Ferrari Fandom, Supercharged by AI from Smart Talks with IBM

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0:00:43 Pushkin.
0:00:52 I never went to a Formula One race as a kid because we lived in southern Ontario,
0:00:54 and there was just one F1 race in Canada.
0:00:58 That race was in Montreal, a good seven-hour drive away.
0:01:03 I never watched an F1 race on television either, because we didn’t have a television.
0:01:08 But what I did have was a subscription to the car magazine Road & Track,
0:01:12 and Road & Track took F1 very seriously.
0:01:14 Every month my newest shoe would arrive,
0:01:18 I would turn immediately to the long, detailed account of that month’s race,
0:01:20 and I fell in love.
0:01:29 It’s been 50 years, but I can still rattle off the names of all the top drivers of that era from memory.
0:01:34 James Hunt, Mario Andretti, Carlos Pace, Jacques Lafitte, and of course, the greatest of them all,
0:01:43 my adolescent idol, Niki Lauda, who won two world championships in the mid-1970s with Scuderia Ferrari.
0:01:58 There’s no question that in 75, 76, I was really dominating the whole thing without any mistake, so I did nothing wrong.
0:02:00 I mean, this was perfect driving.
0:02:05 If you had met skinny pre-adolescent Malcolm in the mid-1970s in rural Ontario,
0:02:09 there’s a good chance you would have seen me in my prized Ferrari t-shirt.
0:02:10 I was a fan.
0:02:14 One of what the Italians called Tifosi, a Ferrari devotee.
0:02:17 And that’s what it meant to be a fan 50 years ago.
0:02:22 T-shirts, magazine stories, and a big Niki Lauda poster on your wall.
0:02:25 But what does it mean to be a fan today?
0:02:31 Today, we have the internet and streaming and big data and AI and all the other accoutrements of the digital age.
0:02:34 Is there a chance to reinvent the meaning of fandom?
0:02:42 My name is Malcolm Gladwell.
0:02:45 You’re listening to the latest episode of Smart Talks with IBM,
0:02:49 where we offer our listeners a glimpse behind the curtain of the world of technology.
0:02:55 In our first episode, we talked about how an AI assistant created with IBM WatsonX
0:02:58 helps future teachers practice responsive teaching.
0:03:03 Our second episode was how a custom AI model could help L’Oreal’s researchers
0:03:06 shape the future of what we put on our faces every morning.
0:03:13 In this episode, how IBM, one of the world’s preeminent technology companies,
0:03:16 is joining up with one of the world’s preeminent racing brands
0:03:21 to fundamentally change how fans interact with their favorite team.
0:03:29 The size of the Scuderia Ferrari HP fan base is staggering.
0:03:35 396 million people around the world identify as Ferrari fans.
0:03:37 396 million!
0:03:42 The only other fan bases that big belong to the iconic Premier League football teams
0:03:45 like Manchester United or Chelsea FC.
0:03:51 I don’t believe there is any other Formula One team that inspires that kind of devotion.
0:03:55 Ferrari’s job, then, isn’t to necessarily grow its fan base.
0:03:58 396 million is more than enough fans.
0:04:03 Their job is to deepen the connection people feel with the Scuderia Ferrari team.
0:04:08 But if I’m Ferrari, how do I find out more about who my fans are,
0:04:10 what they care about, what they want?
0:04:14 How do I use my archives and data to create experiences that matter to them?
0:04:19 How do I say to the guy who spent his childhood eagerly reading Road & Track every month,
0:04:24 here are other ways you can get involved with your favorite F1 team today?
0:04:31 The task of deepening an emotional connection in the digital age begins as an information problem,
0:04:34 which is where IBM comes in.
0:04:36 How would you describe what you do?
0:04:39 I’d describe it as probably the best job at IBM.
0:04:43 Yeah, I was going to say, I was going to ask you, do you have the best job at IBM?
0:04:45 I think so.
0:04:50 I’m talking to Fred Baker, who leads sports and entertainment for IBM Consulting in Europe,
0:04:52 the Middle East, and Africa.
0:04:56 You can probably guess from the accent, he’s from New Zealand.
0:05:00 We’ve had a really interesting range of experience over the past sort of five, six years.
0:05:03 We’ve worked with Premier League clubs like Liverpool Football.
0:05:06 We’ve worked with England Rugby, St. Andrews Lynx.
0:05:09 We also globally, we’ve got a global team.
0:05:15 So we work with the Masters, the US Open, ESPN Fantasy Football, the Grammys.
0:05:16 You do the tennis stuff?
0:05:17 Is that all under your remit?
0:05:19 Yeah, so we do Wimbledon as well.
0:05:20 Yep, that’s under my remit.
0:05:22 If you’ve ever watched Wimbledon on television,
0:05:27 I’m sure you’ve seen at various moments a little IBM logo on the bottom of the screen.
0:05:33 That’s because IBM has been Wimbledon’s official information technology partner since 1990.
0:05:38 When the idea of a collaboration between Ferrari and IBM was first broached,
0:05:43 Baker actually took people from Ferrari on a tour of IBM’s Wimbledon operation,
0:05:48 just so they could see what a tech company like IBM could do for a sports franchise.
0:05:50 Which Wimbledon did you take them to?
0:05:53 Last year’s champs.
0:05:55 Tell me what you showed them.
0:05:58 We take them into what we call the bunker.
0:06:04 So it’s literally underground at the champs and showed them how we bring everything to life from
0:06:12 the data capture off the courts, how we real-time categorize, serve all those points to broadcasters
0:06:15 and serve them into the app, the website for millions of fans around the world.
0:06:17 They were really impressed by that.
0:06:18 I’m also impressed by that.
0:06:24 IBM trained its AI on the language of tennis, and not only the language of tennis, but specifically
0:06:27 the language of tennis at Wimbledon.
0:06:36 So it can then decipher what an unforced error or a winner or a lob or idiosyncrasies in the
0:06:37 language, it can decipher all of that.
0:06:41 And then it can also tell what does a broadcaster like to talk about that is interesting to a
0:06:42 fan.
0:06:47 We’ve trained it so it can not only analyze everything going on in the match, it can analyze
0:06:54 past performances and rationalize results based on conditions or form, and then make predictions
0:06:55 that fans can learn from.
0:07:02 But it can also pull out on the spot really interesting milestones, moments, data points that then come
0:07:03 out of the mouth of a broadcaster.
0:07:10 IBM is running an AI model that has been trained on huge amounts of tennis data in order to
0:07:13 give human broadcasters ideas on what they can talk about.
0:07:17 And it all takes place underground, right near the courts.
0:07:23 It’s literally like it’s the underground floor of the broadcast center at Wimbledon.
0:07:25 It’s literally almost under the courts.
0:07:27 Is IBM got the entire bunker?
0:07:28 Yeah.
0:07:29 How big is the room?
0:07:35 Well, I’m sure our team would like it to be bigger, but it’s big enough.
0:07:37 There’s probably 30, 40 IBMers down there.
0:07:38 Oh, I see.
0:07:39 Man in the fall.
0:07:44 Seeing it live is just really impressive when you see how much work and intelligence goes
0:07:50 on to then make an end experience for a fan that is really beautiful and representative
0:07:52 of their brand and tradition.
0:07:59 IBM’s goal in taking Ferrari to the Wimbledon bunker was to show them what it looks like to
0:08:04 harness the power of data and how this could help shape Scuderia Ferrari’s fan and digital
0:08:04 experiences.
0:08:08 Could AI learn the language of Scuderia Ferrari?
0:08:12 What was the original app like before IBM got involved?
0:08:17 I’m speaking with Stefano Pollard, who runs fan development for Ferrari’s F1 team.
0:08:22 It was quite a good app, a very good digital product, but just an editorial product.
0:08:28 So we were providing fans news and videos, articles, and it was mainly about that.
0:08:35 The strategy and the idea was trying to use the app to have a deeper connection and interaction
0:08:37 with our fans, making it more interactive.
0:08:44 So turning it from an editorial product, which was a very good editorial product, to a more
0:08:46 interactive product, digital product.
0:08:52 With such a massive undertaking, I asked Stefano how it all started once IBM got involved.
0:08:56 We started really with a very long couple of months of discovery phase.
0:09:02 So looking at the current app, looking at fans, looking at what fans wanted from a fan app.
0:09:05 Tell me a little bit more about that phrase, something the fan wanted.
0:09:12 What is it that the superfan wasn’t getting before that was something that would tie them even
0:09:19 closer to Ferrari, having run some focus group, having read of market research, having spoken
0:09:21 to fans and being a fan.
0:09:27 The strongest insight is Ferrari fans and superfans want to be part of something, want to belong
0:09:28 to something.
0:09:33 So they want to be part of a community and ultimately they want to be part of a winning team.
0:09:37 So they want to feel closer and get access.
0:09:46 The way Stefano saw it, the opportunity wasn’t with race days.
0:09:50 When the cars are on the track, the Tifosi are already locked in.
0:09:55 But there was an opportunity to engage Ferrari fans on the other days of the week or during
0:09:56 the off season.
0:10:00 Formula One is so much more than just the race.
0:10:01 This is Fred Baker again.
0:10:07 What we can do is relive the race and bring it to life after the fact.
0:10:12 Um, we can help them prepare, we can help them relive the past and we can also bring the experience
0:10:14 around race weekend to life as well.
0:10:19 That of course made me wonder, how do you engage fans when there’s not a race happening?
0:10:24 Baker says it all comes back to data and information.
0:10:29 Talk a little bit about data collection because you’re talking about a brand with tentacles
0:10:32 everywhere and you’re trying to bring a lot of that stuff together in the app.
0:10:38 This is an organization that has for decades used data for racing, for performance.
0:10:44 It’s not historically used that data for everyone in the world to see.
0:10:47 What we’re trying to do is expose as much of it as we can to fans.
0:10:52 So part of collecting the data, the challenge was around how you go across all the disparate
0:10:55 different groups that collect data for different purposes.
0:11:01 The team that collects data on tires, the team that has data on drivers, on weather, on competitors
0:11:02 and so on.
0:11:07 So you’re trying to bring all that together and source it and make sense of it and train our
0:11:13 AI to understand what it means, what things on team radio mean, what nicknames mean, what
0:11:19 abbreviations and slang and idiosyncrasies on car specifics and track specifics and so on
0:11:19 mean.
0:11:27 And you’re also trying to design for something that is going to be fan engaging, but also appropriate
0:11:32 to all the sensitivities of the privacy that’s necessary.
0:11:36 So you want it to be able to do all of that, collect all the data, produce something for fans
0:11:37 in an automated way.
0:11:43 But in order to design something to expertly engage the Tifosi, it’s necessary to understand
0:11:48 more about the passion and the type of national identity behind the fan base.
0:11:52 You need to get inside the mind of the superfan.
0:11:58 If you wanted to meet some modern day Tifosi in the United States, you could head to a bar
0:12:00 in midtown Manhattan called Fela.
0:12:06 Every race day, Formula One fans gather at Fela to cheer on their favorite drivers, their
0:12:06 favorite teams.
0:12:08 And I mean, really cheer.
0:12:15 I sent our producer, Jake Harper, to Fela on the day of the Canadian Grand Prix so he could
0:12:17 see the fandom up close.
0:12:21 The bar gets loud and so crowded, it’s hard to move.
0:12:25 Today, the room is packed with Scuderia Ferrari HP fans.
0:12:26 Even your glasses are Ferrari.
0:12:27 I just noticed that.
0:12:33 Jake talked to a Ferrari fan named Gino, who was dressed head to toe in Ferrari’s signature
0:12:34 red and black.
0:12:35 My shoes are Ferrari.
0:12:37 Fully decked out.
0:12:39 They were making fun of me last time I was here.
0:12:40 They were like, is your underwear Ferrari?
0:12:44 And I texted my girlfriend like, babe, I need Ferrari underwear.
0:12:45 Did you get it?
0:12:46 Not yet.
0:12:46 Not yet.
0:12:47 I’ll work on it.
0:12:50 Gino’s fandom started with Ferrari as a brand.
0:12:52 I love the cars.
0:12:56 I think the 458 Scuderia is like the pinnacle of automotive engineering.
0:12:57 That’s my dream car.
0:13:00 The 430 with the glass house for the engine.
0:13:02 I mean, they’re all gorgeous.
0:13:05 It’s always been an aspiration of mine to own one.
0:13:09 So that naturally made me gravitate towards Ferrari.
0:13:17 Even when the company I worked for sponsored AMG Patronus, I was secretly like hiding my
0:13:19 Tifosi at the races.
0:13:22 It was like Clark Kent and Superman, just hiding the uniform underneath.
0:13:23 I love that.
0:13:24 I love that.
0:13:24 Yeah.
0:13:26 I was wearing a Ferrari shirt underneath my suit.
0:13:30 In one sense, Gino is typical of what Ferrari has learned about its followers.
0:13:35 A lot of F1 fans, especially newer fans, are fans of drivers.
0:13:37 But the Tifosi love Ferrari.
0:13:42 It’s the oldest brand of Formula One, the only team that has stuck around since the series
0:13:44 was founded in 1950.
0:13:47 But in another sense, Gino is not typical.
0:13:49 He lives in New York.
0:13:52 He can go to Fela to celebrate F1 with other Tifosi.
0:13:54 I’m a big racing fan.
0:13:58 And coming to this bar, I found a bunch of people that were in an F1.
0:14:03 Now I’m at this bar every weekend, just about with four or five friends that I made just
0:14:04 through racing.
0:14:11 But lots and lots of Scuderia Ferrari’s 396 million fans don’t live in a big city with
0:14:12 a Ferrari bar.
0:14:18 And lots of those 396 million fans aren’t the kind of hardcore fan who dress head to toe
0:14:20 in Ferrari’s signature red and black.
0:14:24 A group that large is diverse, necessarily.
0:14:30 And one of the first tasks that IBM and Ferrari set out to do was to understand the full range
0:14:31 of the Tifosi phenomenon.
0:14:35 People like Gino, hardcore fans, they were easy.
0:14:39 They would follow Scuderia, Ferrari, HP anywhere it wanted to go.
0:14:41 But who else was out there?
0:14:46 The most interesting addition to the F1 fan base were those who watched the phenomenally
0:14:49 successful Netflix documentary, Drive to Survive.
0:14:54 These tended to be newcomers to the sport, more Americans than Europeans.
0:14:57 What was their emotional perspective?
0:14:58 What did they want?
0:15:02 Here’s Fred Baker again, the guy with the coolest job at IBM.
0:15:07 If I’m a passionate fan, I want to read a totally different thing on the app to a casual fan who
0:15:13 is of the Netflix Drive to Survive generation versus some really niche personas that we found
0:15:18 that are super interested but don’t find it accessible yet until we start to deliver to
0:15:20 quite different needs that they have.
0:15:27 Working with IBM Watson X, Baker and his team began to develop personas, archetypes of all the
0:15:28 possible kinds of Ferrari fans.
0:15:33 Because if Ferrari wanted to get better at talking to their fans, they had to understand
0:15:34 who the fans were.
0:15:41 And the personas are helping Ferrari and IBM create an app that caters to the Tifosi in
0:15:42 all their iterations.
0:15:46 How many personas did you come up with?
0:15:49 I think we had over 10 in the end, maybe a dozen.
0:15:51 And this is different, yeah, archetypes of people.
0:15:53 Even that process is helped by AI.
0:15:57 So we train AI to help us develop out a persona.
0:16:04 We can get really detailed as to what each archetype is and their hobbies and backgrounds and so
0:16:04 on.
0:16:07 So our own Watson X helped us in developing those personas.
0:16:15 Like our research helped us uncover a segment of middle-aged women in China who Ferrari is
0:16:16 a real status symbol.
0:16:19 And they’re really interested in the scooter air Ferrari brand.
0:16:24 And now they can engage more with it, but it wasn’t yet, you know, accessible or inclusive
0:16:25 enough for them to feel comfortable doing.
0:16:30 So real spectrums of fans across those dozen personas that we had to design for.
0:16:34 Give me some more examples of personas.
0:16:36 Can you give me a couple more just so I get a flavor?
0:16:37 Yeah, sure.
0:16:42 So the other obvious one is the Drive to Survive fan and that they’re probably not a diehard
0:16:46 all their life scooter air Ferrari fan, but they’ve really got into the more social side
0:16:51 of Formula One that’s been born out of the really popular series Drive to Survive on Netflix.
0:16:56 You then have gamer personas who are into, you know, esports is growing massively in motorsport
0:17:00 and they’re probably not necessarily into the real life racing quite so much, but they’re
0:17:01 certainly into gaming.
0:17:02 So how do you appeal to them?
0:17:07 Then casual fans who are sort of into the luxury of scooter or Ferrari, but not the sport necessarily.
0:17:09 Do the personas have names?
0:17:11 Yeah.
0:17:12 I mean, we give them human names.
0:17:17 So we had a Max, we had a Alfonso, I think we had a Pedro.
0:17:23 The woman in China, is she watching F1 or is she interested more in the brand and what it
0:17:23 signifies?
0:17:23 Yeah.
0:17:28 So more in the brand and being part of a community, if I’m that persona in China, then
0:17:34 I probably don’t feel like I belong to it truly yet, but I’d love to feel like I do.
0:17:39 So I could start to become a part of a digital community, learn more about the brand, probably
0:17:46 get access to exclusive merchandise or, you know, if I can’t necessarily own a Ferrari car, which
0:17:47 let’s face it, not many people can.
0:17:50 And if we’re reliant only on the people who can own a car, then we’re probably not going
0:17:52 to get much engagement.
0:17:56 So how do we make others feel that they’re still a part of that community?
0:18:02 This is what I mean when I say the task of relating to the Ferrari fan base is a data and information
0:18:03 problem.
0:18:09 It’s about collecting, organizing and analyzing the needs and wants of an enormous pool of
0:18:13 people and speaking to each of them in their own emotional language.
0:18:20 Giving all the work Fred put into understanding Ferrari’s fan base, I was curious to know how his
0:18:21 framework would categorize me.
0:18:24 I want to figure out which persona I am.
0:18:28 So I’ll describe to you my relationship to Ferrari.
0:18:29 You tell me.
0:18:34 So what I am is a huge car nut.
0:18:37 So I like all cars.
0:18:37 Yeah.
0:18:38 Obsessively.
0:18:42 Collect on a very limited stage vintage cars.
0:18:45 Read serious car magazines.
0:18:47 Spend a lot of time on car websites.
0:18:53 Have a historical relationship to F1 because I grew up with Nicky Lauda battling James Hunt
0:18:56 in Lauda’s Ferrari years.
0:18:58 I have a great nostalgic connection.
0:19:06 Went to Italy with my nephew and went to the Ferrari factory and rented one of those to drive
0:19:06 around.
0:19:11 And I follow F1, but I don’t think I would ever go to an F1.
0:19:14 I wouldn’t fly to Miami for F1 in Miami.
0:19:15 I wouldn’t go that far.
0:19:19 And I don’t have time to watch F1 on TV on a regular basis.
0:19:21 But I’m interested.
0:19:26 And I have a red Ferrari t-shirt, which I’ve been known to wear.
0:19:29 And if I ever got really rich, would I buy a Ferrari?
0:19:30 Yes, I would.
0:19:31 Okay.
0:19:34 So where am I in your breakdown?
0:19:35 Yeah.
0:19:39 I think you’re probably a combination of the, I think it’s casual loyalist.
0:19:45 is not going to, not going to overtly go out of their way to sort of spend money on the
0:19:50 racing, but they are loyal to the Ferrari brand and they have nostalgia with it or whatever
0:19:50 it might be.
0:19:52 And then the luxury enthusiasts as well.
0:19:55 And so, and that type of fan, you’re right.
0:19:59 We’re probably not going to engage you by doing a ton more on race weekend, but we can engage
0:20:08 you by bringing this hugely rich amount of archive material, footage, feelings, and past drivers
0:20:10 of yesteryear by bringing them to life.
0:20:24 Is there an app that you saw another brand doing that served as a kind of model?
0:20:25 I don’t mean within F1.
0:20:28 I’m talking about from any other field.
0:20:35 On top of being a very sport passionate, I’m a, let’s say, a marketing passionate, a digital
0:20:37 passionate guy.
0:20:42 So I have a lot of apps and also for my job, I try to look at different markets and different
0:20:42 apps.
0:20:45 As we were talking, I was thinking about Strava.
0:20:46 I’m a huge Strava head.
0:20:48 It’s my favorite app.
0:20:52 If you don’t already know, Strava is used by millions of active people around the world.
0:20:58 I’m a runner and the app shows me a map of where I went, how fast I ran, what my heart
0:21:00 rate was, what the weather was, on and on.
0:21:01 Are you a cyclist or a runner?
0:21:02 I’m a runner.
0:21:02 I’m a runner.
0:21:06 I run marathons and ultra marathons.
0:21:08 I did last year 100 kilometers.
0:21:11 As it turns out, Stefano is a Strava head too.
0:21:14 Right after I spoke to him, I followed him on Strava.
0:21:17 He and I run roughly the same distance every day at the same pace.
0:21:22 And if I’m ever in Milan, I’m almost certainly going to look him up to see if he’ll take me
0:21:23 out on one of his favorite routes through the city.
0:21:26 This is what I love about Strava.
0:21:29 You can find people to run with and interact with.
0:21:32 Strava is a community of like-minded people.
0:21:37 And for those like me, the Strava app becomes a regular part of my daily routine.
0:21:40 And that’s what Stefano wanted for the Ferrari app.
0:21:45 Are you interested in allowing, creating sort of robust forums for Ferrari fans to communicate
0:21:47 with each other?
0:21:51 I think you have to work in three directions.
0:21:54 So direction number one is Ferrari to fans.
0:21:58 So providing them something which is compelling, which has value.
0:22:01 And this I think we’re already doing and we’re working on it.
0:22:04 Second way is fans to Ferrari.
0:22:10 So help like allowing fans to better interact with us, which was something we were not doing
0:22:11 with the previous app.
0:22:15 For example, we have just introduced two features, which are polls.
0:22:19 So basic ones, but polls and the possibility like the submit your message feature.
0:22:23 So really to work on this way, fans to Ferrari.
0:22:28 And then the third important way to build a community and nurture a community is like fans
0:22:28 to fans.
0:22:35 So if you were able to work on those three dimensions of Ferrari to fans, fans to Ferrari and fans
0:22:40 to fans, that’s how you could really create a strong community and start really monetizing
0:22:41 and creating value.
0:22:44 I think we are very strong in the first dimension right now.
0:22:46 We are building the second one.
0:22:47 So fans to Ferrari.
0:22:53 And then definitely the third one has to be there in order to have a complete community
0:22:54 engagement.
0:22:56 So let’s talk about results.
0:23:03 Scuderia Ferrari HP launched the new app at the Miami Grand Prix in 2025, incorporating AI
0:23:07 elements and tailoring it to those archetypes Fred was talking about.
0:23:11 Are more people using the app?
0:23:15 Are users spending more time on it than they did on the older version of the app?
0:23:16 Yes.
0:23:21 We doubled these months the daily active users we were having last season.
0:23:26 So compared to the average of 2024 season, we have more than double of daily active users.
0:23:30 Also, we are doubling a normal month’s downloads.
0:23:36 So we did in these months more than two times the downloads we are doing in a normal month.
0:23:41 We are increasing by 35% the average time spent on app.
0:23:42 So KPIs are good.
0:23:46 If you build the right app, they will come.
0:23:54 For generations, fans of all varieties have met in public places.
0:23:58 The stands of stadiums and bars to watch races and matches on television.
0:24:04 But there is a chance now for fandom to exist on a higher and broader level.
0:24:12 For a community to be created over the internet, even when the fans are vastly different people who live vast distances apart.
0:24:24 I could imagine Gino, in his Ferrari red and black, using the Scuderia Ferrari app, relating to me as I relive my memories of Niki Lauda from the 1970s.
0:24:33 Maybe I could use the app to learn something from the woman in China, the Tifosi newcomer, or some 17-year-old who got sucked in first by Drive to Survive.
0:24:40 I could imagine myself as part of that vision, taking my lifelong obsession to the next level.
0:25:01 Smart Talks with IBM is produced by Matt Romano, Amy Gaines McQuaid, Trina Menino, and Jake Harper.
0:25:03 We’re edited by Lacey Roberts.
0:25:05 Engineering by Nina Byrd-Lawrence.
0:25:07 Mastering by Sarah Bruguere.
0:25:08 Music by Grammoscope.
0:25:12 Strategy by Tatiana Lieberman and Cassidy Meyer.
0:25:18 Special thanks to Scuderia Ferrari HP and the bar and restaurant Fela in New York City.
0:25:24 Smart Talks with IBM is a production of Pushkin Industries and Ruby Studio at iHeartMedia.
0:25:31 To find more Pushkin podcasts, listen on the iHeartRadio app, Apple Podcasts, or wherever you listen to podcasts.
0:25:33 I’m Malcolm Glapo.
0:25:36 This is a paid advertisement from IBM.
0:25:43 The conversations on this podcast don’t necessarily represent IBM’s positions, strategies, or opinions.
0:25:56 I asked Fred Baker to come up with a hypothetical.
0:25:59 Something that could fulfill my childhood dreams.
0:26:05 Something that this type of technology could theoretically do that might appeal to a fan like me.
0:26:08 Someone whose interest in the sport went back 50 years.
0:26:14 He said, what about using AI to bring historical cars to life?
0:26:26 Bringing to life cars of the past and allows fans to simulate a 1950 Ferrari race versus a 1971 to see which car would be faster.
0:26:27 So it’s those sorts of trade-offs.
0:26:29 Wait, you could do it?
0:26:30 Wait, you could do that?
0:26:32 Tell me what that last thing you said.
0:26:33 You can run simulations?
0:26:35 Race simulations out of the app?
0:26:37 You can’t out of the app at this point.
0:26:39 So, you know…
0:26:40 No, I’m telling you, I know, potentially.
0:26:40 Potentially.
0:26:41 Yeah, yeah.
0:26:46 It can, you know, it simulates based on a whole range of factors that we can feed it and train it on.
0:26:48 Wait, so I could…
0:26:54 Hypothetically, you could allow me to compare Niki Lauda, for example, to a contemporary driver.
0:26:55 Yep.
0:27:13 And I could say, if I put Niki Lauda in a contemporary car, what you’re saying is that there is a scenario where I could recreate that era in modern cars and get a sense of how my childhood heroes were performing, would have performed in the present day.
0:27:14 Yeah, yeah.
0:27:20 Yeah, so you can analyze and understand how you would rank all drivers of all time based on the different traits of a driver, right?
0:27:28 So you can say who’s the best late braking, who was typically the best on a tight track with limited overtaking opportunities, who was the best overtaker, who was the best of all these traits.
0:27:38 You then apply those traits and rankings to different tracks and different cars where, you know, some different cars are better for a late breaker, some different cars are better for, you know, on straights and so on.
0:27:43 So you can simulate, you could hypothetically allow fans to simulate any scenario.
0:27:49 You could say who’s going to win in Monaco on a 1980 model car.
0:27:54 You could put a current driver in a 1980 car equally, so you can do all sorts of fun simulations.
0:27:57 And that’s just the beginning.