Smart Talks with IBM: The Mayflower Autonomous Ship: AI and Automation at Sea

matter the industry. Join hosts from your favorite Pushkin Industries podcast as they use their expertise to deepen these conversations. Malcolm Gladwell will guide you through this season as your host to provide his thoughts and analysis along the way. Look out for new episodes of Smart Talks with IBM every month on the I Heart Radio app, Apple Podcasts, or wherever you get your podcasts. And learn more at

IBM dot com slash smart Talks. Hello, Hello, Welcome to Smart Talks with IBM, a podcast from Pushkin Industries, I Heart Radio and IBM. I'm Malcolm Blobwell. This season we're talking to new creators, the developers, data scientists, c t o s, and other visionaries who are creatively applying technology and business to drive change. Channeling their knowledge and expertise, they're developing more creative and effective solutions no matter the industry.

Our guest today are Brett Fanoff and Don Scott. Brett and Dawn are responsible for creating the world's first unmanned, fully autonomous ship to cross the Atlantic Ocean, a research vessel they've dubbed the Mayflower four hundred. Brett is the director of the Mayflower Autonomous Ship Project and Dawn is the CTO of Marine AI. On June thirty two, the Mayflower four hundred successfully completed its voyage from Plymouth, UK

to Plymouth, Massachusetts. It's both an homage to the original Mayflower, which crossed the Atlantic forundered years earlier, and a bell weather for the ways autonomous technology will push the boundaries

of maritime exploration in the next four years. On today's show, the Unlikely Origins of a self directed Ship, some motion misadventures, and what AI and machine learning will mean for the future of seafaring and beyond, Brett and Dawn spoke with Lauren Ober, host of the forthcoming Pushkin podcast The Loudest Girl in the World. Lauren is a longtime radio host and reporter, helming shows like NPRS, The Big Listen and Spectacular failures from American public Media. Okay, now let's get

to the interview with Brett Fanoff and Don Scott. Don and Brett, it's really great to be talking with you guys today. I was wondering for each of you, what is the draw of the sea? I mean, it's like this expansive place. It feels so unknown in so many ways. Um, but I'm curious, like, what is the allure there for me? It's I wanted to be I wanted to do aerospace, so I always feel like I'm like the poor cousin of aerospace. But it isn't. It's actually it's harder to

to do the underwater stuff. It's closer. It's just harder than being in space. It's it's incredibly hostile and wildly unexplored.

And why what I like about it is that you know, you can take a bucket and go down to the beach, get a bucket of water, analyze the bucket of water for the next twenty years, and you know, chances are pretty high you're gonna have a couple of things in there that nobody's ever seen before, and that's every bucket of water everywhere in the world, right, So I like the idea that you get to discover something new all

the time. And it's also hard. It's a difficult place to work, so it challenges you to come up with new ideas and new ways to do things and new materials, and that's what I like about it. I don't know, don what about you, Yeah, I mean, um, there's obviously an allure and draw there's some great descriptions about why people are drawn to the ocean. Talk to the authors and the poets, you know, it's it's definitely a real

sort of visceral feeling that people get. I think you're find that the people that are involved in ocean engineering and or marine sides like that. You don't just sort of fall into this career by accident. You make proactive decisions to get involved in that environment. So you have a bunch of people working there that that want to be there and sort of have this uh understanding of that this is the place they want to be and

this is where they want to work. So that becomes a very very positive work environment workspace because everyone's they want to be there, So there's that. Yeah, it's highly collaborative, isn't it. It's um like anything, there's personalities, but it tends to be a lot of fun more than anything else. It's challenging in all the ways that make life interesting. And then it also tends to be a good time. And you can't work in the ocean by yourself, like, well,

you can, but it's kind of hard. So, like Brett said, it's an incredibly collaborative environment. I mean, if you want to be doing anything of significance, you have to be working as a group because you need to rely on each other. It is an incredibly dynamic, hostile environment, very humbling. So you find you you're going to achieve success as a collaborative group as opposed to some sort of lone

wolf type out to right. Okay, so we're here to talk about the Mayflower Autonomous Ship project, which obviously is very cool. Um, how exactly did you guys decide to build an autonomous ship and then model it after the Mayflower? I mean it was just to hold my beer kind of thing. Um, I'm sure what it really is, it really was, it really was. Yeah, what it really was is it was so in meeting with the City of

Plymouth on something else. They were talking about what they were going to do and maybe build a replica ship, of which there's already one. And I thought that wasn't the best idea. And you're talking for anniversary. Yeah, And so I was a little bit indelicate in my comment as to how they wanted to proceed with a possible replica. Think you said it was a stupid idea, I said,

I said it was stupid. And uh, and there was more I couldn't resist and and and I said, there already is one, you know, And it's it's just I grew up near there. And and so they said, all right, smart guy, what are you gonna do. I was like, oh, we should build one that challenges us technologically and from an engineering perspective and sort of invokes the spirit of the original risk taking and do something that informs the

next four years. And everybody was like, yeah, you should do that, and I was like, you know what, I will hold my beer. And so so I called Don after the meeting and I was like, oh, Don, we

we have to build an AI. I need Captain Watson because we're going to build an A ton of a ship across the Atlantic, and he was like great and so yeah, and it was just that literally, that glib, but it also I mean, he and I have been working on unmanned systems and autonomous systems for a long time together, twenty plus years, and so I wanted to see where we could get to, like, how hard could this be? Right? I mean? And AI, sure, let's do it. Then,

So we built a ship. You mentioned capturing the spirit of the original Mayflower Journey, and I wonder what exactly where you're trying to capture. Was it the spirit of taking risks or was it doing something that hadn't been done before? What we were trying to do. We knew it was really hard, right like, and it was a huge amount of risk to undertake it. Press the real risk taker. He's the one with the big ideas and

wants to take the risk. I'm I'm a little more cautious and sort of pragmatic in the sense of, Okay, what's going to take to do that? We we actually didn't think we were going to make it, or I fully expected at some point the ocean we get annoyed and mighte us, you know, pilgrims like that to me is what's interesting. The pilgrims took a risk, right, So every one of them fully expected that they would die

if not on the voyage within like the first year. Right, That's how it was, and it was worth it to them to take that risk. So our risk is infinitesimal by comparison, Right, it's tiny. What was our risk, really, We'd lose a ship we spent some money on. So what the knowledge about how to approach these problems is, and the and the experience that you get to give people to take risk at that level from an engineering perspective is really important. Right, somebody had to do the

first open heart surgery and took a risk. Now we're not doing open heart surgery, right, No one's going to die. So what's appealing about the risk thing is it has a technical risk and environmental risk, and then there's a legislative and regulatory risk. Because we had to have our fights with various agencies about the fact that they didn't have a law that said we couldn't so they didn't get to say no just because they didn't want us to.

And at the same time trying to create a reliable machine and then some sort of an AI machine learning based system that would be safe whatever that is in the middle of the ocean. It's really interesting and gives people a lot to a lot of purchase for different people with different skill sets to collaborate. Brett and John started developing the Mayflower Autono, a ship in It took them six years to figure out both the software and the body of the boat itself. In that time, over

seventy people contributed to the project. Lauren asked Don and Brett what it really took to go from hold my beer to an actual ship? You know, it is mind boggling when you think of how many people are involved, how many people are touching this project, how many interesting minds doing interesting things, but you have to funnel it all into this one project. Well that I don't know

if it's that way. I mean, I guess you could say there was one project, but there were lots of projects, and so, you know, there was sort of the hardcore group of people that are trying to build the actual software that works, and then there's the guys trying to build the hardware and they have an interface, but they're

parallel pursuits that don't have direct overlap. And then we said yes a lot to anybody who wanted to help, because we learned from experience that most people don't last in terms of the ability to stick out four or five years focus on the projects very hard. And so the people that I wanted to stick it out and bring it to fruition ended up, you know, sticking it out and that was great, you know. And then there

are all sorts of different things. There was a group making a web interface so that they could show the world what we were doing, and you know, then there was a PR group that was marketing things and sort of talking about how we tell the world about it, and we would support them. But it's hard to describe it as one project. I guess would be my position. It's lots of interlinked programs, right, Sure, I get that, I get that. Can you tell me more about how

automate is built into the ship and how it works. Well, there's tons of automation and Mayflow, I mean Mayflower is like most robotics systems, right, So you peel it open and you find you know, programmable logic controllers and motor drives and also its of other things sensors and industrial automation that you'd see, you know, in an elevator or an escalator or industrial machinery for manufacture. And that's one

sort of layer of it. Right, So you've got the basic analog control, then you've got sort of a veneer of automation, and then what I would call sophisticated automation, which don and I have worked on for decades in the marine space. So all that's in there. And you know, Donn and I talked really early on if I just wanted to get across the Atlantic, we could have bought an old fishing boat, filled up the fisholds with diesel fuel, and put a cheap autopilot on it and sent it.

It probably would have got across. But so what it's not reducing risk, and it's not unburdening a person, and

it's not doing anything really clever or sophisticated. And so what we were more interested in was getting to a point where instead of having to tell it to do everything, saying go do this task right, a goal like go to Plymouth right, and then while you're doing that, oh, by the way, while you're doing that, collect all this science data and if you see anything unusual, tell us and and while you're looking for all these unusual things

and trying to achieve your goal don't hit anything. So then what role did IBM s technology play in all of this? Yeah, I mean their their technology is all over the ship. Probably the main contribution it was the decision making process or it's it's an automation TOOLM operational

decision manager. It's actually a financial services tool. It's for your making decisions about the viability of a transaction, whether it's fraud or order or alone or let's say, And we were being presented this by one of the ODIUM engineers, and I remember sitting in the room with Brett thing, what what in the world does uh financial services product have to do with marine navigation? And they sort of were brought to realize by the IBM engineer how this is.

This isn't really so much about financial services as it is about making making really difficult decisions in a really complex environment, which is what they do in financial services. But it's also exactly what we needed to do in re navigation. And when it's when the system was actually undering, it would create a log essentially of why that decision was made, so they can validate that decision and verify and validate that that that was in fact the right decision.

And um, so that's a that's one of the key

IVM tools that are on board. Well, one of the things you might want to consider about that is the fundamentals, Right, the theoretical independence of all the AI that we're deploying now have been sort of understood for decades, right, and so now we just happened to live in a world where the microprocesses are up to snuff that they can deplace some of these very sophisticated theoretical and reality and all of which IBM has been involved with from inception,

based on its pedigree is in the national business machines. There isn't an IBM product that I can think of that we haven't tried to utilize the deploying so it's it's it's everywhere in the ship. Yeah, I don't think a lot of people think of technology as as as a creative pursuit, but I imagine building an autonomous ship from scratch takes a lot of creativity. And I'm wondering,

do you guys think of your work as creative? Yeah, engineering is essentially designing technological innovation sort of do you think of it as a very logical process, and there is that, for sure, but there's an incredible amount of innovation involved too, Like there's no template for what we're doing.

And you know, we call it white paper design, where you're basically given a blank piece of paper and a goal, which is, okay, ship that's going to cross the Atlantic, Um, okay, come up with some ideas, right, So I mean it requires major conceptual leaps and then the technical skill to realize those those leaps. You're not going to make any advances just doing things the way you've always done them. Right.

You need to stretch right, and the only way it stretches what implementing new ideas, like you can spend a decade. We call it power point engineering right where you do nothing but think of things. We don't actually do anything, as opposed to what we call full contact engineering, where you actually built the boat, right, the software to go on the boat and send it out on the water. Get your kick like, get sea sick, you know, all that sort of fun stuff that happens when you're dont

see trials um. And because that's where you that's where the actual learning is happening, that's where the actual development is happening is being out on the ocean. Crossing the Atlantic is no small voyage for any vessel, but the Mayflower Autonomous Ship Project is more than just about sailing from point A to point B. Automation and AI have game changing implications for the way we design the next generation of vessels and the way these vessels will behave

and interact at sea. Ships will be able to gather data from the ocean by themselves, providing humans with critical information we need to address problems like global warming, ocean pollution, and our impact on marine life. For instance, the Mayfire four hundred can sample ocean water for microplastics and record audio of whale vocalizations. Taking the human factor out of a ship allows us to explore new designs and functions that haven't been imagined before. Lauren asked bread and Down

more about this. What are some of the benefits of having an unmanned vessel, like, how does automation push the boundaries of what we can do out in the ocean. Well, the few major apples right or through facets to that one is you can do some risky things when you don't have the people there right because no one's going to be lost at sea. And then the other thing is you can drive cost down, and I mean cost financially but also environmental cost, right, because you can use

a far less energy to accomplish a similar goal. And then what that allows you to do is have more Right. So instead of say having one fifty million dollar hundred million dollar research ship, which is the kind of numbers you're talking about to take scientists to see, you can have twenty or thirty or forty million dollars or two million dollar ships that go out and work collaboratively with space based assets and with one another and collect vast

amounts of data from disparate parts of the ocean. And then you use that data to create information that informs where you send the man vessel, right, so that they get the most out of their time at sea. So it's about enabling the people. It's about leaving the humans to do the uniquely human part, which is have the insight,

the intuition and and the creativity. And so you know, that's why it's important, and we're going to see an increasing amount of this, and I think it's also important for people to get comfortable with the idea that these things will be roaming around and that it's okay. Yeah, And and on an interim basis, I mean, we're also talking about this same technology that allows a ship to sail autonomously also can be used to assist a human crew now, you know, basically be another set of eyes

and years be a watchkeeper for a manned vessel. Right, I want to know more about the AI captain. How did you build it so that it would be comparable to the way a human captain might direct a ship. What we're trying to do is augment the person, Right, We're trying to let them be more of a person than sort of. They don't have to watch the radar,

they don't have to watch the cameras. Right. The machine can do all that, and then if it can't do something safely, if it can't come to a solution, it can ask a person send a little texic, I don't know what to do, and then a person can, in a very calm way, with no stress, tell it what to do. But in the in the interim, they're doing something more important, like looking at all the information that's

being produced by the instruments and having insight. You know, ever since we started sailing, there's been expectation of how ships interact with each other. Let's see, you know, they've been codified by the the I M O. Right, they're called like the regulations to prevent collisions at sea. We just called them coal ricks. But they're quite nuanced. Like it's not like they're called rules of the road, you know, after like the idea of like cars, but they're they're

much more nuanced than like rules for cars. How you act depends on the type of vessels that are interacting, like if it's a sail boat or a fishing boat, or a container ship or a pleasure craft. Like imagine if you're driving your car down the road and you're at a stop sign, and then depending whether you could go or not depended on whether the other car about the stop sign was a bus or you know, or something else, Like the rules change anyway. So that's where

humans are are really really good at. Is this nuanced understanding of these these rules, um squshy squishy rules. Yeah. So, and that's where we've done. You know, a lot of our lot of our work on is in that area. And that's the hardest part of this whole puzzle. I wonder if the ship ever got into any sticky situations that the AI captain was able to get it out of. One time, we had a sailboat come at us in the night head on reciprocal course, no lights on, no

radar reflector. Everybody was probably asleep and they just had the autopilot on and um, we easily could have speared them, or they would have actually hit us because they were in violation of regulations. But but that's common, right, And see, when you're crossing, it's so unlikely, it's so fast that you're going to run into somebody, but it happens. So we you know, the ship took appropriate action and moved so that that wouldn't happen. But it's not like it

seems very dramatic at the moment. But you know, you see these things coming miles away and it unfolds it like five miles an hour or something, right, So it's yeah, so it seems more nervous than it is. And I mean weather was challenging, and we had some failures technical and mechanical failures in the ship that were very very challenging. But from the AI captain perspective, the only time that

we got annoyed was. There was a research ship that shall remain nameless from a university that was coming along and was going to cross in front of us by ten twelve miles, which is fine, and they were going along, but they clearly saw us on there, neither their radar or their automated identification system which we broadcast, and they just at some point turned and came directly at us at a angle that it's the it's the I'm messing with you angle, Yeah, the angle that allows them to

maintain right of way but makes it very, very difficult to understand their intent and take action. So the ship was kind of like, if they had persisted, it would have ended up kind of going around in circles trying to avoid them. But but fortunately we had a support boat that was coming out of Halifax to meet it, and it physically got in between the Mayflower and this

research boat and so what are you doing? Oh, we were just going to take a look, and but we weren't going to get any closer than two miles and it's like, well, what are you going to see from two miles away? They absolutely are going to come over and take a much closer look because they didn't understand that the vessel was trying to avoid them. You know, when they see these unmanned systems at sea, they're just dumb robots, right, They just float around with winder wave power.

They are a bunch of sideists coming back from like a six week cruise, and there was like, oh, that looks interesting, let's go take a look. So yeah, and so that was the only thing that was annoying. Other than that, it was getting into and out of port. Getting out of Plymouth was a little challenging. Once we get outside twelve miles, we had a lot of fishing

boats to dodge, but that was fine. And then out in the deep sea, it's just it's mostly the sea that you're concerned with, and it's the fishing grounds are always the trickiest place because, yeah, because fishing boats do whatever they want. Yeah, and they're like container ships. They're not going to change course unless they have to, so you can pretty much understand what they're what they're doing.

Fishing boats could be going along a nice straight line and then all of a sudden do a money or worse, a ninety degree turn, and they don't care about you, and they just expect you to avoid them, and they literally there's no one in the wheelhouse. Probably they're all on the backs of the rules too, we're supposed to avoid them. And so, but what Brett caught it earlier, it was things evolved very slowly. Like things don't happen quickly at sea. It's sort of like, Okay, there's ship,

it's you know, it's it's twenty miles away. I've got a little bit of time to figure out what I'm gonna do. You don't ever try to put yourself into a situation where there's a risk of collision, so you make decisions that so you don't put yourself at that risk. Right, So, like I'm not going to cross the street at the busiest place. I'm gonna cross it dada, you know somewhere say, fishing boats, container ships, scientists on a cruise. The vast majority of vessels at sea are still of the not

autonomous variety. To wrap up their conversation, Lauren asked Brett and Don where the technology they've developed is headed, what it means for the humans who work at SEE, and what's next for the two of them. What do you guys think this type of automation means for the future of the maritime industry and people who work in at first of all, like we mentioned, Brett and I have both worked in the ocean community for decades our entire careers, Like we haven't a lot of respect for the people

that work in this area. And this isn't about a replacement technology. It's an augmented augment what's what's the right how do you say augmented intelligence? I mean, look, ships have always been the leading edge of technology and almost every society up until the twentieth century where we started into flight, and now they're kind of resurging into really new technological areas. But the point of trying to make is there was a time when there were no propellers.

There's a time when there are no rudders, right, it was just sales and steering oars. And then so it's been this evolution in technology um and ships have always been right at the absolute forefront of it from design and engineering and material science. And you know, we've seen this sort of long evolution of technology and this is

just another thing. So I think you're going to see lots of areas where really smart port of machine learning models helped like to improve efficiencies, and so we're at the advent of of a new way of thinking about design and implementation of very sophisticated solutions that are based in vast amounts of data analytics that are hitherto impossible to address. What is next for the Mayflower Autonomous Ship.

We may do a few things with the Coast Guard, and there's a few other folks that want us to do some work on national marine sanctuaries looking at cetacean populations, and so we'll do that kind of thing with with it, and more and more people will get involved in its day to day operation and we'll have less sort of

day to day input, which is fine. And then the AI Captain is going into a whole bunch of other projects and programs, and we're just starting off on a new design for a much larger ship for vast oceanic voyages,

um maybe even a circumnavigation. That's that's quite an effort. Yeah, And then we're going to connect with with NASA with the there you know, with the International Space Station and satellite networks and sort of have them work collaboratively so the space assets see things and they know there's another ship asset. So it's almost like a satellite in revers

It's like the inverse satellite at sea. So it sees something from space and it's as a ship such and such as over there, ask it to go and look at that and tell us if what we're seeing is right, or collect a sample right, and those things will work collaboratively without people. You kind of opened up Pandora's box here. So we did this, and now there's all these other things that we can do. So yeah, and we just have to pick one that we can do within the

remainder of our lifetime. There you go. Well, I I hope you. I hope you both get to do all the new things that you want and have capacity to do. Thank you both so much for your time and good luck with future journeys and projects. Thank you, hi everybody. In the centuries long evolution of maritime technology, the Mayflower

automous ship represents an inflection point. The ship's success indicates that artificial intelligence and automation are tools ready to be normalized within the nautical industry, and that the advantages they provide will change the way we conceive of ship building. But the technology aboard the Mayflower four hundred has implications

beyond just application at see. Brett and Don's project has shown that the potential reward for innovative risk taking is to achieve something unprecedented, and that's true for any industry. But like the original Mayflower Voyage four n years ago, it may require a leap of faith. On the next episode of Smart Talks with IBM, what does it take to create a sustainability focused global supply chain innovative and

equitable enough to connect our modern world? We talk with Sherry Highness, IBM's global sustainability services leader and offering leader for a sustainable supply chain. Smart Talks with IBM is produced by Molly Sosha, David jaw, Royston Reserve, Matt Romano, and Edith Russelo with Jacob Goldstein. Our engineers are Jason Gambrel,

Sarah Bruger and Ben Tolliday. Theme song by Gramascope. Special thanks to Colly mcglory, Andy Kelly, Kathy Callaghan and the eight Bar and IBM teams, as well as the Pushkin marketing team. Smart Talks with IBM is a production of Pushkin Industries and I Heart Media. To find more Pushkin podcasts, listen to the i Heart Radio app, Apple Podcasts, or wherever you listen to podcasts. I'm Malcolm Glacko. This is a paid advertisement from IBM.