time I care about the rudder is when it broke and the machine says, Help, I’m going in circles. And I have to say, well, why is that happening?
BK: Now, would humans intervene in that moment—
BP: Oh, yeah.
BK: Would someone be available to correct?
BP: 24 hours a day. The first voyages, we’re going to be monitoring it 24 hours a day, seven days a week, because we’re worried about it. It’s kind of taken on a life of its own. And it’s quite possible it won’t make it at all. I mean, that would not be great, but we’re going to learn a lot. And the goal isn’t—the voyage is to learn. And if we don’t make the voyage, we’re not going to learn. If we don’t complete the voyage, we’ll still have knowledge at the end, which is really important. So, humans will watch it all the time because we’re still learning about it. We’re still putting these very complex virtual and real machines together. So, this is a sort of a virtual—I don’t want to say virtual machines. It’s a technical term—so this is an A.I. system that sort of lives in the ether, so to speak, in a computer. And it’s going to act in the real world through a sophisticated set of robotics. And some people like to do digital twins. We can do that. We’ve been doing that sort of, well, what happens if we do this to it, what happens if we do that to it, in sort of a parallel simulation. We can just cheque all that all the time. And then but we have the thing acting in the real world. So, we want to watch it. I can make anything work in a simulation. The ocean and the world is far less predictable than the simulations we create as people to test.
BK: That’s exactly what I was going to say. But there’s the unpredictability of the world and the actual ocean.
BP: Yeah. Imagine how boring it would it be if things were predictable. What would you do?
BK: Agreed.
BP: Yeah. So, it’s fascinating. So, we go out and we’re going to watch it. We’re going to learn things. And so, we’ve got people who’ve written models from IBM Research and several research institutions and universities who’voe created these amazing models of whale song that we’re deploying on the boat. And the boat’s going to be listening for these things and trying to identify different species and number of animals. And where are they? What are they? How many are they? Can we detect a specific animal? You know, they are just interested in that.
Then we’ve got other people interested micro plastics and other people interested in plankton and other people that just care about acidification or O2 and CO2 content of the water and all sorts of different things like that happening real time. So, there’s all those scientists are begging us for more bandwidth because they want all their data. They want to make that information either on the ship or they want to get it off and make it on land or both. Right?
And then they want to push back to the ship and say, “oh, my God, you found this strange thing. Are you still seeing that weird?” Whatever it is. “Are you still hearing that song? Are you still hearing that sound? Are you still near that weird pH or weird reading we got? Can you get me more?” And then the ship might say, “well, yeah, I could just stay here, or I could stop, or I could go in a circle or I could zigzag so I spend more time in this area.” You can do all those things and we want it to start making those decisions. But we want to watch it. We want to validate that all the things we’ve been testing about it being safe while it does this are true. And it’s more than likely it’s going to get stumped because you can’t think of everything, so, it might come into a situation where it says, “I don’t know what to do.” And then we’ll have—and it’ll ask us for help.
BK: Okay.
BP: And that’s okay.
BK: Right. Yes. That’s what I was wondering, too, is when, you know, the communication back with the humans and then if there was or would be any real time, we’ve got to get to the vessel or if you or will you have people ready and standing by if they’re needed to be any assistance there, or is it capable of fixing itself?
BP: Well, it can fix itself. That’s an interesting question. So, certain things are highly resilient and redundant on the vessel. So, it has a slightly more sophisticated form of braker. Like, you know, when a light goes out in your house, like the kitchen stops working, so you go, and you reset the breaker. So, it has breakers that are automatically resettable. And there’s a routine. Somebody was responsible for writing a programme that controlled the breakers, that if one opened, it would try to restart it a certain number of times over certain periodicity. And it would look at the current draw and it could infer from that, hey, maybe there’s a ground, so, I’m going to secure this and not use it at instrument’s dead. So, there’s that kind of resilience. And then dual redundancy of those systems as well.
And then the parts that aren’t and even the A.I. is as multiple instantiations on the boat. And if worst case scenarios, it just gives up the ghost, the A.I. stops working at a very high level. We can drive it like a big remote-control car directly from land.
BK: Oh, fantastic. I mean, I’m sure that’s going to be fun for somebody, if that—
BP: You’d think that, but you know when you’re 1,000 miles offshore and there’s nothing there but water going up and down and you’re looking at a screen, I can tell you it will make you queasy. And it is immensely boring. And that’s why A.I.’s important. It doesn’t get bored, ever.
BK: Right.
BP: So, yeah. So, the things that really scare me are none of those things. I worry about monofilament line in the prop. I worry about we hit a floating container or a submerged container that you can’t see, and it jams the rudder, and we just do circles. You know, that’s the kind of thing that I worry about, silly things. Or the five-dollar gasket that we thought was more than adequate, and just, we got the one bad one in a lot of 1,000, and it fails, and then we have a water leak on a switchboard, and now half the science payloads are burnt up. You know, those kind of—those things happen all the time, right, and so on manned vessels, so we’ve tried to simplify it and make everything very robust and redundant, but there are certain things that if they fail, that’s not going to work.
BK: So, to that point, at worst case scenario, if something were to happen with the rudder, say it was going in circles, and you’ve got the two Hexagon positioning receivers aboard the MAS – what information would it provide to the humans who are monitoring it?
BP: Well, the good thing is that because we have those Hexagon systems, we always know where it is with great precision, accuracy and precision. So, we’re going to know immediately if there’s a problem like that. And then second, okay, it wouldn’t be ideal if it just did lazy 1,000 mile diameter circles in the ocean or whatever it was. But we’ll still collect data. We’re still going to learn a ton. We’re still going to—because of the IMU, the Inertial Motion Unit, coupled to these fantastic Veripos, Hexagon Veripos systems, we can still do sea surface height measurements. And that’s important for climate change, to look at sort of corrected measurements for the shape of the ocean, essentially. Right. And that gives you sort of how much difference has there been over time? And we want to know that stuff because it matters for low lying areas near the ocean on land. And so we’ll still have all that data. And somebody said, well, “what if the propeller falls off?” Somebody asked me the other day. Not going to happen, but what if it did? You know, okay, well, it’ll drift, right? And it will slowly crash into Ireland. You know, I’m being facetious. We’ll wait until it gets closer, and we’ll get it. But all its power systems will still work. Its lights will be on, its AIS will be on, its radar will be working, all its science payloads will be working. We’ll still be talking to it through the satellites. And so we’ll just get a lot of data very slowly until it gets to a point where we could retrieve it.
BK: Which is ultimately the goal, the data collection and the learning. That’s the ultimate goal with this vessel. And to that point, and I know you’ve mentioned a few of these, but are there other technologies that you would like to mention that you’re partnering with? You did name a few, but are there any specifics that you would like to go into?
BP: Well, there’s so many. I mean, we’ve got great stuff from IBM, great stuff from Hexagon. We’ve got Chelsea Technologies providing floor—I think they’re providing us a fluorometer. We’ve got IBM in Switzerland with the university in Geneva building a holographic microscope so we can take pictures of tiny little critters, plankton and know what they are and do speciation and population density real time, which is awesome. And then we’ve got great hydrophones from RS Aqua. We’ve got a water sampling kit from RS Hydro. We’ve got, gosh, everything you can imagine. What else do we have? It’s just the list is long, but we’ve had so many great sponsors. But really the big one is IBM and then Hexagon is the key enabling partners.
And then, gosh, the solar panel technology is from a company, Solara, in Germany is amazing. They made these fantastic flexible, adhesive backed, very high performance marine rated solar panels that we could just stick to the hull and they’re nonskid so you can walk on them and not slip if you have to walk up onto the boat to change out a cable or light or something. So, the technology’s amazing that’s on these things. And gosh, what else do we have? You know, the model makers from University of Plymouth, the people at Bridgewater State, Massachusetts, the US Coast Guard has been unbelievably helpful because they don’t have a comprehensive set of rules for vessels like this. So, they’ve taken this really wonderful, proactive approach about, well, we’re going to have to learn about this and if you’re paying for it, so, we’re going to help you figure out how to come into US waters safely. And we’re going to learn a lot. And they’ve just been fantastic.
BK: A lot of partners.
BP: Yeah, lots and lots and lots and lots of partners.
BK: Which is exceptional. This is definitely an endeavour to get excited about, which I can tell you’re so excited. You’re going to show us the truth of it all in this adventure. So we will be following along this journey very closely.
BP: The good thing for Hexagon is no matter what else breaks, that stuff’s bulletproof. And your job is to tell us where we are and where we’re pointed. So, that’s always going to work. And so, that’s a good thing.
BK: So, at least you’ll know where you’re going.
BP: At least we’ll know where we’re going. Very important.
BK: Well, you’ve mentioned the technologies that are observing the ocean, but do you have specific goals for the oceanic research as you journey from Plymouth, Massachusetts to Plymouth, UK?
BP: I don’t, because I’m really interested in the sort of higher level sort of, hey, I wonder if I can do this, and can we get it all together and make it work and have it be safe and sort of the robotics and the programmatics and the assembling the higher level systems. That’s where my head’s at.
But what we’re—I guess, you know, maybe my inspiration for it came from when I was a kid. I was really enamoured with the space programme, US space programme. And so, I was born in 1968, so I sort of missed the Apollo heyday. But I remember when I was in the fifth grade, I wrote a letter to the NASA director asking him questions about the space shuttle. And they wrote—and he—wrote me back directly, a handwritten letter and sent me all sorts of information and photographs. And it was like to me it was like a watershed moment in my life. And what we’re doing pales in comparison to the giants that those engineers were and are.
But I think of it in terms of like a space shuttle for the sea. So, we’ve got payload bays for other people’s things. So, just like the space station and the space shuttle took other people’s research to space, my research aim is in the sort of complex robotics and autonomy. But we want to use that to enable other smarter people to put their things out to sea, where maybe they couldn’t afford it before and there just was no access before, or they couldn’t get in the right team or in the right university or on the right ship cruise. You know, there’s lots of people with great ideas that never get that opportunity. So, I look at it that way. It’s a space shuttle for the ocean.
BK: That’s exceptional. And I hope you hung on to that letter. You still have it, right?
BP: Yeah, I have it somewhere. It’s back at home in Massachusetts, with all my childhood things in my family house. So yes.
BK: What a cool experience for a guy in fifth grade. That’s wonderful.
So, okay. As far as the research goes, just so I can dig a little bit deeper, you know, the ocean is two-thirds of our planet, so I’m assuming that they will hope to start learning some things that we just don’t know. Is that correct?
BP: Well, yeah. I think it’s all about data, right? Every time, so, every time we go out in the ocean, we find something we didn’t see before and we learn something new. I mean, universally, I would say the one truth about oceanic research and exploration is that every single person who goes to sea on any research cruise finds something that no one else has ever seen before, period. Right? So, a lot of times I think young people specifically grow up feeling like everything’s been done and everything’s been explored and that there’s nothing left to learn. So, the vast majority of the planet is wholly and completely unexplored. Right? Just period. That’s it.
BK: Right, yes.
BP: And nobody says it. And so we look out at space and, you know, it’s an interesting conundrum because the ocean’s accessible, right. It’s right here. You can go to the beach, get in it. So, it’s much harder to get to space, but the ocean is a much more hostile environment, and people don’t think about it. So, it’s challenging. It’s challenging in every way, and we wish people took up that challenge more so from the physical sciences, engineering, just making things that can do deep ocean research is a challenge, right? Powers and SU communications is an issue. Data collection and processing is an issue. So, for us, every time you go to sea, it’s something new. We just want to reduce the cost of doing it and give away all this information, data and information and the knowledge we have about how to do it so we can facilitate more people doing exactly this and then sharing without cost all of that data so that we all better understand what’s going on.
BK: And you are not going to stop at this maiden voyage, correct? What’s the next journey? Do you already have a list of things that you’re wanting to tackle?
BP: Yeah, we do. So, we got, we were thinking about the Arctic, but maybe later, because that’s pretty tough. We were going to come back at the end of the summer, but we’re not going to come back to the U.K. We’ve decided to stay in the states over winter because we’re going to be in a stop in Provincetown and Plymouth, and we’re going to go up to Boston for the Fourth of July. And, because why not? That’s where I was born. Fourth of July will be a good time. And then we’re going to go down to Washington, D.C. and right into the city. At the Capitol Yacht Club, we’ll be berthed there at the end of July. And then we’re going to go to the Sea-Air-Space conference. I think it’s an Alexandria. It’s just south of D.C. on the Potomac at National Harbor. We’ll be there talking to people and folks from NASA and folks from different organisations and bringing the ship. And then we’re going to go back up the East Coast. So, we’re going to collect data the whole way through the Chesapeake Bay, out into the ocean, back up to Massachusetts. We’re going to stop in Plymouth. We’ll fix anything that breaks, because that always happens. Then we’re going to go to Halifax. We’ve been invited to Halifax. So, we’re going to pay a port call to Halifax, and we’ll stay there for a week or two and do some research locally. And then it sort of gets a little murky. After that, we’re going to do a little bit more work in that sort of Gulf of Maine, Cape Cod area and then Virginia, back down to sort of the Norfolk area. And then we’re contemplating overwintering in the Gulf of Mexico, working, doing the oceanographic and climatological research as an asset down there in the Gulf of Mexico for universities. And it’s got to go somewhere for the winter, so we might as well go down to the Gulf and spend the winter there. And then we’ll come back to the UK in ’22. And then the city of Marseille is super excited. They are talking to our ProMare leadership. I’m one of the board members. And I’m sort of a little focused on the ship right now, but I guess then they want us to come down to the Med in the spring of ‘22 and do some research in the Black Sea, all around Mediterranean, tough places, Corsica, Sardinia, the Cote d’Azur. We’ll suffer through it somehow. And then after that, I don’t know. I’d like to go along, you know, we’ll do a transatlantic voyage and back. I’d like to do a long north-south voyage. I’d like to go down to St. Helena and come back. That’s a long way down. That’s sort of—
BK: MAS is very, very busy, Brett. How are you going to be in all these places at one time?
BP: My wife likes it when I’m out of the house. So, no. I think we have lots of people helping and it keeps growing. You know, the one thing about the project that I probably love more than everything else is how helpful everybody is. I tell people all the time it’s only this exciting because so little happened last year, this past year. But people just seem to like it. And I think people like that we’re doing something and that we’re willing to take risks and that there is no return on investment, not fiscally anyway. And so it just it really is the absolute altruistic pursuit of knowledge. And that isn’t happening a lot these days as far as I can see. There’s no political agenda. It’s just for fun, right, to learn, and so I think we’ll have plenty of volunteers. I mean, we can barely keep track of the number of people who offer us help now. And that’s the goal of it, right, is bringing people together. And maybe if we must, we’ll build something else. There’s a second one kind of taking shape in the back of my mind already.
BK: You beat me to it, Brett. That was my next question. What’s next in additional vessels? What would their design be, or their goal be in creation?
BP: Oh, well, more of the same. But, I’m really thinking that where I want to go next is with a few more vessels, maybe smaller but deeply interlinked with new satellite technology, so not one without the other, sort of doing collaborative space-based what we would call sort of cross-domain, multi-domain research, so from space to the sea surface to the subsurface of the sea, working together in unison, collaboratively providing data and information to disparate parts of the world’s oceans in real time, in a way that’s never been done before. And I’ll tell you that actually to me, and this is where you’ll think I’ve diverged into madness, is that, to me, is a corollary for extraterrestrial exploration, for other bodies, solar bodies. So, Insettelis, Io, Neptune, things we’re never going to put—we’re never going to put people up there. So, it’s not going to happen. Not in our lifetime. So, what we can put a cluster of 20 CubeSats and surface detection systems and rovers. And if there’s an ocean somewhere out there into that water, somehow people are thinking about it, this is a corollary to figure out how all those things work together to pursue the research objectives that are interesting to people. So, maybe that’s a little far out.
BK: No. It sounds exciting. And I think we all think about those things. And you’re talking about not only thinking about it but putting all of this imaginative technology into application and actually trying to find answers, because we all really want that.
BP: Yeah. That’s the only thing that matters at the end, is what you do. And you know, I don’t know. I get different questions sometimes that worry me. I often get asked when I give a lecture on this is like how I got permission to do this, which I find troubling and bizarre. I thought it sounded like a good idea, so we’re doing it. And, you know, you have to take agency in your own life. You know, some people look at how long they’re going to live, which is important because it’s a finite amount of time. You don’t know what it is, but it’s finite. So, as a matter of course, it’s important, but it’s what you do in that time that gives your life meaning. Right? And we’re a long time dead. What’s the worst outcome of a research experiment that fails? It won’t matter 100 years from now, but if it succeeds, it will. And so, I never understand why not put it into application. Just do it. How badly can you fail? I mean, and why does that matter
BK: Right. Well, it’s the age-old adage of failure teaching you. And is it Thomas Edison that failed 1,000 times before he discovered the light bulb. And it’s completely changed humanity in the way that we live. So, I think it’s so important to make attempts. And I think even for young people to see, like you were saying, is there a purpose? Is there somewhere to explore? And knowing that there really, truly is right here where we are on planet Earth, but then also using that technology to continue to expand what we know beyond the earth, and giving people hope that that we can, you know, answer some questions that people have been grappling with, like global warming and, you know, saving coral reefs and things that are vastly important for the ecosystem of where we live right now.
BP: Oh, totally agree. We can get some more perspective, you know, and that’s important in any life. One of the things I guess it’s interesting technology. We keep talking about technology in a good way. And it is unbelievable what we’ve been able to achieve as a species technologically in the last, say, 50, 60 years, really say since around 1969, when we went to the Moon. My grandmother lived to almost 100. She’d never been on an aeroplane. She was born before there were aeroplanes, period. At all. That’s amazing. So, we’ve come a huge distance. But the other side of this is, you know, when we talk about doing things, putting things into application, which I think is really what matters at the end of the day, social media is an unbelievably great platform to sort of disseminate information and knowledge, but I also think it’s an opportunity. It’s something that prevents people from acting, right, because now there’s multiple platforms where anybody can call you a moron 24 hours a day. And you know what? All those people you don’t know that have an opinion about whatever it is you’ve done or said don’t actually exist in reality for you. You’re never going to meet them all. And their opinion of you isn’t important, right, but it’s imbued with this unbelievable currency in the makeup of a young person’s ego. It’s a real problem. So, we got to get to that because nobody wants to be mocked wildly. But I would tell anybody who’s afraid about failing that you get to choose whether you care what someone you don’t know thinks about it. Right?
BK: That’s exactly right.
BP: You don’t have to care, right?
BK: Right. Of course, of course. And you know, as we’re kind of moving along in this conversation and we’re discussing how people make you feel, let’s really talk about the feeling you guys have right now. You’re looking to launch very soon. So, what’s the overall vibe, I’ll say, on your team and the community of Plymouth.
BP: Terror. Hope and terror.
BK: Not what I was expecting, Brett.
BP: Hope and mixed with a good deal of scepticism and not terror. I mean, we know we’re not—you know, nobody’s going to be hurt, right. Nothing bad is going to happen. Nothing bad is going to happen. And you know what? Sometimes bad things happen, and that’s okay, too, right? You deal with these things throughout the course of your life, but nothing bad is going to happen. And so, we just, we want it to work, you know? And I think it’s the, you know, a little bit with me, I stay up a lot sort of handwringing about , did we test everything enough? What about the rudder? Did we do—is the bearing all right? Did I forget? What did I forget? What did my engineers, who’voe been working so hard, what did they forget? Are they too tired? You know, did we, you know—and we’re sort of head down right now to the point where we’re not looking at it. And when it sails off like we all know it’s going to go, but I think that there’s always, I don’t know, there’s always some denial. Like he’s not really going to send us across the ocean, is he? It’s like, yeah, he says he’s going to do it. Like I can hear that conversation in my mind. He’s like, not seriously, right? We just finished it. And it’s going to go now? What does he know? You know, there’s probably a lot of that. And, you know, it’s—
BK: It’s the one person waiting to press the launch button. Oh, are we going…? Yep, we’re going to do it. Okay. It’s going to go.
BP: Yeah. Really? Yeah, there’s a lot of that. And, you know, the chief engineer on the project I’ve worked with for 20 years, Rob Shaw, a great guy. His son is one of the engineers that’s working on it. And he was laughing the other day. We were talking about it. The company that’s building it for ProMare, a year ago the average age was, like, 48 in the company—or two years ago—almost 50. And now it’s like 30—
BK: Wow.
BP: —because we’ve recruited so many young people that we’re trying to bring up. And they get to do this, right? This is like the first project they’ve worked on outside university. And so, we’re kind of spoiling them a little bit, right, but—
BK: No. You’re starting them at the top, Brett.
BP: Well, we’ll see. I mean, but they’re great. But he was laughing the other day. He said, “you know, this whole thing’s been built by children.” You know, so it’s like—they’re all half our age, right? So, it’s fun. And I think that, you know, you just don’t get a chance to do this kind of stuff very often, and so they’re all super excited. But I think there’s also that little bit of disbelief, like really? It’s going to be finished and then just it’s going to go away? We’re not going to do that, are we? It’s like, yes, we’re going to do it. It’s going to go. And so there’s a little appre
BK: Wow. This is a lot to look forward to. Do you have any kind of parting thoughts or just mission goals as we leave this conversation today?
BP: I guess, you know, we’re doing this because we want to and because we think it’s going to be good for the environment ultimately to know more about the ocean. So I would tell anybody, if you’ve got an idea like that, you should just get out and do things. Put the phone down. You can do things like this. Right. There’s a lot to be explored and we need you.
BK: I like that.
BP: Yep. So, the world may not seem it now, but it’s fraught with opportunity. You just have to be willing to dig in. So, give it a try and—
BK: Yeah. And just be proactive, right? Take initiative. Make it happen.
BP: Yeah. And it’s okay to fail. You probably won’t. Most people never hear that. And even if you do, the consequences aren’t really going to be very bad in the grand scheme of things. And if you have any great ideas for science on the ship, reach out. We’re always looking.
BK: Brett, how can we follow along on the MAS journey? Is it possible to follow along?
BP: Yeah. MAS website is—I’m going to be old by saying this now—www.mas400.com. If you go to that site, there’s a dashboard there and there’s all sorts of stuff about the ocean and the technology on the ship. There’s sort of going to I think it’s actually active now. As of the other day, we got all the systems interlinked and broadcasting, so now you can kind of see where the ship is and what’s active and what isn’t and what it’s doing. All that information is going to flow through that portal for anyone to see or use. There’s all sorts of great footage of it in testing. There’s all sorts of links to different companies and individuals and researchers and universities that are helping. And that’s the place to go to follow it.
BK: Wonderful. Well, a big, big, big thank you to Brett Phaneuf for joining us on this episode of HxGN Radio. Please be sure to cheque out all of our latest episodes at HxGNSpotlight.com or on Apple Podcast and Spotify. Thank you for tuning in. And Brett, thank you so much for your time today.
BP: Thank you. It’s a pleasure.
