The Business of TechSailGP's chief technology officer Warren Jones goes deep into all the ways he and his team have integrated digital technologies into the very foundation of the sport changing the nature of racing.
Plus, the ramifications for New Zealand and the world-at-large of the technology billionaires buying their way into US President Donald Trump's good graces.
The Business of Tech is sponsored by 2degrees for Business.
We go New Zealand absolutely flat out at the top of the line.
They're going to struggle to control the boat with those big foils. From here.
France on the.
Insight should lead at mark one, but it's going to.
Be a sprint, and we are often racing here in New Zealand.
Ah.
Yes, nothing says summer like watching Team New Zealand foiling its way across the hierarchy Gulf in sale GP.
That's right. And although the Aussies ended up winning sale GP headed by New Zealand, America's cup legend. So Russell Coots is not only a triumph of innovation and yacht design, it's one of the most high tech sports in the world. Without official intelligence playing an increasingly important role in the sale GP action.
Some of the athletes look at it as a sailboat. I look at the mercer and IoT device. So the amount of information that we can get off one catamound, we can use AI to be able to predict what they're doing right and what they're doing wrong, it's pretty amazing, it really is.
We're back with season three of the Business of Tech, and this week we catch up with the Chief Technology Officer of cel GP Warren Jones. Now he had a very successful tournament in Auckland over the weekend where the IF fifty foiling catamarans were on display for some pretty intense racing, which Ben you got to see firsthand from the sale GP chase boat.
I did. I did. I was very fortunate to be able to catch the fourth race of the first day of racing from the water and it was awesome to be honest, like, I'm not a big sailing guy. I'm not even a big sports guy in general, but there is something about sale GP that they have really captured some magic in a bottle there. It's a combination of the marketing, the format, I think the money behind the event as well. It was just it was almost a festival like event at the venue with the grant these massive grandstands and there were people all around excited having a good time, and you get up into the grandstands as I it was lucky enough to do as well, had a really great view, completely sold out, buzzing people cheering for Auckland and waving flags for their respective countries. It really was an exciting and fun event to be part of and I do hope that it does come back to Auckland again.
Well, that's the thing, because we had that debacle down in Littleton where we had racing postponed because of the dolphins in the harbor, which was what Russell Coots and companies signed up to. They knew that this was a possibility, but it left a really bad taste and suggested maybe that we might not see sell GP back. But it's in Auckland at a time when economic gloom is everywhere. It's just really good to see some big event like that that has those elements like performance, yachting technology, A lot of people coming to see this great event. We sort of need more of that.
Yeah, absolutely, it did draw crowds to the waterfront and to win you'd quart it, which is one of my favorite parts of Auckland as well. So great to see. And I was also very fortunate to be able to get a tour of the behind the scenes as well for SALGB through their tech tent, their tech base, i should say, and I got close up with the foils, these new titanium teafoils, and I got to go into the data room and check out all of the dashboards and panels and talk to some of the people there on the ground working with this immense amount of data, and it was quite eye opening and really impressive to understand how the digital world is built into this sport from the ground up. The CTO, Warren Jones, as you're here in the interview, he was there from day one figuring out how to make this a global event, how to make it the most technology forward event. So we'll have a listen to that interview later in the episode, and I think it's a really interesting one.
Yeah, so much tech involved, and as you'd expect with Larry Ellison, the Oracle founder, he was the one behind a lot of the America's Cup campaigns against Team New Zealand and is the co founder of SLGP, so very much infused with that sort of tech philosophy. So yeah, looking forward to that. First, though, we've got to talk about the big news of the week. Trump's inauguration surreal for so many reasons, not least of which was the side of the tech titans. Tim Cook from Apple, Jeff Bezos from Amazon, Sundhaaripachai from Google, of course Elon Musk there. Those are just the ones that were directly behind the president, so obviously had a front row seat to the inauguration and Ben all there really to bend the knee to the new president.
Yeah. Absolutely, And you know, it reminds me of that kid in high school who the popular kids would all rally around because they could get him to do whatever they wanted. And Trump is that kid. You know, He's so hungry for power and money that he will just kind of do whatever he is And this is obviously my opinion, he will do whatever he's paid to do. And the biggest, most money rich people in the world are all there to take advantage of that. And for the current world that we live in, that means technology, because tech companies are the biggest and richest companies in the world.
Yeah. Well, I think it definitely is a striking shift that has gone on in Silicon Valley, and this really illustrated it this week. You know, four years ago, many of those Silicon Valley executives viewed Trump with skepticism, if not outright hostility. Eight years ago, he pulled them all into Trump Tower just after he'd won the election, and to twenty sixteen very awkward meeting that they had because they didn't trust them, they didn't take him seriously. They thought he was going to be a one hit wonder. Pretty soon after that, the anti trust stuff really kicked in. That happened actually under Trump's rain, it really accelerated under Biden and then we saw the for instance, Google being declared a monopoly by US district court. So they've got these regulatory concerns looming, anti trust investigations in court cases. They're worried about that. They see financial opportunities as well. Just as we're recording this, there's news breaking about so called Stargate in the US, this massive AI investment up to five hundred billion dollars at the likes of Open Ai and others are committing to artificial intelligence. Trump is launching that. So he's basically saying to these companies, get on my bandwagon the whole America first, make America great again, and you will profit from it as well. And then it's really a matter of I think, political survival. If you're not in the tent with Trump, you're seen as his enemy and he will use whatever lever he has to go against you. So I guess it's slightly cynical, but it's strategic. By the likes of Zuckerberg and Bezos, to really align with Trump. They realize that if they don't, their massive empires could be dismantled.
Yeah. I mean, it's just good business, isn't it, to be honest like these people they I think it does go to show that despite all of the issues maybe with some of the previous administrations, that they were actually managing to keep somewhat of a cap on these massive super corporations, that they were actually exercising some power to make the likes of Matter be a bit more responsible around their impact on the population that are using them, and that once that, once that administration is gone, all bets are off. You know. So clearly, although you can criticize whatever, you criticize the previous administrations as much as you want, it is a really clear indicator that they were actually doing something. You know, Mark Zuckerberg wouldn't have taken off the energy mask and revealed his true self had things continued as they were. You know, I don't know. It's a terrifying situation for me because I've beat the drum for a long time about the importance of technology, as somebody who's been reporting on technology for some time, about how much it underpins everything we do. In the world everything we are now as a global and smaller national communities, and now the people who are controlling technology are coming out and in behind the man who has you know, tried to put ridiculous medical pseudomedical day phoinicians around gender about a man, you know, one of the richest men in the world, the technology leader, coming out onto a stage and doing what is very clearly a Nazi salute. And I don't think that that can be explained away really because if he is, you know, either he's the mega genius that everyone that a lot of people say he is, and if that's so, he wouldn't have accidentally done a Nazi salute. But so if he's not a mega genius, then he just oh, whoops, I did it by accident.
Well, he's a student of history. I mean, he's read all the Greek and Roman philosophy, knows about European history and World War Two, and you know, I sort of wonder if he knows what he's doing.
And he came up in apartheid South Africa. Yeah, like, you know, there's no way, there is no way he didn't have some sense of what he was doing, but he knew that he could get away with it because of the halo effect that comes from being associated with the Trump administration and the US media's shyness around making accusations.
So yeah, and.
That's the and that's the real worry, this concentration of power. You've got the PayPal mafia sort of there. You've got Peter Thiel, You've got David Sachs, You've got Elon Musk, You've got all these other people who see themselves as tech utopians or tech optimists. That's Mark Andresen, the venture capitalist who is donkey deep with with Trump, has spent the last few months at Mara Lago advising him. So really, you know what's in it for them? Sure, they want deregulation, particularly around AI and crypto, and we've seen Trump jump into crypto himself with his own mean coin. Millennia has her own mean coin as well, so they've been working on him and influencing him as well. And you know, to some extent, AI and these technologies will underpin some of the biggest transformations this century, and healthcare and battling climate change and that as well. But what they don't seem to talk about or really accept is the concentration of power into the hands of basically them and a few of their friends, and how bad that is. They keep preaching the tech will solve the world's challenges, but who controls it and who gets to profit from that? They're quite comfortable with the idea of someone having four hundred billion dollars in wealth being worth more than a mid sized country and that is just the free market working for them.
Yeah, we've lost the distaste that we had for the idea of for profit companies basically controlling the world. The US went through it already in the age of the Rockefellers and these kinds of things, and they had to really clamp down and turn around and say no. But it looks like this time they're just heading the gas on that whole concept. Maybe they'll hit a wall, and you know, maybe the next four years will create some much needed institutional change in the following administration after this one, But who knows. You know, maybe it's just reached a point where hope is so gone from a lot of these people who are struggling in the US that they're just going to kind of throw their lot in with whoever promises them the most radical change and quite frankly, the most radical change that was promised in the US is Trump.
Yeah, for the tech CEOs. Now there is a price to this allegiance. You know, we're already seeing the policy shifts that for instance, Meta has made around fact checking and reverting back to freedom of speech, which is very much Trump and Musks sort of lends on freedom of speech. They've had to lend financial support Elon Musk to the tune of two hundred five fifty million dollars, but they've all chipped into Trump's inaugural fund, and no doubt future campaign efforts there will be an expectation that they fund him. They're making platform changes. This is just the start really, as the ideology really starts to set in, how far do they have to go before they sort of sort of get really uncomfortable about it. So there's that dynamic. I guess the dynamic for us also, you know, at the bottom of the world is what does it mean for us? What are the global implications of this? And I think the key one really is any efforts that we are trying to make in this part of the world, in New Zealand and Australia to rain in big tech. All of that is probably going to be put on ice or watered down significantly for fear that Trump will retaliate with some sort of trade sanctions or tariffs or a lessening of the relationship between the US and our country trees. That's literally the game that he plays. It's what he's playing with Canada, Panama and Greenland. At the moment. New Zealand does not want to get on his ship list.
Absolutely. Yeah, we've been focusing on the US as an export market for a really long time because the US has kind of been wooing us to keep us away from China as much as possible. But you know, it's only going to take it's only going to take a word in the ear to Trump for all of that to potentially change, and so then we might have to re look at China as you know, a really close source of export revenue because we may not have as much of a choice, which would be a pity because it's you know, like choosing kind of which which choosing which knife stab yourself in the foot with. I guess maybe that's a bit extreme, but you know it is. It's just a sad state of affairs. And obviously the US has never been. No country is perfect, no country is without faults. But I think that when you so closely intertwine you're like politics with corporate interests and then kind of identity politics as well, in particular targeting of certain identities as a as a other group as a scapegoat, then you start to get into trouble. And yeah, I'm just I don't know. I feel that the influence of technology, these technology titans, these these oligarchs is going to spiral, and I am concerned for what it means for New Zealand, particularly given the kind of investment that the government has into the likes of Microsoft and Amazon. In the terms of our systems. Yeah, hopefully this year will be a big call for considering New Zealand's tech industry, how we can bolster it, and how we can maybe put a little bit of a fence around ourselves from big tech as much as we can.
Yeah, I think we really need to think strategically about where our place in the world is. We're exporting some fantastic technology which the US are buying, you know, lots of subscribers to zero and other companies over there, but how do we actually cement the infrastructure and the pipeline to make sure that we continue to do more of this and really compete on the global stage. You know, I think we're sort of past the point where we can sort of sit on the fence and be the Switzerland of the South Pacific. I think in this new sort of era of deglobalization, we do need to have strong relationships with one camp or the other, but we've also got to have something to give, something to differentiate ourselves. And you know, I think this malaiser in at the moment is really about we're struggling to find out what our edge is. We need to figure identify it and really go after it.
Absolutely so.
One person who wasn't in the room at the inauguration earlier this week was Larry Ellison, one of the other richest men in the world, the founder of Oracle.
Yeah. He's got a long association with the America's Cup as the owner of Oracle Team USA.
Which famously beat US in twenty thirteen in San Francisco after clawing its way back from being seven points down. Jimmy Spiddle got one up on us in the biggest comeback in sporting history.
After that, he and Russell Kurtz formed a new tournament sale GP which featured these fast foiling catamarans and is really intended to be the formula one of say large audience, quick and exciting races, fast paced entertainment.
And it is fast. The boats reach top speeds of around one hundred kilometers per hour, which is pretty incredible for foiling boat.
It is. Yeah, and the foiling technology which did evolve from the America's Cup along with the carbon fiber design of the boats is incredible. But so too is the digital tech on the boats that monitors every aspect of the yacht and crew performance.
Yeah. Literally billions, billions of data points created in every single race, So a huge it operation. It really underpins sell GP YEP.
And the man behind it is Warren Jones. He's a brit based in London who was previously the director of Technology at Oracle Racing, so also has an America's Cup association.
And being caught up with Warren following the racing action of the past weekend in Auckland. Here's his interview with sale GP tech mastermind Warren Jones.
Hi, Warren, welcome to the Business of Tech podcast. Thank you so much for joining.
Us now, thank you for inviointing me.
So sale GP. We just had the Auckland event this weekend, the second event for the year, and from what I understand, quite a successful one as well. So we were jam packed, sold out at the grand stands in the Auckland Harbor, and I was lucky enough to come along and see a few of the races and just a high paced, adrenaline filled kind of experience, which is I guess for me a little bit different from the traditional sailing experience when it comes to sport. The America's Cup obviously exciting, but there is a next level of fervor and kind of speed that comes with sale GP. So I guess, from your perspective, how does sale GP kind of differ from your traditional sailing experience.
So from my perspective on the two technology officers, so I look at it differently. Rather than some of the athletes look at it as a sail boat, I look at them as an IoT device. So the amount of information that we can get off one catam around one f fifty. What that information is if what the athletes are doing, where they're going, what they're where they've come from, where the other boats are going where we can use AI to be able to predict what they're doing, what they're doing right, and what they're doing wrong.
It's yeah, it's pretty amazing, it really is.
So Yeah, so I call them extreme I IoT devices.
They are probably maybe the fastest IoT devices are around.
Probably, Yes, yeah, I agree with that.
Yeah, I mean it's fantastic because I'm talking to some of the tech people on the day. They were saying that there's one hundred and twenty five sensors on each boat.
Is that correct, Yeah, yeah, exactly.
And something like thirty two thousand data points per second that come off those boats.
No, three hundred and fifty thousand per second.
I was off by an order of magnitude three hundred thousand data points per second.
Yeah. We manage around within the Oracle OCI Oracle cloud, we manage around fifty three billion data requests go every afternoon, So it's it's pretty monumental the amount of information that we process. And then on the back of that is that we need to get that information out as quick as possible. So that information we have, there's about ten buckets of stakeholders that would need that information. Going from the broadcast the teams to be able to coach social media, the surgier by tech team to look at the boat and see how the boat is sailing on there so it goes on and on, so move that information around the world in milliseconds. Yeah, it's incredible.
It is truly incredible because one of those sets of stakeholders is in fact the umpires, who I believe are based in the UK. And so there you're having a sail boat race moving up to one hundred ks an hour in extreme cases, with three hundred and fifty thousand data points per second that are not only streaming out of these boats, but they're going all the way over to the United Kingdom to be assessed by the umpires. That must be quite cutting edge in terms of the technology that's involved there. Where did you even go about starting that kind of project? What were the kind of thought processes?
So it's all started in twenty eighteen, So you know what I decided, I wanted to have a remote because of our global nature, we were traveling around the world. I wanted consistency to be able to where people would be able to sit in the same seat or be able to have the same equipment doing things Previously, you know, if we traveled from from New Zealand to San Francisco, the equipment is not the same equipment because it's on a boat. It's on it, it gets off the motor transport and it's it's it's different transfer. So yeah, so having an Oracle Cloud where we have security, we have power management, we have always on as well. So you know, previously we had an equipment that had to be strapped down to travel from destination to destination. Now, within within the o C, I we it's on all the time, or it's on how much we want.
It to be on.
So it's yeah, it's it's pretty it's it's pretty crazy. But yeah, there's a product called within Oracle called Oracle fast Connect, so extends your data center to anywhere around the world.
So we build.
High availability links between London and in your case, Auckland and then we send the data down there. So I think in Auckland we are about one hundred and sixty two milliseconds back to London, so it's a blink of an eye. It's pretty incredible. But Oracle fast Connect then extends that out, so we use a data center within London called London.
South Data Center.
We utilize that one because it's halfway in the middle of the world, so when we go east and when we go west is sort of halfway through there, and it's one hundred percent of a new world as well, So they use they use all the different power that this station. And I gotta say rain has to be part of that because it rains a lot in London ablutely. Yeah.
I guess one of the challenges when you have such a high technologically dense sport is that there are going to be issues, and we saw this weekend there was an issue with the sensor on the Black Foils boat, which Peter Birling attributed to some of his late starts, or at least one of his late starts at How do you navigate that challenge when you do want everything to be the same, and that is a key aspect of the sport. You want everything to be the same each race, but you are going to have these like you say, no, even even if two sensors are the same product on different boats, there is some level of transformation between them by dint of you know, physics.
Yeah, it's it's unfortunate, but it's it happens, and the boats are rigorously checked and failed tested it in every every way. We use a product called Oracle Anomaly Detection. So out of those fifty three billion data requests that we get, we scan them overnight and it looks for anomalies within the data and we can find out fault on on, if something's coming, if something's going to fail and it's failed before, then we can see that and we can see the anomalies within it and then we can change it out. But unfortunately it was a new vault that we found within the black foils, and therefore then you know, we couldn't be able to do that. But it we check and check and check and test and test and test, and it's just it sucks that, you know, we have to pay it. We're talking about this rather we're talking about than the athletes navigating the waters as as they do.
Yeah, but I suppose when it comes to higher levels of technology, there's always going to be these these small points of failure. And so if we can get to kind of ninety nine percent, that's still pretty good. There is the unfortunate time when you're going to have that one percent.
But we're trying for one hundred percent that's our goal. We want to be able to say that the boats. You know, we're very lucky in a way that all eleven boats that sailed in Auckland do exactly the same.
You know.
They have the same sensors, the same weight, the same uh rudders, the same t foils, they have everything the same. And therefore then when the athletes then look at the data, they can all look at their each other's data as well, because it's you know, that type of technology that can share a manstall competing teams. It's it's a shame, but yeah, they'll they'll hopefully, they'll, they'll, they'll, they'll get back in Sydney and have a good race there.
Yeah, And that is actually quite a unique thing about sale GP, the fact that all of the data between the teams is actually shared. And not only that, but it's actually kept within the sale GP company itself. So there's a lot of your analysts are within sale GP, and a lot of the technological specialists are actually within sale GP, so you have some of them on the teams. But the disbursement of the data isn't It is wide and broad and highly available for all of the teams. I guess, first of all, do you want to talk through kind of the decision around that and what that means in a highly technological sport. To have that data broadly available, I think.
It's pretty huge and I don't see any sports or any other federation being able to do that, let alone give that data to each competitor. I remember in season three the Canadian team joined CLGP. Within their third race, they won a race, and they would ask the question, how you know your third race?
You win a race? How did you do that?
And they come back and said, data using the Oracle data, looking at the Oracle dashboards, looking at teams that are sailing the boat correctly, not what they would be doing if they didn't have that data, they'd be sailing it incorrectly. They're having that information is a great start and level out the play and field. To be honest that the probably the top teams don't like it, but the teams, the emergent teams coming through love it because it gives them that that it neutralizes everything from that point of view. But it's so powerful now the data, because you could be you could be going down. You could say, okay, then this is how I want to sail the boat and it could be right, it could be wrong. But then you have other teams being able to do something or try something, so you're all looking at each other's data to be able to find that sweet spot. It's pretty powerful and.
I guess, well, it sounds like what that's going to do is kind of result in a return to the mean, and so everybody's doing the same thing. In reality, these athletes are pushing the boundaries. They're trying new things to try and get that edge, and so there's a constant feedback loop of trying different little tiny maneuvers to see if they can push it. And then everybody can see how six for those maneuvers were.
Going back and say, we're very lucky in a way that sailing is that. You know, if we generate fifty three billion data requests, there's equivalent of fifty three billion options. So there's a lot of things to do and a lot of things to change, and you could change it. For one, in Auckland, the setting on the boat could be fantastic, But then when you get to Sydney, there's different current, there's different wind, there's different courses, there's different so many other things that you need to change to be able to sail those conditions.
Going back to the text, So, staying on this shared data theme, one of the things about data is that really it's a stream of numbers when you get down to its core, which is not particularly helpful for people who are not data scientists. And like you said, you have ten buckets of stakeholders that need to be able to access and understand this data. So there must have been a user interface challenge in terms of how you communicate this data to all the different people involved. Do you want to talk a bit about that side of it.
Yeah, So the main component is Oracle stream analytics. So we we didn't want to create we didn't want to get the data and then get data ten times from the boat, so we just get one source of data and then manipulate that data to whoever needs that information and what they do. So stream analytics gives us stability to get the series and ones, as you said, and then be able to create a metric like Team New Zealand, what's the distance between the finishing line to the boundary to Team A to Team B to Team C. So you know, we know that if you put an f fifty on the water is going to generate data. So once it gets to the data, then you can work out where they are. We have very very complex information on the boats and we can generate We know where each f fifty years within one centimeter in the spatial world, so we can then work out where that boat is comparison to where everything else is on the racetrack. So within stream analytics you create metrics called patterns, so we have around I think it's about three thousand patterns within it. So as soon as that data comes in, then it converts it into this information and then it goes off to the individual stakeholders. So for broadcast it would go into liveline. So liveline is augmented reality package for the coaches. It goes back into the venue and therefore the coaches have access to a dashboard and then live video. We also recreate the wing screen, so each each f fifty has two screens in the wing and it has information about about the start, about the boundaries and things like that. So we recreate that then to the coaches, so the coaches can see real time what the sailors have seen on the boat as well. So there's the huge amounts of information going around back and forth around the world, and it's just you know.
What information you need.
And the coaches at a great point really because historically the coaches were always on the water, they were looking at the boat, they were communicating, and SLGP wanted to change the way that was. We thought that was inefficient and we have so much information that we can help them. We didn't want to use fossil fuel engines on the water, just running around chasing out the boats and burning fuel and necessary. So bringing them on the shore is something that we really wanted and from And you asked one of the coaches now if they want to go back on the water, and they go, nope, we're pretty happy here we are.
Yeah, what are the kind of advantages of being a sthetic on the sideline rather than on the water.
For me, I'm not a coach, and I've talked to many coaches on there, but I think it's the amount of informations asvailable to them. I think when you're on a boat, you're you're holding on to your life with one hand and then you're trying to look at a phone or a tablet on it within the other just as a work. But having that information and being able to have that real time and also talk to the boat as well. We're seeing the role of the coach is changing, it's evolving, it's having there, they're part of the team now, they're giving information, real time information and things like that which they didn't before.
How long did it actually take you to architect this whole system, because it sounds incredibly, credibly complex. I imagine there must have been a few few men hours put into getting everything the way that you needed it to be.
Well.
I remember in two and late twenty seventeen, early twenty eighteen, I sat down and they took me about three months to go through our calls catalogue of services, and.
I was cherry picking.
Yeah, I want that, that's what that's what we need, that's what we should be doing, that's what we could do.
And we we I.
Cherry picked up about a dozen applications that we thought we could use. Some of the applications we had to modify or oracle modified for us because the user case was not what it was supposed to be. But they were the teams were happy to to change that. But it Yeah, it was about three months. There's there's they we talk about threety three billion data recrafts. They have fifty three billion products, so it's it's it's huge, the amount of the products and the things they do. So yeah, we sat down and we built it out. But we we always wanted to have a cloud instance that's where we we thought the future was, and that's that's where it's that's where it's gone.
You know.
We we I talked to you at the beginning. I'm in London with our broadcasts and we sat with the umpires, we sat with the people who were producing the show. The content, all the cameras, all four t eight cameras, go back to London, We create a show, we distribute them to one hundred and sixty eight broadcasters around the world. From London, we send that feedback to you to watching the Adrenaline Lounge, to the big screens, and that's all coming from London within three hundred milliseconds. It's yeah, it's crazy.
It is crazy. It's it's almost that. I mean, if you go back five ten years, unimaginable, you just couldn't couldn't have imagined it.
So yeah, the.
Capability to do it, it does feel very cutting edge, and it sounds like you were, you know, set on Oracle from very very early on. Was there a technological reason as well?
We have we have a we have a relationship with them, But if I was if we didn't have a relationship with them, I would have chosen them due to their their oci locations around the world. If you look where we go around the world, that they have a data center around the corner. It's you know that that's one of the big things that us. We need low latency, We need data to get to its end location as quick as possible, and Oracle are very very good at that.
What were some of the most tricky challenges for you and the team in setting this up, whether whether in the setup or ongoing. What are the kind of what are the technological limits that you're budding up against?
You know, Auckland is probably the furthest away from London as you could possibly go. I think if you go a bit further, you're coming home, aren't you. So it gets to its limit there, so we utilize Oracle has an edge component in Sydney, so we utilize that. But it's we're generating about four times more data today than we were in twenty nineteen. We're it, and we need that data as fast fast, So it's it's we with and how do you You can generate data as long as you want it, doesn't you know, you're always going to be getting information. But what does that mean? Does it? Does it mean something? Is it giving you more insight to what's happening? Is it giving you more the ability to make the boats go faster, to make the boats more reliable? So it's it's given that context of what that data means as well. So that's more information, more dashboards, more there. But then we have to train people because some of the information now is getting as granular as possible. And you talked about we have we have a data scientists working for sales GP, but most of them are all sailors as well. So having that ability to look at the data from the X and Y, but then also look at what they represent on a on a on a racecourse as well is invaluable.
Yeah, I could imagine that. How how does that how does it translate into the real world boat? So I mean, because these are standsized boats, you've got things like your major upgrades like the tfoil for example, was did you obviously you must have used the data to be able to say, well, you know, we can recognize that it's giving us all these advantage, but there's a physical aspect to it as well. So when it comes to making decisions about fleet upgrades, changes to the fleet, how does it go from data to action?
We we have a we have a we have an application that we can generate it's called a BPP so to be able to look at the boats. So you can put t foils on there, you can put the l foils on there, you can make the boat longer, shorter, and it will give you what like. It's basically a CFD which lives.
Within the OCI.
It's a cloud based tool, so so you can you like like like whether you design cars or you can just sign.
We have our own there with our.
Physics in there, so have the ability to be able to test the foils. So we start off within the virtual world and work out what that looks like from from that point of view, and then they test it. They test it then the simulation simulation, so we use our we have our own simulator that the team is used to be able to do that, so we test it what what and we use real time data so from from Auckland. We'll get the data, we'll put that into our platform and then we run the simulations then using the wind, the tide the conditions of what that was, and then you could work out then what the numbers were. So it gets to a point there where we think that yes, and I'm not a designer, just given the tools to be able to do it. And there comes a time when you think that yes, I think we can start building physical models, or we can build test models and stuff that and then then it goes out there. But then you need software then to be able to control the boards, to be able to control the forces, to the loads and things like that as well. And the performance engineering team at SALGP they will manage all that. So they build, they rocked the code to be able to drop the boards, to be able to manage the loads, all these other things as well. So it's a it's a load of it's it's multi department, it's everybody working looking at data and trying to work out how to move that forward.
It's yeah, it's pretty pretty tough.
Yeah, I can imagine. So, so basically you have a digital twin of the boats and then you use the data from the boats to inform that digital twin and then make changes and then bring it slowly into the real world to simplify things drastically. But there's a lot of stages and software and engineering that goes into that whole process.
Huge, huge amounts, and you know, you change one thing, then another thing changes as well, and that batterfly effect then is happening on there. So it's trying to limit that case and go from there. But we're young as well. We've only been doing this for five years, five six years as well, so there are a couple of steps that we don't know that we should be doing as well. So we're learning and we're trying to move this forward as well. So it's a long way to go.
Yeah, I can imagine speaking of that, what are you hoping for in the future, What are your pipe dreams? What are you hoping for?
So we utilize a lot of AI at the moment. As you know, we mentioned that that fable number, that fifty three billion, that a human mind can't comprehend what that is. So you need you need mL you need AI, you need large language models to be able to handle that now. So we're working with Oracle on really cool stuff on what to do that the automated cameras now that we're working on now that that is no other federation or sport is being able to do that. But that's all underlined on data. So you know those those sensors that you mentioned there, we know when the boat is going to capsize, all the hull is forty two percent from the water. So therefore then we can tell the cameras to go and go and film this boat here and things like that, so we you know, predictive AI to be able to work out where the boats are going, if there's going to be a collision or something's happening, go and move the cameras to this location. So at the moment, all the cameras are controlled from London.
So each boat.
Has an agile camera on the back of the boat and the operators are in London control in it over the weekend.
So it's a pretty tough job there. So to have.
AI to be able to go and find these shots for you and then you can frame it then is.
Exactly what we want.
So just that I can kind of understand what you mean is that there's a AI program that on the camera that is able to understand when a shot is what you might be looking for, and so rather than having to manually adjust constantly and find what you're looking for, it just can go oh, yeah, this is good here for a while.
Yeah, or you just say follow Follow Follow Team New Zealand, and the camera just follows it everywhere it goes. It's it's it's pretty. It's amazing, it really is. But a lot of the industry is running on vision, object recognition and things like that, but we have abundance of information, events of data, and real time data as well, so we we we're using data to follow the story rather than the division, but we also use an augment minted reality and we we can we have what we call athlete tracking, so we have the camera at the back end, we have the athletes coming from side to side, and we built a model with Oracle skeletons, so we have good facial recognition models. But they have helmets on, they have goggles on, so we can't really see them. So we modeled each athletes from their skeleton and how they run, and therefore then we can use AI to match that so when they're running past, then we can work out within I think it was su fifteen milliseconds who they are and then we can put a little name strap above them and tell tell the audience this is this person or that person.
Oh my gosh, that's that's incredible, quite a really cutting edge. And so are you when are you expecting that to be available.
To it's live? Yeah, So if you can have a look at the recording of the Auckland eventuals see I think day two they had it on a couple of times there, so it's a camera at the back and they do it I think Spain and Australia.
Fantastic. Wow. And so that kind of thing. We'll just continue to expand where you're able to understand things more fully I guess, and then use that information to provide deeper insights but also gain some predictive knowledge about what might be going on with the race.
Yeah exactly.
And you know, we we've got at the moment, within the OCI, we've got about two trillion lines of data available to us. So that's every race that sales GPS competed in. We keep every bit of data available. So when we create a new metric in today's world, we can go back and then create it from the other races as well and then test it. So we're always using that information and testing on models and moving that on. But yeah, there's a lot of there's a lot of information, and it's that the autonomous databases are just amazing. They just they just keep on going. It's just you know, fifty three billion data lines of code in it. It's just incredible.
Just to round us out, you mentioned large language models and so you know I'm assuming, then correct me if I'm wrong. If you've got this extraordinary amount of data, are you using the large language models to actually interrogate that data to say, going to show me what would you know all of the wing data from this race or any Is it that advanced it is?
You can you can compare, you can compare races, you can compare boats, you can compare area everything. There's there's there's things that we're we've got plans to do and and use that. But it's it's a huge amount of information and the huge amounts of a bit of data. But we think that there's things that we're not thinking about at the moment. And like if you if you find a metric today and you've you know, this is the new metric. We we do a chasing within season twenty twenty five, we have a chasing target, so it works out that if a boat has chasing another boat and it brings that down. That was only done for this season, but because we have the data, we could go back to season one and be able to work that that that out from there because we have this as you as you reckon, as you said, the zeros are ones that that's available to us, so we can really create that as well.
Wow, right, we need to wrap up because I'm aware you've probably got a lot of sleep to catch up on after a busy weekend, or maybe some more work to do one of the two. So just the final question, is there anything that we haven't covered that you think is super interesting, super unique to sal GP technological technology wise?
Really, I think we've been pretty it's been pretty good actually with everything. It's just we're you know, we're very lucky in a way that that that that the CEO of of c l GP, Sir Russell Cootz, he he really believes in technology and he wants the tech to.
To go forward.
He's he's incredibly he's saying in knowledge, as you know from Olympic Gold Medals and America's Cups and things like that. But to understand the tech as well is really good. So to have a champion pushing us forward, to be able to use this tech, to be able to find nuances to be more efficient and how we.
Do it is is pretty cool.
So yeah, we're you know, we we've got a load of a load of new new things that we've got coming out over the season now and you know, thanks to Oracle, they're they're helping us push these through.
So being one of the really interesting things that cel GP has decided to do, which Warren talked about in there, is share all of the data off the boats with every team. So here you have the super competitive group of racing syndicates. Normally they're hiding everything and keeping everything close to their chists, and with sel GP, they said, look, we're about innovation and going faster, trying to put on a really good show here. The best way to facilitate that is to give everyone full visibility and what the competitors are doing.
Yeah, it's such an interesting choice that really does define sale GP as a sport because it does become more about the sailing and you know, I had a chat to very brief chat to the strategists from the Great Britain team and the following the press conference. Her name's Hannah Mills, incredible sailing talent, and she was basically like, it is just really exciting to be able to access all this data, to be able to work with all of it, and then to balance that with the kind of vibes out there on the water to figure out kind of how we actually approach things. It turns it into a thoughtful strategic sport broadly across the entire fleet, rather than just saying who can afford the best technology and the best analysts.
Yeah, obviously Oracle is all over this as it was the America's Cup were Oracle racing in particular. But you look at it from their point of view. Sure they love their technology being used, but the insights they're getting here, like the stuff you're talking about digital twins, you know, being able to build a digital twin off an f fifty boat and every aspect of its design and its performance all the way down to the crew. They can track through their skeletal shape exactly who's moving around a boat. Where So the granularity of detail that they've got on this, they can then apply to other types of industries, anything that's fast moving, high performance, where there's potential health and safety issues. They can take this and put it into factories, put it into transport systems. It's got to be a hugely valuable thing in terms of intellectual property that it creates for Oracle.
Definitely. Yeah, and you know that the talk about the capabilities of the Oracle Cloud to actually do these this kind of project. I would imagine the learnings that the Oracle team is taking from working with sale GP to you know, get these this massive amount of data from one side of the world to the other as fast as possible, to run some real time analytics, some post post capture analytics over it, to stream it into different places. That's all going to be really useful for Oracle to take back into its team and apply to other areas of industry as well. So it's definitely a win win situation for Larry Ellison.
Yeah, and AI and machine learning playing a role less so at the moment, but definitely seems as though they're exploring the use of that for future applications.
Yeah. Yeah, really interesting what they're talking about there in terms of being able to predict where a boat might be headed and be able to say, look, you're on a collision course. And not only can that, as Warren Jones said, mean like let's get the cameras over there immediately, but also it can actually make it safer. So if you know, if you get a flag as the driver of a boat saying we need to we need to be careful because you're on a collision course, there's you know, the tides are coming this way, your boat's doing this, so we can predict that this course is going to be a concern, make it just make a change. Now, that's actually going to make it safer for the athletes there out on the water as well. So that requires some pretty hefty on board compute as well. So when I talked to the Oracle representative Alistair Green, he was saying that there wills there will need to be some work on making those inference models as small as possible, because you can't have too much equipment on a boat because you can't have too much weight. So you'll need, you know, if you can throw a powerful but light gpu on there and have a really small inferencing model that can run on a small amount of space, then you can start to get some really exciting things happening.
Yeah, and from the viewer's point of view, you know, broadcasting is a big part of this. So the rich experience that they're able to create, the augmented reality and all that sort of thing is really cool. I guess part of me feels And this was an argument about the America's Cup. It got two technology centric, you know, this this race for more and more innovation, being the fastest, being the most impressive. You know, at some point, you know, you just want to get back to the basics, getting out in the boat, not having looking at a screen and the sensors and all that sort of thing. Just the prowess of human beings sailing, putting all that experience to good use sort of. I think part of me craves that, and we're getting further and further away from it.
Yeah, that's a fair and that's a fair observation, I think. But I would say that that is that is just not what sale GP is, you know, and maybe that's an opportunity for up. You can start your own sailing competition. That's a class. Yeah, hands in the Wellington Harbor, that's right.
Yeah, Well, that's it for the Business of Tech this week, Thanks so much to Warren Jones fantastic technology that he showcased here. Lots of big issues to get our teeth into in twenty twenty five on the Business of Tech, and we've got some other great guests lined up for the podcast too.
Next week we'll hear from a New Zealand software startup that has one hundred million users internationally, perhaps the greatest reach of Kiwi Tech so far.
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