January 22, 2025 • 56 mins
SailGP'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.
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Speaker 1 (00:00):
We go New Zealand absolutely flat out at the top
of the line.
Speaker 2 (00:04):
They're going to struggle to control the boat with those
big foils. From here.
Speaker 3 (00:08):
France on the.
Speaker 4 (00:08):
Insight should lead at mark one, but it's going to.
Speaker 3 (00:11):
Be a sprint, and we are often racing here in
New Zealand.
Speaker 1 (00:15):
Ah.
Speaker 2 (00:15):
Yes, nothing says summer like watching Team New Zealand foiling
its way across the hierarchy Gulf in sale GP.
Speaker 3 (00:23):
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.
Speaker 1 (00:43):
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.
Speaker 2 (01:00):
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
(01:20):
the sale GP chase boat.
Speaker 3 (01:22):
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
(01:45):
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,
(02:06):
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.
Speaker 2 (02:20):
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
(02:41):
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.
Speaker 3 (03:02):
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,
(03:23):
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
(03:46):
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.
Speaker 2 (04:04):
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
(04:25):
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,
(04:46):
so obviously had a front row seat to the inauguration
and Ben all there really to bend the knee to
the new president.
Speaker 3 (04:55):
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
(05:16):
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.
Speaker 2 (05:35):
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
(05:55):
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
(06:16):
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
(06:37):
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
(07:00):
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,
(07:22):
their massive empires could be dismantled.
Speaker 3 (07:25):
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
(07:50):
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
(08:11):
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,
(08:34):
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
(08:55):
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
(09:16):
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.
Speaker 2 (09:28):
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.
Speaker 4 (09:40):
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.
Speaker 3 (10:01):
So yeah, and.
Speaker 2 (10:03):
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
(10:26):
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
(10:51):
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
(11:14):
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
(11:37):
working for them.
Speaker 3 (11:38):
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
(11:59):
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
(12:21):
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.
Speaker 2 (12:36):
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
(12:59):
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
(13:20):
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,
(13:41):
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
(14:03):
what he's playing with Canada, Panama and Greenland. At the moment.
New Zealand does not want to get on his ship list.
Speaker 3 (14:10):
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
(14:33):
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
(14:53):
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
(15:15):
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,
(15:35):
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
(15:59):
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.
Speaker 2 (16:16):
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
(16:36):
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
(16:59):
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.
Speaker 3 (17:13):
Absolutely so.
Speaker 2 (17:20):
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.
Speaker 3 (17:30):
Yeah. He's got a long association with the America's Cup
as the owner of Oracle Team USA.
Speaker 2 (17:36):
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.
Speaker 3 (17:50):
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.
Speaker 2 (18:05):
And it is fast. The boats reach top speeds of
around one hundred kilometers per hour, which is pretty incredible
for foiling boat.
Speaker 3 (18:13):
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.
Speaker 2 (18:27):
Yeah. Literally billions, billions of data points created in every
single race, So a huge it operation. It really underpins
sell GP YEP.
Speaker 3 (18:38):
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.
Speaker 2 (18:48):
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.
Speaker 3 (19:01):
Hi, Warren, welcome to the Business of Tech podcast. Thank
you so much for joining.
Speaker 1 (19:05):
Us now, thank you for inviointing me.
Speaker 3 (19:08):
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,
(19:31):
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,
(19:54):
from your perspective, how does sale GP kind of differ
from your traditional sailing experience.
Speaker 1 (20:02):
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
(20:23):
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.
Speaker 5 (20:34):
It's yeah, it's pretty amazing, it really is.
Speaker 1 (20:37):
So Yeah, so I call them extreme I IoT devices.
Speaker 3 (20:41):
They are probably maybe the fastest IoT devices are around.
Speaker 1 (20:45):
Probably, Yes, yeah, I agree with that.
Speaker 3 (20:47):
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.
Speaker 1 (20:56):
Is that correct, Yeah, yeah, exactly.
Speaker 3 (20:59):
And something like thirty two thousand data points per second
that come off those boats.
Speaker 5 (21:04):
No, three hundred and fifty thousand per second.
Speaker 3 (21:08):
I was off by an order of magnitude three hundred
thousand data points per second.
Speaker 1 (21:13):
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
(21:37):
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
(21:58):
the world in milliseconds. Yeah, it's incredible.
Speaker 3 (22:03):
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
(22:25):
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?
Speaker 1 (22:46):
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,
(23:07):
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
(23:28):
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.
Speaker 5 (23:43):
It to be on.
Speaker 1 (23:45):
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.
Speaker 5 (23:58):
So we build.
Speaker 1 (24:00):
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
(24:23):
London called London.
Speaker 5 (24:26):
South Data Center.
Speaker 1 (24:28):
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.
Speaker 3 (24:52):
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
(25:14):
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.
Speaker 1 (25:32):
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
(25:53):
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
(26:15):
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.
Speaker 3 (26:34):
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.
Speaker 1 (26:49):
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.
Speaker 5 (27:00):
You know.
Speaker 1 (27:00):
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,
(27:24):
they'll they'll hopefully, they'll, they'll, they'll, they'll get back in
Sydney and have a good race there.
Speaker 3 (27:30):
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
(27:50):
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
(28:14):
broadly available, I think.
Speaker 1 (28:17):
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,
(28:39):
how you know your third race?
Speaker 5 (28:41):
You win a race? How did you do that?
Speaker 1 (28:42):
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,
(29:06):
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
(29:28):
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.
Speaker 3 (29:35):
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
(29:57):
if they can push it. And then everybody can see
how six for those maneuvers were.
Speaker 1 (30:02):
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
(30:24):
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.
Speaker 3 (30:36):
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
(30:58):
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.
Speaker 1 (31:08):
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
(31:30):
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
(31:51):
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
(32:14):
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.
(32:40):
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.
(33:01):
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.
Speaker 5 (33:15):
What information you need.
Speaker 1 (33:16):
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
(33:38):
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.
Speaker 3 (33:50):
Yeah, what are the kind of advantages of being a
sthetic on the sideline rather than on the water.
Speaker 1 (34:00):
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
(34:21):
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.
Speaker 3 (34:38):
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.
Speaker 5 (34:51):
Well.
Speaker 1 (34:51):
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.
Speaker 5 (35:02):
I was cherry picking.
Speaker 1 (35:04):
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.
Speaker 5 (35:09):
And we we I.
Speaker 1 (35:10):
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
(35:31):
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.
Speaker 5 (35:50):
You know.
Speaker 1 (35:50):
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
(36:11):
the Adrenaline Lounge, to the big screens, and that's all
coming from London within three hundred milliseconds. It's yeah, it's crazy.
Speaker 3 (36:20):
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.
Speaker 1 (36:27):
So yeah, the.
Speaker 3 (36:28):
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?
Speaker 1 (36:42):
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
(37:05):
quick as possible, and Oracle are very very good at that.
Speaker 3 (37:11):
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?
Speaker 1 (37:28):
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
(37:49):
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?
(38:12):
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.
(38:33):
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.
Speaker 3 (38:51):
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
(39:12):
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?
Speaker 1 (39:27):
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,
(39:48):
and it will give you what like. It's basically a
CFD which lives.
Speaker 5 (39:52):
Within the OCI.
Speaker 1 (39:53):
It's a cloud based tool, so so you can you
like like like whether you design cars or you can
just sign.
Speaker 5 (40:06):
We have our own there with our.
Speaker 1 (40:07):
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
(40:31):
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
(40:51):
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.
(41:14):
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.
Speaker 5 (41:32):
It's yeah, it's pretty pretty tough.
Speaker 3 (41:34):
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.
Speaker 1 (41:56):
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.
(42:17):
So we're learning and we're trying to move this forward
as well. So it's a long way to go.
Speaker 3 (42:22):
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?
Speaker 1 (42:31):
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
(42:54):
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
(43:15):
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.
Speaker 5 (43:36):
So each boat.
Speaker 1 (43:36):
Has an agile camera on the back of the boat
and the operators are in London control in it over
the weekend.
Speaker 5 (43:43):
So it's a pretty tough job there. So to have.
Speaker 1 (43:48):
AI to be able to go and find these shots
for you and then you can frame it then is.
Speaker 5 (43:54):
Exactly what we want.
Speaker 3 (43:56):
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
(44:17):
for a while.
Speaker 1 (44:19):
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
(44:40):
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
(45:01):
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
(45:23):
are and then we can put a little name strap
above them and tell tell the audience this is this
person or that person.
Speaker 3 (45:29):
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.
Speaker 1 (45:38):
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.
Speaker 3 (45:57):
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.
Speaker 5 (46:19):
Yeah exactly.
Speaker 1 (46:20):
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
(46:40):
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.
Speaker 3 (47:00):
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
(47:21):
or any Is it that advanced it is?
Speaker 1 (47:24):
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
(47:46):
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
(48:06):
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.
Speaker 3 (48:18):
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?
Speaker 1 (48:42):
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.
Speaker 5 (48:59):
To go forward.
Speaker 1 (48:59):
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.
Speaker 5 (49:17):
Do it is is pretty cool.
Speaker 1 (49:19):
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.
Speaker 2 (49:37):
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,
(50:00):
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.
Speaker 3 (50:14):
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,
(50:36):
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,
(50:57):
rather than just saying who can afford the best technology
and the best analysts.
Speaker 2 (51:01):
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
(51:21):
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
(51:42):
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.
Speaker 3 (51:59):
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
(52:22):
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.
Speaker 2 (52:37):
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.
Speaker 3 (52:49):
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
(53:09):
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
(53:33):
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
(53:54):
that can run on a small amount of space, then
you can start to get some really exciting things happening.
Speaker 2 (54:00):
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,
(54:22):
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.
Speaker 3 (54:44):
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.
Speaker 2 (55:03):
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.
Speaker 3 (55:23):
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.
Speaker 2 (55:33):
It's a great success story and there's plenty more like
that to come. To catch all of our episodes, subscribe
to the Business of Tech on your podcast platform of choice.
We're also streaming on iHeartRadio.
Speaker 3 (55:45):
Get in touch with us with your feedback and topic suggestions.
We're on LinkedIn and blue Sky, and catch.
Speaker 2 (55:50):
Us again for the next episode next Thursday.
Speaker 3 (55:54):
See you later.
We go New Zealand absolutely flat out at the top
of the line.
Speaker 2 (00:04):
They're going to struggle to control the boat with those
big foils. From here.
Speaker 3 (00:08):
France on the.
Speaker 4 (00:08):
Insight should lead at mark one, but it's going to.
Speaker 3 (00:11):
Be a sprint, and we are often racing here in
New Zealand.
Speaker 1 (00:15):
Ah.
Speaker 2 (00:15):
Yes, nothing says summer like watching Team New Zealand foiling
its way across the hierarchy Gulf in sale GP.
Speaker 3 (00:23):
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.
Speaker 1 (00:43):
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.
Speaker 2 (01:00):
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
(01:20):
the sale GP chase boat.
Speaker 3 (01:22):
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
(01:45):
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,
(02:06):
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.
Speaker 2 (02:20):
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
(02:41):
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.
Speaker 3 (03:02):
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,
(03:23):
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
(03:46):
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.
Speaker 2 (04:04):
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
(04:25):
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,
(04:46):
so obviously had a front row seat to the inauguration
and Ben all there really to bend the knee to
the new president.
Speaker 3 (04:55):
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
(05:16):
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.
Speaker 2 (05:35):
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
(05:55):
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
(06:16):
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
(06:37):
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
(07:00):
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,
(07:22):
their massive empires could be dismantled.
Speaker 3 (07:25):
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
(07:50):
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
(08:11):
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,
(08:34):
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
(08:55):
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
(09:16):
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.
Speaker 2 (09:28):
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.
Speaker 4 (09:40):
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.
Speaker 3 (10:01):
So yeah, and.
Speaker 2 (10:03):
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
(10:26):
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
(10:51):
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
(11:14):
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
(11:37):
working for them.
Speaker 3 (11:38):
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
(11:59):
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
(12:21):
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.
Speaker 2 (12:36):
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
(12:59):
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
(13:20):
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,
(13:41):
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
(14:03):
what he's playing with Canada, Panama and Greenland. At the moment.
New Zealand does not want to get on his ship list.
Speaker 3 (14:10):
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
(14:33):
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
(14:53):
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
(15:15):
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,
(15:35):
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
(15:59):
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.
Speaker 2 (16:16):
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
(16:36):
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
(16:59):
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.
Speaker 3 (17:13):
Absolutely so.
Speaker 2 (17:20):
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.
Speaker 3 (17:30):
Yeah. He's got a long association with the America's Cup
as the owner of Oracle Team USA.
Speaker 2 (17:36):
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.
Speaker 3 (17:50):
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.
Speaker 2 (18:05):
And it is fast. The boats reach top speeds of
around one hundred kilometers per hour, which is pretty incredible
for foiling boat.
Speaker 3 (18:13):
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.
Speaker 2 (18:27):
Yeah. Literally billions, billions of data points created in every
single race, So a huge it operation. It really underpins
sell GP YEP.
Speaker 3 (18:38):
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.
Speaker 2 (18:48):
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.
Speaker 3 (19:01):
Hi, Warren, welcome to the Business of Tech podcast. Thank
you so much for joining.
Speaker 1 (19:05):
Us now, thank you for inviointing me.
Speaker 3 (19:08):
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,
(19:31):
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,
(19:54):
from your perspective, how does sale GP kind of differ
from your traditional sailing experience.
Speaker 1 (20:02):
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
(20:23):
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.
Speaker 5 (20:34):
It's yeah, it's pretty amazing, it really is.
Speaker 1 (20:37):
So Yeah, so I call them extreme I IoT devices.
Speaker 3 (20:41):
They are probably maybe the fastest IoT devices are around.
Speaker 1 (20:45):
Probably, Yes, yeah, I agree with that.
Speaker 3 (20:47):
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.
Speaker 1 (20:56):
Is that correct, Yeah, yeah, exactly.
Speaker 3 (20:59):
And something like thirty two thousand data points per second
that come off those boats.
Speaker 5 (21:04):
No, three hundred and fifty thousand per second.
Speaker 3 (21:08):
I was off by an order of magnitude three hundred
thousand data points per second.
Speaker 1 (21:13):
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
(21:37):
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
(21:58):
the world in milliseconds. Yeah, it's incredible.
Speaker 3 (22:03):
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
(22:25):
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?
Speaker 1 (22:46):
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,
(23:07):
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
(23:28):
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.
Speaker 5 (23:43):
It to be on.
Speaker 1 (23:45):
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.
Speaker 5 (23:58):
So we build.
Speaker 1 (24:00):
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
(24:23):
London called London.
Speaker 5 (24:26):
South Data Center.
Speaker 1 (24:28):
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.
Speaker 3 (24:52):
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
(25:14):
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.
Speaker 1 (25:32):
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
(25:53):
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
(26:15):
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.
Speaker 3 (26:34):
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.
Speaker 1 (26:49):
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.
Speaker 5 (27:00):
You know.
Speaker 1 (27:00):
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,
(27:24):
they'll they'll hopefully, they'll, they'll, they'll, they'll get back in
Sydney and have a good race there.
Speaker 3 (27:30):
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
(27:50):
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
(28:14):
broadly available, I think.
Speaker 1 (28:17):
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,
(28:39):
how you know your third race?
Speaker 5 (28:41):
You win a race? How did you do that?
Speaker 1 (28:42):
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,
(29:06):
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
(29:28):
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.
Speaker 3 (29:35):
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
(29:57):
if they can push it. And then everybody can see
how six for those maneuvers were.
Speaker 1 (30:02):
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
(30:24):
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.
Speaker 3 (30:36):
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
(30:58):
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.
Speaker 1 (31:08):
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
(31:30):
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
(31:51):
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
(32:14):
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.
(32:40):
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.
(33:01):
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.
Speaker 5 (33:15):
What information you need.
Speaker 1 (33:16):
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
(33:38):
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.
Speaker 3 (33:50):
Yeah, what are the kind of advantages of being a
sthetic on the sideline rather than on the water.
Speaker 1 (34:00):
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
(34:21):
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.
Speaker 3 (34:38):
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.
Speaker 5 (34:51):
Well.
Speaker 1 (34:51):
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.
Speaker 5 (35:02):
I was cherry picking.
Speaker 1 (35:04):
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.
Speaker 5 (35:09):
And we we I.
Speaker 1 (35:10):
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
(35:31):
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.
Speaker 5 (35:50):
You know.
Speaker 1 (35:50):
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
(36:11):
the Adrenaline Lounge, to the big screens, and that's all
coming from London within three hundred milliseconds. It's yeah, it's crazy.
Speaker 3 (36:20):
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.
Speaker 1 (36:27):
So yeah, the.
Speaker 3 (36:28):
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?
Speaker 1 (36:42):
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
(37:05):
quick as possible, and Oracle are very very good at that.
Speaker 3 (37:11):
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?
Speaker 1 (37:28):
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
(37:49):
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?
(38:12):
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.
(38:33):
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.
Speaker 3 (38:51):
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
(39:12):
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?
Speaker 1 (39:27):
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,
(39:48):
and it will give you what like. It's basically a
CFD which lives.
Speaker 5 (39:52):
Within the OCI.
Speaker 1 (39:53):
It's a cloud based tool, so so you can you
like like like whether you design cars or you can
just sign.
Speaker 5 (40:06):
We have our own there with our.
Speaker 1 (40:07):
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
(40:31):
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
(40:51):
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.
(41:14):
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.
Speaker 5 (41:32):
It's yeah, it's pretty pretty tough.
Speaker 3 (41:34):
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.
Speaker 1 (41:56):
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.
(42:17):
So we're learning and we're trying to move this forward
as well. So it's a long way to go.
Speaker 3 (42:22):
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?
Speaker 1 (42:31):
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
(42:54):
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
(43:15):
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.
Speaker 5 (43:36):
So each boat.
Speaker 1 (43:36):
Has an agile camera on the back of the boat
and the operators are in London control in it over
the weekend.
Speaker 5 (43:43):
So it's a pretty tough job there. So to have.
Speaker 1 (43:48):
AI to be able to go and find these shots
for you and then you can frame it then is.
Speaker 5 (43:54):
Exactly what we want.
Speaker 3 (43:56):
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
(44:17):
for a while.
Speaker 1 (44:19):
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
(44:40):
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
(45:01):
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
(45:23):
are and then we can put a little name strap
above them and tell tell the audience this is this
person or that person.
Speaker 3 (45:29):
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.
Speaker 1 (45:38):
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.
Speaker 3 (45:57):
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.
Speaker 5 (46:19):
Yeah exactly.
Speaker 1 (46:20):
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
(46:40):
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.
Speaker 3 (47:00):
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
(47:21):
or any Is it that advanced it is?
Speaker 1 (47:24):
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
(47:46):
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
(48:06):
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.
Speaker 3 (48:18):
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?
Speaker 1 (48:42):
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.
Speaker 5 (48:59):
To go forward.
Speaker 1 (48:59):
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.
Speaker 5 (49:17):
Do it is is pretty cool.
Speaker 1 (49:19):
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.
Speaker 2 (49:37):
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,
(50:00):
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.
Speaker 3 (50:14):
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,
(50:36):
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,
(50:57):
rather than just saying who can afford the best technology
and the best analysts.
Speaker 2 (51:01):
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
(51:21):
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
(51:42):
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.
Speaker 3 (51:59):
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
(52:22):
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.
Speaker 2 (52:37):
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.
Speaker 3 (52:49):
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
(53:09):
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
(53:33):
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
(53:54):
that can run on a small amount of space, then
you can start to get some really exciting things happening.
Speaker 2 (54:00):
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,
(54:22):
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.
Speaker 3 (54:44):
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.
Speaker 2 (55:03):
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.
Speaker 3 (55:23):
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.
Speaker 2 (55:33):
It's a great success story and there's plenty more like
that to come. To catch all of our episodes, subscribe
to the Business of Tech on your podcast platform of choice.
We're also streaming on iHeartRadio.
Speaker 3 (55:45):
Get in touch with us with your feedback and topic suggestions.
We're on LinkedIn and blue Sky, and catch.
Speaker 2 (55:50):
Us again for the next episode next Thursday.
Speaker 3 (55:54):
See you later.
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