WEBVTT - Smart Talks with IBM:  Ferrari Fandom, Supercharged by AI

0:00:00.160 --> 0:00:02.960
<v Speaker 1>Hey everyone, it's Robert and Joe here. Today we've got

0:00:02.960 --> 0:00:05.240
<v Speaker 1>something a little bit different to share with you. It's

0:00:05.280 --> 0:00:09.400
<v Speaker 1>a new season of the Smart Talks with IBM podcast series.

0:00:09.720 --> 0:00:13.520
<v Speaker 2>This season on Smart Talks with IBM, Malcolm Gladwell is back,

0:00:13.520 --> 0:00:15.760
<v Speaker 2>and this time he's taking the show on the road.

0:00:15.880 --> 0:00:19.160
<v Speaker 2>Malcolm is stepping outside the studio to explore how IBM

0:00:19.239 --> 0:00:22.880
<v Speaker 2>clients are using artificial intelligence to solve real world challenges

0:00:23.079 --> 0:00:25.440
<v Speaker 2>and transform the way they do business.

0:00:25.480 --> 0:00:29.560
<v Speaker 1>From accelerating scientific breakthroughs to reimagining education. It's a fresh

0:00:29.600 --> 0:00:33.040
<v Speaker 1>look at innovation in action, where big ideas meet cutting

0:00:33.120 --> 0:00:33.960
<v Speaker 1>edge solutions.

0:00:34.320 --> 0:00:37.160
<v Speaker 2>You'll hear from industry leaders, creative thinkers, and of course

0:00:37.280 --> 0:00:40.920
<v Speaker 2>Malcolm Gladwell himself as he guides you through each story.

0:00:41.440 --> 0:00:44.680
<v Speaker 1>New episodes of Smart Talks with IBM drop every month

0:00:44.680 --> 0:00:48.279
<v Speaker 1>on the iHeartRadio app, Apple Podcasts, or wherever you get

0:00:48.320 --> 0:00:52.240
<v Speaker 1>your podcasts. Learn more at IBM dot com slash smart Talks.

0:00:52.880 --> 0:01:02.160
<v Speaker 1>This is a paid advertisement from IBM pushkin.

0:01:07.440 --> 0:01:09.400
<v Speaker 3>I never went to a Formula one race as a

0:01:09.480 --> 0:01:11.959
<v Speaker 3>kid because we lived in southern Ontario and there was

0:01:12.040 --> 0:01:14.800
<v Speaker 3>just one F one race in Canada. That race was

0:01:14.840 --> 0:01:18.640
<v Speaker 3>in Montreal. A good seven hour drive away. I never

0:01:18.680 --> 0:01:22.320
<v Speaker 3>watched F one race on television either, because we didn't.

0:01:22.040 --> 0:01:22.880
<v Speaker 4>Have a television.

0:01:23.840 --> 0:01:26.360
<v Speaker 3>But what I did have was a subscription to the

0:01:26.360 --> 0:01:29.480
<v Speaker 3>car magazine Road and Track, and Roadent Track took F

0:01:29.520 --> 0:01:33.199
<v Speaker 3>one very seriously. Every month my new issue would arrive,

0:01:33.560 --> 0:01:36.600
<v Speaker 3>I would turn immediately to the long, detailed account of

0:01:36.600 --> 0:01:43.080
<v Speaker 3>that month's race, and I fell in love. It's been

0:01:43.160 --> 0:01:45.800
<v Speaker 3>fifty years, but I can still rattle off the names

0:01:45.800 --> 0:01:48.040
<v Speaker 3>of all the top drivers of that era from memory.

0:01:48.440 --> 0:01:52.360
<v Speaker 3>James Hunt, Mario Andretti, Carlos Pace, Jacques Lafitte, and of

0:01:52.400 --> 0:01:56.360
<v Speaker 3>course the greatest of them all, my adolescent idol, Niki Lauda,

0:01:56.960 --> 0:01:59.920
<v Speaker 3>who won two world championships in the mid nineteen seventies

0:02:00.440 --> 0:02:02.040
<v Speaker 3>with Scuderia Ferrari.

0:02:02.880 --> 0:02:05.919
<v Speaker 4>He was world championship material from the moment he joined

0:02:05.960 --> 0:02:09.120
<v Speaker 4>the Ferrari team.

0:02:09.639 --> 0:02:12.640
<v Speaker 2>There's no question that in seventy five seventy six I

0:02:12.760 --> 0:02:16.680
<v Speaker 2>was really dominating the whole thing without any mistake. So

0:02:16.800 --> 0:02:17.639
<v Speaker 2>I did nothing wrong.

0:02:17.800 --> 0:02:19.680
<v Speaker 5>I mean, this was perfect driving.

0:02:20.360 --> 0:02:22.800
<v Speaker 3>If you had met skinny pre adolescent Malcolm in the

0:02:22.800 --> 0:02:25.960
<v Speaker 3>mid nineteen seventies in rural Ontario, there's a good chance

0:02:25.960 --> 0:02:28.440
<v Speaker 3>you would have seen me in my prize Ferrari T shirt.

0:02:28.880 --> 0:02:32.040
<v Speaker 3>I was a fan, one of what the Italians called tifosi,

0:02:32.440 --> 0:02:35.239
<v Speaker 3>a Ferrari devote, And that's what it meant to be

0:02:35.280 --> 0:02:39.440
<v Speaker 3>a fan fifty years ago, t shirts, magazine stories, and

0:02:39.480 --> 0:02:42.480
<v Speaker 3>a big Nikki Lauta poster on your wall. But what

0:02:42.520 --> 0:02:45.560
<v Speaker 3>does it mean to be a fan today? Today we

0:02:45.600 --> 0:02:48.160
<v Speaker 3>have the Internet and streaming and big data and AI

0:02:48.240 --> 0:02:50.960
<v Speaker 3>and all the other accouterment of the digital age. Is

0:02:51.000 --> 0:03:00.120
<v Speaker 3>there a chance to reinvent the meaning of fandom? My

0:03:00.160 --> 0:03:02.840
<v Speaker 3>name is Malcolm Gladwell. You're listening to the latest episode

0:03:02.880 --> 0:03:05.840
<v Speaker 3>of Smart Talks with IBM, where we offer our listeners

0:03:05.880 --> 0:03:08.440
<v Speaker 3>a glimpse behind the curtain of the world of technology.

0:03:09.200 --> 0:03:11.960
<v Speaker 3>In our first episode, we talked about how an AI

0:03:12.040 --> 0:03:17.720
<v Speaker 3>assistant created with IBM watsonex helps future teachers practice responsive teaching.

0:03:18.160 --> 0:03:21.440
<v Speaker 3>Our second episode was how a custom AI model could

0:03:21.520 --> 0:03:24.600
<v Speaker 3>help Loreel's researchers shape the future of what we put

0:03:24.680 --> 0:03:29.560
<v Speaker 3>on our faces every morning. In this episode, how IBM,

0:03:29.800 --> 0:03:33.239
<v Speaker 3>one of the world's pre eminent technology companies, is joining

0:03:33.280 --> 0:03:35.840
<v Speaker 3>up with one of the world's pre eminent racing brands

0:03:36.200 --> 0:03:44.280
<v Speaker 3>to fundamentally change how fans interact with their favorite team.

0:03:44.600 --> 0:03:48.640
<v Speaker 3>The size of the Scuderia Ferrari HP fan base is staggering.

0:03:49.200 --> 0:03:52.440
<v Speaker 3>Three hundred and ninety six million people around the world

0:03:52.480 --> 0:03:56.720
<v Speaker 3>identify as Ferrari fans. Three hundred and ninety six million.

0:03:57.240 --> 0:03:59.560
<v Speaker 3>The only other fan base is that big belong to

0:03:59.600 --> 0:04:03.480
<v Speaker 3>the icon Premier League Football teams like Manchester United or

0:04:03.560 --> 0:04:07.640
<v Speaker 3>Chelsea FC. I don't believe there is any other Formula

0:04:07.640 --> 0:04:12.000
<v Speaker 3>one team that inspires that kind of devotion. Ferrari's job, then,

0:04:12.120 --> 0:04:15.600
<v Speaker 3>isn't necessarily grow its fan base. Three hundred and ninety

0:04:15.640 --> 0:04:18.680
<v Speaker 3>six million is more than enough fans. Their job is

0:04:18.720 --> 0:04:21.840
<v Speaker 3>to deepen the connection people feel with the scudery A

0:04:21.880 --> 0:04:25.279
<v Speaker 3>Ferrari team. But if I'm Ferrari, how do I find

0:04:25.279 --> 0:04:28.000
<v Speaker 3>out more about who my fans are, what they care about,

0:04:28.320 --> 0:04:30.520
<v Speaker 3>what they want? How do I use my archives and

0:04:30.600 --> 0:04:34.000
<v Speaker 3>data to create experiences that matter to them? How do

0:04:34.080 --> 0:04:36.600
<v Speaker 3>I say to the guy who spent his childhood eagerly

0:04:36.640 --> 0:04:39.880
<v Speaker 3>reading roadent track every month? Here are other ways you

0:04:39.920 --> 0:04:43.160
<v Speaker 3>can get involved with your favorite F one team Today.

0:04:44.120 --> 0:04:47.440
<v Speaker 3>The task of deepening an emotional connection in the digital

0:04:47.480 --> 0:04:52.400
<v Speaker 3>age begins as an information problem, which is where IBM

0:04:52.480 --> 0:04:55.360
<v Speaker 3>comes in. How would you describe what you do.

0:04:56.279 --> 0:04:58.320
<v Speaker 6>I describe it as the probably the best job, but

0:04:58.400 --> 0:04:58.760
<v Speaker 6>I bem.

0:04:59.000 --> 0:05:00.599
<v Speaker 3>Yeah, I was going to say, I was going to

0:05:00.600 --> 0:05:02.640
<v Speaker 3>ask you, do you have the best job at IBM?

0:05:03.600 --> 0:05:04.159
<v Speaker 6>I think so.

0:05:04.800 --> 0:05:07.719
<v Speaker 3>I'm talking to Fred Baker, who leads sports and Entertainment

0:05:07.760 --> 0:05:11.120
<v Speaker 3>for IBM consulting in Europe, the Middle East and Africa.

0:05:11.920 --> 0:05:14.880
<v Speaker 3>You can probably guess from the accent he's from New Zealand.

0:05:15.240 --> 0:05:17.560
<v Speaker 6>We've had a really interesting range of experience over the

0:05:17.640 --> 0:05:20.159
<v Speaker 6>past sort of five six years. We've worked with Premier

0:05:20.240 --> 0:05:23.960
<v Speaker 6>League clubs like Liverpool Football. We've worked with England Rugby

0:05:24.360 --> 0:05:28.120
<v Speaker 6>St Andrews Links. We also globally, we've got a global team,

0:05:28.200 --> 0:05:31.679
<v Speaker 6>so we work with the Masters, the US Open, ESPN,

0:05:31.760 --> 0:05:33.880
<v Speaker 6>Fantasy Football, the Grammys.

0:05:34.279 --> 0:05:36.719
<v Speaker 4>You do the tennis stuff. Is it all under Europe?

0:05:36.800 --> 0:05:38.880
<v Speaker 6>Yeah, so we do Wimbledon as well. Yep, that's under

0:05:38.880 --> 0:05:39.279
<v Speaker 6>my rima.

0:05:39.680 --> 0:05:42.400
<v Speaker 3>If you've ever watched Wimbledon on television, I'm sure you've

0:05:42.400 --> 0:05:45.240
<v Speaker 3>seen at various moments a little IBM logo on the

0:05:45.240 --> 0:05:49.159
<v Speaker 3>bottom of the screen. That's because IBM has been Wimbledon's

0:05:49.200 --> 0:05:54.480
<v Speaker 3>official information technology partner since nineteen ninety, when the idea

0:05:54.520 --> 0:05:57.599
<v Speaker 3>of a collaboration between Ferrari and IBM was first broached.

0:05:58.040 --> 0:06:00.680
<v Speaker 3>Baker actually took people from Ferrari on a tour of

0:06:00.800 --> 0:06:04.000
<v Speaker 3>IBM's Wimbledon operation, just so they could see what a

0:06:04.000 --> 0:06:07.440
<v Speaker 3>tech company like IBM could do for a sports franchise.

0:06:08.240 --> 0:06:08.960
<v Speaker 4>Which Wimbledon.

0:06:09.040 --> 0:06:12.400
<v Speaker 6>Did you take them to last year's champs?

0:06:12.560 --> 0:06:14.520
<v Speaker 3>Tell me what you showed them.

0:06:15.000 --> 0:06:17.560
<v Speaker 6>We take them into what we call the bunker, so

0:06:17.800 --> 0:06:21.360
<v Speaker 6>it's literally underground at the Champs, and showed them how

0:06:21.400 --> 0:06:25.240
<v Speaker 6>we bring everything to life from the data capture off

0:06:25.240 --> 0:06:29.920
<v Speaker 6>the courts, how we real time categorize, serve all those

0:06:29.920 --> 0:06:32.359
<v Speaker 6>points to broadcasters and serve them into the app the

0:06:32.400 --> 0:06:34.760
<v Speaker 6>website for millions of fans around the world. They were

0:06:34.760 --> 0:06:35.680
<v Speaker 6>really impressed by that.

0:06:36.320 --> 0:06:39.560
<v Speaker 3>I'm also impressed by that IBM trained it on the

0:06:39.640 --> 0:06:42.400
<v Speaker 3>language of tennis, and not only the language of tennis,

0:06:42.720 --> 0:06:46.159
<v Speaker 3>but specifically the language of tennis at Wimbledon.

0:06:46.920 --> 0:06:51.359
<v Speaker 6>So it can then decipher what an unforced era or

0:06:51.400 --> 0:06:54.839
<v Speaker 6>a winner or a lob or you know, idiosyncrasies in

0:06:54.839 --> 0:06:56.680
<v Speaker 6>the language. It can decipher all of that, and then

0:06:56.680 --> 0:06:58.800
<v Speaker 6>it can also tell what is a broadcast like to

0:06:58.800 --> 0:07:01.719
<v Speaker 6>talk about that is in to a fan. You know,

0:07:01.839 --> 0:07:04.360
<v Speaker 6>we've trained it so it can not only analyze everything

0:07:04.360 --> 0:07:07.279
<v Speaker 6>going on in the match. It can analyze past performances

0:07:07.320 --> 0:07:12.240
<v Speaker 6>and rationalize results based on conditions or form and then

0:07:12.280 --> 0:07:14.520
<v Speaker 6>make predictions that fans can learn from. But it can

0:07:14.560 --> 0:07:19.480
<v Speaker 6>also pull out on the spot really interesting milestones, moments,

0:07:19.560 --> 0:07:21.960
<v Speaker 6>data points that then come out of the mouth of

0:07:22.000 --> 0:07:22.600
<v Speaker 6>a broadcaster.

0:07:23.480 --> 0:07:26.080
<v Speaker 3>IBM is running an AI model that has been trained

0:07:26.160 --> 0:07:29.320
<v Speaker 3>on huge amounts of tennis data in order to give

0:07:29.400 --> 0:07:33.040
<v Speaker 3>human broadcasters ideas on what they can talk about. And

0:07:33.080 --> 0:07:36.800
<v Speaker 3>it all takes place underground, right near the courts.

0:07:37.280 --> 0:07:41.160
<v Speaker 6>It's literally like it's the underground floor of the broadcast

0:07:41.200 --> 0:07:44.200
<v Speaker 6>center at Wimbledon. It's literally almost under the courts.

0:07:44.440 --> 0:07:46.000
<v Speaker 4>Is IBM got the entire bunker?

0:07:46.720 --> 0:07:47.160
<v Speaker 6>Yeah?

0:07:47.240 --> 0:07:48.640
<v Speaker 4>How big is the room?

0:07:49.960 --> 0:07:52.000
<v Speaker 6>I'm sure our team would like it to be bigger,

0:07:52.040 --> 0:07:56.040
<v Speaker 6>but it's big enough. There's probably thirty forty IBM is

0:07:56.080 --> 0:08:00.760
<v Speaker 6>down there. Man. Seeing it live is just impressive when

0:08:00.800 --> 0:08:04.440
<v Speaker 6>you see how much work and intelligence goes on to

0:08:04.520 --> 0:08:06.960
<v Speaker 6>then make an end experience for a fan that is

0:08:07.680 --> 0:08:11.520
<v Speaker 6>really beautiful and representative of their brand and tradition.

0:08:12.520 --> 0:08:16.120
<v Speaker 3>IBM's goal in taking Ferrari to the Wimbledon bunker was

0:08:16.160 --> 0:08:18.600
<v Speaker 3>to show them what it looks like to harness the

0:08:18.600 --> 0:08:21.600
<v Speaker 3>power of data and how this could help shape Scuderia

0:08:21.640 --> 0:08:26.320
<v Speaker 3>Ferrari's fan and digital experiences. Could AI learn the language

0:08:26.560 --> 0:08:30.040
<v Speaker 3>of Scuderia Ferrari. What was the original app like before

0:08:30.080 --> 0:08:33.880
<v Speaker 3>IBM got involved. I'm speaking with Stefano Pollard, who runs

0:08:33.920 --> 0:08:36.200
<v Speaker 3>fan development for Ferrari's f one team.

0:08:36.360 --> 0:08:39.760
<v Speaker 7>It was quite a good app, a very good digital product,

0:08:39.760 --> 0:08:43.320
<v Speaker 7>but just an editorial product. So we were providing fans

0:08:43.600 --> 0:08:47.320
<v Speaker 7>news and videos, articles and it was mainly about that.

0:08:48.040 --> 0:08:51.080
<v Speaker 7>The strategy and the idea was trying to use the

0:08:51.120 --> 0:08:54.839
<v Speaker 7>app to have a deeper connection and interaction with our fans,

0:08:54.880 --> 0:08:59.520
<v Speaker 7>make it more interactive. So turning it from an editorial product,

0:08:59.760 --> 0:09:02.760
<v Speaker 7>which was a very good editorial product, to a more

0:09:03.120 --> 0:09:05.320
<v Speaker 7>interactive product, digital product.

0:09:05.160 --> 0:09:08.560
<v Speaker 3>With such a massive undertaking. I asked Stephen how it

0:09:08.600 --> 0:09:10.960
<v Speaker 3>all started once IBM got involved.

0:09:11.840 --> 0:09:14.720
<v Speaker 7>We started really with a very long couple of months

0:09:14.720 --> 0:09:18.480
<v Speaker 7>of discovery phase. So looking at the current app, looking

0:09:18.520 --> 0:09:21.640
<v Speaker 7>at fans, looking at what fans wanted from an app.

0:09:21.920 --> 0:09:23.800
<v Speaker 3>Tell me a little bit more about that phrase something

0:09:23.840 --> 0:09:26.680
<v Speaker 3>a fan wanted, What is it that the super fan

0:09:27.840 --> 0:09:31.560
<v Speaker 3>wasn't getting before? That was something that would tie them

0:09:31.559 --> 0:09:32.960
<v Speaker 3>even closer to Ferrari.

0:09:33.240 --> 0:09:38.040
<v Speaker 7>Having run some focused group, having having read that market research,

0:09:38.080 --> 0:09:40.920
<v Speaker 7>having spoken to fans, and being a fan. The strongest

0:09:41.040 --> 0:09:44.880
<v Speaker 7>inside is feridy. Fans and super fans want to be

0:09:45.040 --> 0:09:48.200
<v Speaker 7>part of something, want to belong to something, so they

0:09:48.240 --> 0:09:50.679
<v Speaker 7>want to be part of a community, and ultimately they

0:09:50.679 --> 0:09:53.880
<v Speaker 7>want to be part of a winning team, so they

0:09:53.920 --> 0:09:56.679
<v Speaker 7>want to feel closer and get access.

0:10:01.320 --> 0:10:05.000
<v Speaker 3>The way Stefano side. The opportunity wasn't with race days

0:10:05.520 --> 0:10:07.960
<v Speaker 3>when the cars are on the track, the tafosi are

0:10:08.000 --> 0:10:11.280
<v Speaker 3>already locked in, but there was an opportunity to engage

0:10:11.280 --> 0:10:14.360
<v Speaker 3>Ferrari fans on the other days of the week or

0:10:14.440 --> 0:10:15.400
<v Speaker 3>during the off season.

0:10:15.760 --> 0:10:19.200
<v Speaker 6>Formula One is so much more than just the race.

0:10:19.520 --> 0:10:20.760
<v Speaker 4>This is Fred Baker again.

0:10:21.040 --> 0:10:24.800
<v Speaker 6>What we can do is relive the race and bring

0:10:24.840 --> 0:10:28.040
<v Speaker 6>it to life after the fact. We can help them prepare,

0:10:28.080 --> 0:10:30.000
<v Speaker 6>we can help them relive the past, and we can

0:10:30.040 --> 0:10:33.200
<v Speaker 6>also bring the experience around race weekend to life as well.

0:10:33.760 --> 0:10:36.720
<v Speaker 3>That of course, maybe wonder how do you engage fans

0:10:36.760 --> 0:10:40.640
<v Speaker 3>when there's not a race happening. Baker says it all

0:10:40.640 --> 0:10:44.480
<v Speaker 3>comes back to data and information. Talk a little bit

0:10:44.440 --> 0:10:47.240
<v Speaker 3>about data collection, because you're talking about a brand with

0:10:47.880 --> 0:10:50.400
<v Speaker 3>tentacles everywhere, and you're trying to bring a lot of

0:10:50.440 --> 0:10:51.680
<v Speaker 3>that stuff together in the app.

0:10:52.200 --> 0:10:55.440
<v Speaker 6>This is an organization that has for decades used data

0:10:55.800 --> 0:10:59.960
<v Speaker 6>for racing the performance, it's not historically used that data

0:11:00.360 --> 0:11:04.080
<v Speaker 6>for everyone in the world to see. What we're trying

0:11:04.120 --> 0:11:05.560
<v Speaker 6>to do is expose as much of it as we

0:11:05.600 --> 0:11:08.360
<v Speaker 6>can to fans. So part of collecting the data, the

0:11:08.440 --> 0:11:10.880
<v Speaker 6>challenge with around how you go across all the disparate

0:11:11.040 --> 0:11:14.920
<v Speaker 6>different groups that collect data for different purposes. The team

0:11:14.960 --> 0:11:17.480
<v Speaker 6>that collects data on tires, the team that has data

0:11:17.559 --> 0:11:20.920
<v Speaker 6>on drivers, on whether or on competitors, and so on.

0:11:21.600 --> 0:11:23.760
<v Speaker 6>So you're trying to bring all that together and source

0:11:23.800 --> 0:11:26.720
<v Speaker 6>it and make sense of it and train our AI

0:11:26.800 --> 0:11:30.440
<v Speaker 6>to understand what it means, what things on team radio mean,

0:11:30.640 --> 0:11:35.160
<v Speaker 6>what nicknames mean, what abbreviations and slang and idiosyncrasies on

0:11:35.640 --> 0:11:38.960
<v Speaker 6>car specifics and track specifics and so on mean. And

0:11:39.000 --> 0:11:42.679
<v Speaker 6>you're also trying to design for something that is going

0:11:42.720 --> 0:11:47.120
<v Speaker 6>to be fan engaging but also appropriate to all the

0:11:47.160 --> 0:11:51.720
<v Speaker 6>sensitivities of the privacy that's necessary. So you want it

0:11:51.760 --> 0:11:53.480
<v Speaker 6>to be able to do all of that, collect all

0:11:53.480 --> 0:11:56.160
<v Speaker 6>the data, produce something for fans in an automated way.

0:11:57.120 --> 0:12:00.800
<v Speaker 3>But in order to design something to expertly engage the tafosi,

0:12:01.200 --> 0:12:04.600
<v Speaker 3>it's necessary to understand more about the passion and the

0:12:04.640 --> 0:12:08.959
<v Speaker 3>type of national identity behind the fan base. You need

0:12:09.160 --> 0:12:12.800
<v Speaker 3>to get inside the mind of the super fan. If

0:12:12.840 --> 0:12:15.040
<v Speaker 3>you wanted to meet some modern day tafosi in the

0:12:15.120 --> 0:12:17.720
<v Speaker 3>United States, you could head to a bar in Midtown

0:12:17.760 --> 0:12:22.200
<v Speaker 3>Manhattan called Fela. Every race day, Formula One fans gathered

0:12:22.240 --> 0:12:25.600
<v Speaker 3>Feala to cheer on their favorite drivers, their favorite teams,

0:12:25.640 --> 0:12:31.079
<v Speaker 3>and I mean really cheer. I sent our producer Jake

0:12:31.120 --> 0:12:33.760
<v Speaker 3>Harper to Feala on the day of the Canadian Grand

0:12:33.800 --> 0:12:36.880
<v Speaker 3>Prix so you could see the fandom up close. The

0:12:36.920 --> 0:12:39.840
<v Speaker 3>bar gets loud and so crowded it's hard to move.

0:12:40.440 --> 0:12:43.960
<v Speaker 3>Today the room is packed with Scuderia Ferrari HP fans.

0:12:44.280 --> 0:12:45.760
<v Speaker 6>Even your glasses are Ferrari.

0:12:45.840 --> 0:12:48.040
<v Speaker 3>I just noticed that Jake talked to a Ferrari fan

0:12:48.120 --> 0:12:51.600
<v Speaker 3>named Gino who was dressed head to toe in Ferrari's

0:12:51.640 --> 0:12:53.400
<v Speaker 3>signature red and black.

0:12:53.320 --> 0:12:54.960
<v Speaker 8>And my shoes are Ferraria.

0:12:55.480 --> 0:12:56.280
<v Speaker 6>Fully checked out.

0:12:56.360 --> 0:12:58.120
<v Speaker 5>They were making fun of me last time I was here.

0:12:58.160 --> 0:13:01.680
<v Speaker 5>They're like, is your underwear Ferrari? I texted my girlfriend, like, Babe,

0:13:01.720 --> 0:13:03.080
<v Speaker 5>I need Ferrari underwear.

0:13:03.960 --> 0:13:04.600
<v Speaker 6>Did you get it?

0:13:04.679 --> 0:13:06.680
<v Speaker 8>Not yet? Not yet, I'll work on it.

0:13:07.160 --> 0:13:09.800
<v Speaker 3>Gino's fandom started with Ferrari as a brand.

0:13:10.720 --> 0:13:11.600
<v Speaker 8>I love the cars.

0:13:11.720 --> 0:13:13.800
<v Speaker 5>I think the four fifty eight Scoodaria is like the

0:13:13.840 --> 0:13:15.680
<v Speaker 5>pinnacle of automotive engineering.

0:13:15.760 --> 0:13:18.200
<v Speaker 8>That's my dream car. The four point thirty with the

0:13:18.240 --> 0:13:21.160
<v Speaker 8>glass house for the engine. I mean, that's They're all gorgeous.

0:13:21.480 --> 0:13:24.160
<v Speaker 5>It's always been an aspiration of mine to own one,

0:13:25.040 --> 0:13:27.040
<v Speaker 5>so that naturally.

0:13:26.640 --> 0:13:28.360
<v Speaker 8>Made me gravitate towards Ferrari.

0:13:28.760 --> 0:13:32.120
<v Speaker 5>Even when the company I worked for a sponsored AMG Petronis,

0:13:32.600 --> 0:13:38.679
<v Speaker 5>I was secretly like hiding my taphosi at the races, like.

0:13:38.800 --> 0:13:41.880
<v Speaker 6>Clark Kenton Superman. You're just hiding the uniform underneath.

0:13:41.960 --> 0:13:43.520
<v Speaker 8>I love that. I love that. Yeah, I was wearing

0:13:43.520 --> 0:13:45.280
<v Speaker 8>a Ferrari shirt underneath my suit.

0:13:45.960 --> 0:13:48.400
<v Speaker 3>In one sense, Gino is typical of what Ferrari has

0:13:48.480 --> 0:13:51.160
<v Speaker 3>learned about its followers. A lot of F one fans,

0:13:51.440 --> 0:13:55.439
<v Speaker 3>especially newer fans, are fans of drivers, but the tafosi

0:13:55.960 --> 0:13:59.200
<v Speaker 3>love Ferrari. It's the oldest brand in Formula One, the

0:13:59.240 --> 0:14:01.800
<v Speaker 3>only team that is stuck around since the series was

0:14:01.840 --> 0:14:05.920
<v Speaker 3>founded in nineteen fifty. But in another sense, Gino is

0:14:06.000 --> 0:14:08.840
<v Speaker 3>not typical. He lives in New York. He can go

0:14:08.920 --> 0:14:11.400
<v Speaker 3>to Fala to celebrate F one with other tefosi.

0:14:11.600 --> 0:14:14.600
<v Speaker 5>I'm a big racing fan, and coming to this bar,

0:14:15.400 --> 0:14:17.080
<v Speaker 5>I found a bunch of people that were in a

0:14:17.360 --> 0:14:17.680
<v Speaker 5>F one.

0:14:17.720 --> 0:14:18.360
<v Speaker 8>Now I'm at this.

0:14:18.360 --> 0:14:22.160
<v Speaker 5>Bar every weekend just about with four or five friends

0:14:22.160 --> 0:14:23.600
<v Speaker 5>that I made just through racings.

0:14:25.120 --> 0:14:27.800
<v Speaker 3>But lots and lots of Scuderia Ferraris three hundred and

0:14:27.880 --> 0:14:30.680
<v Speaker 3>ninety six million fans don't live in a big city

0:14:30.680 --> 0:14:33.440
<v Speaker 3>with a Ferrari bar, and lots of those three hundred

0:14:33.440 --> 0:14:36.240
<v Speaker 3>and ninety six million fans aren't the kind of hardcore

0:14:36.320 --> 0:14:38.880
<v Speaker 3>fan who dressed head to toe in Ferrari's signature red

0:14:38.920 --> 0:14:43.840
<v Speaker 3>and black. A group that large is diverse, necessarily, and

0:14:43.880 --> 0:14:46.360
<v Speaker 3>one of the first tasks that IBM and Ferrari set

0:14:46.360 --> 0:14:49.400
<v Speaker 3>out to do was to understand the full range of

0:14:49.440 --> 0:14:54.560
<v Speaker 3>the tafosi phenomenon. People like Gino hardcore fans. They were easy,

0:14:54.800 --> 0:14:57.920
<v Speaker 3>They would follow Scuderia Ferrari HB anywhere it wanted to go.

0:14:58.480 --> 0:15:02.000
<v Speaker 3>But who else was out there? The most interesting addition

0:15:02.280 --> 0:15:04.600
<v Speaker 3>to the F one fan base were those who watched

0:15:04.600 --> 0:15:09.840
<v Speaker 3>the phenomenally successful Netflix documentary Drive to Survive. These tended

0:15:09.880 --> 0:15:13.800
<v Speaker 3>to be newcomers to the sport, more Americans than Europeans.

0:15:14.360 --> 0:15:18.560
<v Speaker 3>What was their emotional perspective? What did they want? Here's

0:15:18.600 --> 0:15:21.360
<v Speaker 3>Fred Baker again, the guy with the coolest job at IBM.

0:15:21.600 --> 0:15:23.320
<v Speaker 6>If I'm a passionate fan, I want to read a

0:15:23.360 --> 0:15:26.440
<v Speaker 6>totally different thing on the app to a casual fan

0:15:26.480 --> 0:15:30.000
<v Speaker 6>who is of the Netflix drive to Survive generation versus

0:15:30.480 --> 0:15:32.600
<v Speaker 6>you know, some really niche personas that we found that

0:15:32.880 --> 0:15:36.120
<v Speaker 6>are super interested but don't find it accessible yet until

0:15:36.160 --> 0:15:39.080
<v Speaker 6>we start to deliver to quite different needs that they have.

0:15:39.320 --> 0:15:42.440
<v Speaker 3>Working with IBM WATSONEX, Baker and his team began to

0:15:42.480 --> 0:15:47.560
<v Speaker 3>develop personas archetypes of all the possible kinds of Ferrari fans,

0:15:48.120 --> 0:15:50.360
<v Speaker 3>because if Ferrari wanted to get better at talking to

0:15:50.400 --> 0:15:53.600
<v Speaker 3>their fans, they had to understand who the fans were,

0:15:54.240 --> 0:15:57.960
<v Speaker 3>and the personas are helping Ferrari and IBM create an

0:15:58.000 --> 0:16:01.800
<v Speaker 3>app that caters to the tafosi in all their iterations.

0:16:02.960 --> 0:16:05.280
<v Speaker 4>How many personas did you come up with?

0:16:05.960 --> 0:16:08.240
<v Speaker 6>I think we had over ten in the end, maybe

0:16:08.280 --> 0:16:10.840
<v Speaker 6>a dozen. And this is different, yeah, archetypes of people.

0:16:10.840 --> 0:16:13.560
<v Speaker 6>Even that process is helped by AI, so we train

0:16:13.640 --> 0:16:16.480
<v Speaker 6>AI to help us develop out a persona. We can

0:16:16.520 --> 0:16:20.840
<v Speaker 6>get really detailed as to what each archetype is and

0:16:20.880 --> 0:16:24.160
<v Speaker 6>their hobbies and backgrounds and so on. So our own

0:16:24.160 --> 0:16:28.120
<v Speaker 6>watsonex helped us in developing those personas, like our research

0:16:28.440 --> 0:16:31.800
<v Speaker 6>helped us uncover a segment of middle aged women in

0:16:31.880 --> 0:16:35.920
<v Speaker 6>China who Ferrari is a real status symbol and they're

0:16:35.960 --> 0:16:38.480
<v Speaker 6>really interested in the Scuderia Ferrari brand and now they

0:16:38.520 --> 0:16:42.680
<v Speaker 6>can engage more with it, but it wasn't yet accessible

0:16:42.760 --> 0:16:44.880
<v Speaker 6>or inclusive enough for them to feel comfortable doing so.

0:16:45.120 --> 0:16:48.720
<v Speaker 6>Real spectrums of fans across those dozen personas that we

0:16:48.760 --> 0:16:49.720
<v Speaker 6>had to design for.

0:16:50.360 --> 0:16:54.440
<v Speaker 3>Give me some more examples of personas. Can you give

0:16:54.440 --> 0:16:55.840
<v Speaker 3>you a couple more just so get a flavor?

0:16:56.000 --> 0:16:58.080
<v Speaker 6>Yeah? Sure. So. The other obvious one is the Drive

0:16:58.120 --> 0:17:01.360
<v Speaker 6>to Survive fan and that they're probably not a diehard

0:17:01.600 --> 0:17:03.760
<v Speaker 6>all their lives Scuterier Ferrari fan, but they've really got

0:17:03.760 --> 0:17:06.200
<v Speaker 6>into the more social side of formula one that's been

0:17:06.680 --> 0:17:09.520
<v Speaker 6>born out of the really popular series Drive to Survive

0:17:09.600 --> 0:17:12.680
<v Speaker 6>on Netflix. You then have gamer personas who are into

0:17:13.400 --> 0:17:17.159
<v Speaker 6>esports is growing massively in motorsport, and they're probably not

0:17:17.200 --> 0:17:19.600
<v Speaker 6>necessarily into the real life racing quite so much, but

0:17:19.600 --> 0:17:21.520
<v Speaker 6>they're certainly into gaming, So how do you appeal to

0:17:21.560 --> 0:17:24.040
<v Speaker 6>them then casual fans who are sort of into the

0:17:24.119 --> 0:17:27.359
<v Speaker 6>luxury of scudo Ferrari but not the sport necessarily do

0:17:27.480 --> 0:17:30.760
<v Speaker 6>the personas have names? Yeah, I mean we give them

0:17:30.840 --> 0:17:34.360
<v Speaker 6>human names. So we had a Max, we had a Alfonso.

0:17:34.600 --> 0:17:35.960
<v Speaker 6>I think we had a Pedro.

0:17:36.760 --> 0:17:38.359
<v Speaker 4>Two women in China.

0:17:38.560 --> 0:17:40.760
<v Speaker 3>Is she watching F one or is she interested more

0:17:40.800 --> 0:17:42.359
<v Speaker 3>in the brand and what it signifies?

0:17:42.520 --> 0:17:45.119
<v Speaker 6>Yeah, more in the brand and being part of a community.

0:17:45.440 --> 0:17:48.080
<v Speaker 6>If I'm that persona in China, then I probably don't

0:17:48.080 --> 0:17:52.280
<v Speaker 6>feel like I belong to it truly yet, but I'd

0:17:52.280 --> 0:17:54.120
<v Speaker 6>love to feel like I do, so I could start

0:17:54.160 --> 0:17:56.600
<v Speaker 6>to become a part of a digital community, learn more

0:17:56.640 --> 0:18:01.119
<v Speaker 6>about the brand, probably get access to exclusive merchandise, or

0:18:01.880 --> 0:18:04.800
<v Speaker 6>you know, if I can't necessarily own a Ferrari car,

0:18:04.800 --> 0:18:07.119
<v Speaker 6>which let's face it, not many people can. And if

0:18:07.119 --> 0:18:09.000
<v Speaker 6>we're relyinged only on the people who can own a car,

0:18:09.040 --> 0:18:11.320
<v Speaker 6>then we're probably not going to get much engagement. So

0:18:11.359 --> 0:18:13.760
<v Speaker 6>how do we make others feel that they're still a

0:18:13.800 --> 0:18:15.359
<v Speaker 6>part of that community.

0:18:16.119 --> 0:18:17.800
<v Speaker 3>This is what I mean when I say the task

0:18:17.880 --> 0:18:20.520
<v Speaker 3>of relating to the Ferrari fan base is a data

0:18:20.640 --> 0:18:25.360
<v Speaker 3>and information problem. It's about collecting, organizing, and analyzing the

0:18:25.359 --> 0:18:29.000
<v Speaker 3>needs and wants of an enormous pool of people and

0:18:29.080 --> 0:18:32.520
<v Speaker 3>speaking to each of them in their own emotional language.

0:18:34.040 --> 0:18:36.960
<v Speaker 3>Giving all the work Fred put into understanding Ferrari's fan base,

0:18:37.400 --> 0:18:40.480
<v Speaker 3>I was curious to know how his framework would categorize me.

0:18:41.600 --> 0:18:44.439
<v Speaker 3>I want to figure out which persona I am. So

0:18:44.680 --> 0:18:47.399
<v Speaker 3>I'll describe to you my relationship to Ferrari and you

0:18:47.480 --> 0:18:52.920
<v Speaker 3>tell me so what I am is a huge car,

0:18:53.119 --> 0:18:59.199
<v Speaker 3>not so like all cars. Yeah, obsessively collect on a

0:18:59.280 --> 0:19:05.280
<v Speaker 3>very limited stage vintage cars, read serious car magazines, spend

0:19:05.280 --> 0:19:08.040
<v Speaker 3>a lot of time my car websites. Have a historical

0:19:08.080 --> 0:19:10.480
<v Speaker 3>relationship to have one. Because I grew up with Nikki

0:19:10.560 --> 0:19:15.480
<v Speaker 3>Lauda battling James Hunt in loudest for our years. I

0:19:15.520 --> 0:19:19.480
<v Speaker 3>have a grit nostalgic connection. Went to Italy with my

0:19:19.720 --> 0:19:23.199
<v Speaker 3>nephew and went to the Ferrari factory and rented one

0:19:23.240 --> 0:19:26.760
<v Speaker 3>of those to drive around, you know, and.

0:19:26.760 --> 0:19:27.960
<v Speaker 4>I follow that F one. But I wouldn't.

0:19:28.000 --> 0:19:30.320
<v Speaker 3>I would don't think I would ever go to an

0:19:30.480 --> 0:19:33.040
<v Speaker 3>I wouldn't fly to Miami for F one. Miami, I

0:19:33.040 --> 0:19:36.399
<v Speaker 3>wouldn't go that far, and I don't have time to

0:19:36.440 --> 0:19:38.720
<v Speaker 3>watch a F one on TV on a regular basis,

0:19:39.160 --> 0:19:43.119
<v Speaker 3>but I'm interested. And I have a red Frari T

0:19:43.240 --> 0:19:46.000
<v Speaker 3>shirt which I've been known to wear, and if you,

0:19:46.320 --> 0:19:48.320
<v Speaker 3>if I ever got really rich, would I buy it

0:19:48.359 --> 0:19:48.560
<v Speaker 3>for Aur?

0:19:48.720 --> 0:19:48.880
<v Speaker 6>Yes?

0:19:48.920 --> 0:19:49.240
<v Speaker 9>I would.

0:19:49.880 --> 0:19:53.440
<v Speaker 4>Okay, So where am I? Where am I in your breakdown?

0:19:53.720 --> 0:19:57.200
<v Speaker 6>Yeah? I think you're probably a combination of the I

0:19:57.200 --> 0:20:00.760
<v Speaker 6>think it's casual loyalist. It's not going to not going

0:20:00.840 --> 0:20:03.840
<v Speaker 6>to overtly go out of their way to sort of

0:20:03.880 --> 0:20:05.879
<v Speaker 6>spend money on the racing, but they are loyal to

0:20:05.920 --> 0:20:08.600
<v Speaker 6>the Ferrari brand and they have nostalgia with it or

0:20:08.640 --> 0:20:11.240
<v Speaker 6>whatever it might be. And then the luxury enthusiasts as well,

0:20:11.400 --> 0:20:14.840
<v Speaker 6>so and that type of fan. You're right, We're probably

0:20:14.840 --> 0:20:16.680
<v Speaker 6>not going to engage you by doing a ton more

0:20:16.720 --> 0:20:19.320
<v Speaker 6>on race weekend, but we can engage you by bringing

0:20:20.119 --> 0:20:25.600
<v Speaker 6>this hugely rich amount of archive material, footage, feelings and

0:20:26.200 --> 0:20:31.160
<v Speaker 6>past drivers of yesteryear, by bringing them to life.

0:20:36.680 --> 0:20:41.399
<v Speaker 9>In zero an app that you saw another brand doing

0:20:41.800 --> 0:20:43.600
<v Speaker 9>that served as a kind of model. I don't mean

0:20:43.640 --> 0:20:47.159
<v Speaker 9>within F one, I'm talking about it from any other film.

0:20:47.400 --> 0:20:48.040
<v Speaker 4>On top of.

0:20:47.960 --> 0:20:53.760
<v Speaker 7>Being a very sport passionate. I'm, let's say, a marketing passionate,

0:20:53.840 --> 0:20:57.520
<v Speaker 7>a digital passionate guy. So I have a lot of apps,

0:20:57.600 --> 0:20:59.680
<v Speaker 7>and he also for my job. I tried to look

0:20:59.680 --> 0:21:01.600
<v Speaker 7>at the and different apps.

0:21:01.760 --> 0:21:04.800
<v Speaker 3>As we were talking, I was thinking about Strava. I'm

0:21:04.840 --> 0:21:07.680
<v Speaker 3>a huge Stravahead. It's my favorite app. If you don't

0:21:07.720 --> 0:21:10.760
<v Speaker 3>already know, Strava is used by millions of active people

0:21:10.800 --> 0:21:13.320
<v Speaker 3>around the world. I'm a runner, and the app shows

0:21:13.359 --> 0:21:16.160
<v Speaker 3>me a map of where I went, how fast I ran,

0:21:16.600 --> 0:21:18.679
<v Speaker 3>what my heart ray was, what the weather was, on

0:21:18.760 --> 0:21:19.120
<v Speaker 3>and on.

0:21:19.400 --> 0:21:21.240
<v Speaker 4>Are you're a cyclostore runner, I'm a runner.

0:21:21.240 --> 0:21:21.800
<v Speaker 6>I'm a runner.

0:21:22.040 --> 0:21:26.120
<v Speaker 7>I run marathons and ultra marathons. I did let's see

0:21:26.160 --> 0:21:27.280
<v Speaker 7>one hundred kilometers.

0:21:27.400 --> 0:21:31.200
<v Speaker 3>As it turns out, Stefano is a Stravahead too. Right

0:21:31.240 --> 0:21:33.679
<v Speaker 3>after I spoke to him, I followed him on Strava.

0:21:33.760 --> 0:21:35.800
<v Speaker 3>He and I run roughly the same distance every day

0:21:35.840 --> 0:21:38.040
<v Speaker 3>at the same pace, and if I'm ever in Milan,

0:21:38.280 --> 0:21:40.320
<v Speaker 3>I'm almost certainly going to look him up to see

0:21:40.320 --> 0:21:41.960
<v Speaker 3>if you'll take me out on one of his favorite

0:21:42.000 --> 0:21:45.000
<v Speaker 3>routes through the city. This is what I love about Strava.

0:21:45.320 --> 0:21:47.959
<v Speaker 3>You can find people to run with and interact with

0:21:48.400 --> 0:21:51.600
<v Speaker 3>Strava is a community of like minded people and for

0:21:51.640 --> 0:21:54.880
<v Speaker 3>those like me, the Strava app becomes a regular part

0:21:54.960 --> 0:21:58.119
<v Speaker 3>of my daily routine, and that's what Stefano wanted for

0:21:58.160 --> 0:22:01.480
<v Speaker 3>the Ferrari app. Are you interested allowing creating sort of

0:22:01.560 --> 0:22:05.760
<v Speaker 3>robust forums for our evans to communicate with each other?

0:22:07.080 --> 0:22:10.520
<v Speaker 7>I think you have to work in three directions. So

0:22:10.640 --> 0:22:14.840
<v Speaker 7>direction number one is a Ferrari to fans, so providing

0:22:14.880 --> 0:22:18.280
<v Speaker 7>them something which is compelling, which has value, and this

0:22:18.520 --> 0:22:20.320
<v Speaker 7>I think we're already doing and we're working on it.

0:22:20.760 --> 0:22:25.679
<v Speaker 7>Second way is fans to Ferrari, so help like allowing

0:22:25.720 --> 0:22:28.679
<v Speaker 7>fans to better interact with us, which was something we

0:22:28.720 --> 0:22:31.640
<v Speaker 7>were not doing with the previous app. For example, we've

0:22:31.800 --> 0:22:35.040
<v Speaker 7>just introduced two features which are polls, so basic ones,

0:22:35.080 --> 0:22:38.639
<v Speaker 7>but polls and the possibility like the submit your message feature.

0:22:38.880 --> 0:22:42.040
<v Speaker 7>So really to work on the way fans to Ferrari.

0:22:42.200 --> 0:22:45.240
<v Speaker 7>And then the third important way to build a community

0:22:45.280 --> 0:22:48.640
<v Speaker 7>and nature community is like fans to fans. So if

0:22:48.680 --> 0:22:51.560
<v Speaker 7>you were able to work on those trae dimensions of

0:22:51.640 --> 0:22:54.359
<v Speaker 7>Ferrari to fans, fans to Ferrari and fans to fans,

0:22:55.000 --> 0:22:58.399
<v Speaker 7>that's how you could really create a strong community and

0:22:58.480 --> 0:23:01.119
<v Speaker 7>start really monetizing and create in value. I think we

0:23:01.119 --> 0:23:04.320
<v Speaker 7>are very strong in the first dimension right now, we're

0:23:04.359 --> 0:23:07.400
<v Speaker 7>building the second one, so fans to Ferrari and then

0:23:07.440 --> 0:23:10.600
<v Speaker 7>definitely the third one has to be there in order

0:23:10.680 --> 0:23:13.040
<v Speaker 7>to have a complete community engagement.

0:23:13.600 --> 0:23:15.080
<v Speaker 4>So let's talk about results.

0:23:15.520 --> 0:23:18.720
<v Speaker 3>Scuddery of Ferrari HP launched the new app at the

0:23:18.760 --> 0:23:23.000
<v Speaker 3>Miami Grand Prix in twenty twenty five, incorporating AI elements

0:23:23.080 --> 0:23:28.840
<v Speaker 3>and tailoring it to those archetypes. Was talking about, are

0:23:28.880 --> 0:23:32.120
<v Speaker 3>more people using the app? Are users spending more time

0:23:32.160 --> 0:23:34.159
<v Speaker 3>on it than they did on the older version of

0:23:34.200 --> 0:23:34.560
<v Speaker 3>the app?

0:23:35.160 --> 0:23:38.920
<v Speaker 7>Yes, we doubled these months the daily active users we

0:23:38.920 --> 0:23:41.600
<v Speaker 7>were having last season, so compared to the average of

0:23:41.680 --> 0:23:44.600
<v Speaker 7>twenty twenty four season, we have more than double of

0:23:44.840 --> 0:23:50.040
<v Speaker 7>daily active users. Also, we're doubling normal months down downloads,

0:23:50.080 --> 0:23:53.440
<v Speaker 7>so we did in these months more than two times

0:23:53.480 --> 0:23:56.040
<v Speaker 7>the download we are doing in a normal months. We

0:23:56.320 --> 0:24:00.639
<v Speaker 7>are increasing by thirty five percent the average times. So

0:24:00.720 --> 0:24:01.600
<v Speaker 7>keep your eyes out good.

0:24:02.880 --> 0:24:10.200
<v Speaker 3>If you build the right app, they will come for generations.

0:24:10.359 --> 0:24:14.080
<v Speaker 3>Fans of all varieties have met in public places, the

0:24:14.119 --> 0:24:17.199
<v Speaker 3>stands of stadiums, in bars to watch races, and matches

0:24:17.200 --> 0:24:20.560
<v Speaker 3>on television. But there's a chance now for fandom to

0:24:20.600 --> 0:24:24.240
<v Speaker 3>exist on a higher and broader level, for a community

0:24:24.400 --> 0:24:27.479
<v Speaker 3>to be created over the Internet, even when the fans

0:24:27.520 --> 0:24:34.480
<v Speaker 3>are vastly different people who live vast distances apart. I

0:24:34.480 --> 0:24:37.760
<v Speaker 3>can imagine Gino in his Ferrari Red and Black, using

0:24:37.800 --> 0:24:40.399
<v Speaker 3>the scoodery of Ferrari app relating to me as I

0:24:40.440 --> 0:24:43.240
<v Speaker 3>relive my memories of Niki Lauder from the nineteen seventies.

0:24:44.000 --> 0:24:45.920
<v Speaker 3>Maybe I could use the app to learn something from

0:24:45.920 --> 0:24:49.520
<v Speaker 3>the woman in China, the Tafosie newcomer, or some seventeen

0:24:49.560 --> 0:24:52.320
<v Speaker 3>year old who got sucked in first by drive to survive.

0:24:53.240 --> 0:24:57.320
<v Speaker 3>I can imagine myself as part of that vision, taking

0:24:57.400 --> 0:25:14.000
<v Speaker 3>my lifelong obsession to the next level. Smart Talks with

0:25:14.040 --> 0:25:18.440
<v Speaker 3>IBM is produced by Matt Ramano, Amy Gains, McQuaid, Trina Menino,

0:25:18.960 --> 0:25:23.320
<v Speaker 3>and Jake Harper were edited by Lacy Roberts. Engineering by

0:25:23.440 --> 0:25:27.680
<v Speaker 3>Nina Bird Lawrence, mastering by Sarah Bruguier, music by Gramoscope,

0:25:27.920 --> 0:25:32.639
<v Speaker 3>Strategy by Tatiana Lieberman and Cassidy Meyer. Special thanks to

0:25:32.680 --> 0:25:36.760
<v Speaker 3>Scuderia Ferrari HP and the bar and restaurant Feala in

0:25:36.840 --> 0:25:39.800
<v Speaker 3>New York City Smart Talks with IBM is a production

0:25:39.880 --> 0:25:44.119
<v Speaker 3>of Pushkin Industries and Ruby Studio at iHeartMedia. To find

0:25:44.160 --> 0:25:48.520
<v Speaker 3>more Pushkin podcasts, listen on the iHeartRadio app, Apple Podcasts,

0:25:48.640 --> 0:25:53.240
<v Speaker 3>or wherever you listen to podcasts. I'm Malcolm Glappo. This

0:25:53.400 --> 0:25:56.919
<v Speaker 3>is a paid advertisement from IBM. The conversations on this

0:25:57.000 --> 0:26:12.720
<v Speaker 3>podcast don't necessarily represent IBM's position, strategies or opinions. I

0:26:12.760 --> 0:26:16.040
<v Speaker 3>asked Fred Baker to come up with a hypothetical something

0:26:16.119 --> 0:26:20.160
<v Speaker 3>that could fulfill my childhood dreams, something that this type

0:26:20.160 --> 0:26:23.560
<v Speaker 3>of technology could theoretically do that might appeal to a

0:26:23.600 --> 0:26:26.680
<v Speaker 3>fan like me, someone who's interested in the sport went

0:26:26.760 --> 0:26:31.480
<v Speaker 3>back fifty years. He said, what about using AI to

0:26:31.520 --> 0:26:33.000
<v Speaker 3>bring historical cars to.

0:26:33.000 --> 0:26:36.680
<v Speaker 6>Life, bringing to live cars of the past and allows

0:26:36.720 --> 0:26:42.760
<v Speaker 6>fans to simulate a nineteen fifty Ferrari race versus nineteen

0:26:42.840 --> 0:26:45.000
<v Speaker 6>seventy one to see who which car would be faster.

0:26:45.280 --> 0:26:46.600
<v Speaker 6>So it's those sorts of trade offs.

0:26:47.280 --> 0:26:49.000
<v Speaker 4>Wait, you could do it. Wait you could do that?

0:26:49.040 --> 0:26:51.720
<v Speaker 3>Tell me about last thing you said you can run

0:26:51.760 --> 0:26:54.520
<v Speaker 3>simulations race simulations out of the app.

0:26:54.960 --> 0:26:57.080
<v Speaker 6>You can't out of the app at this point, so

0:26:58.359 --> 0:27:01.760
<v Speaker 6>I know, potentially, potentially, Yeah, it can you know, simulates

0:27:02.400 --> 0:27:04.360
<v Speaker 6>based on a whole range of factors that we can

0:27:04.359 --> 0:27:05.320
<v Speaker 6>feed and train it on.

0:27:06.200 --> 0:27:09.520
<v Speaker 3>Wait, so I could hypothetically you could allow me to

0:27:09.600 --> 0:27:15.560
<v Speaker 3>compare Niki Lauder, for example, to a contemporary driver, and

0:27:15.600 --> 0:27:17.520
<v Speaker 3>I could say if I put Nicki Lauder in a

0:27:17.520 --> 0:27:21.080
<v Speaker 3>contemporary car, what you're saying is that there is a

0:27:21.119 --> 0:27:26.840
<v Speaker 3>scenario where I could recreate that era in modern cars

0:27:27.240 --> 0:27:30.480
<v Speaker 3>and get a sense of how my childhood heroes were performing,

0:27:31.240 --> 0:27:32.520
<v Speaker 3>would have performed a break day?

0:27:32.920 --> 0:27:35.119
<v Speaker 6>Yeah? Yeah, So you can analyze and understand how you

0:27:35.160 --> 0:27:37.879
<v Speaker 6>would rank all drivers of all time based on the

0:27:37.920 --> 0:27:39.800
<v Speaker 6>different traits of a driver, right, So you can say

0:27:39.800 --> 0:27:42.240
<v Speaker 6>who's the best late breaking, Who's who was typically the

0:27:42.280 --> 0:27:44.720
<v Speaker 6>best on a tight track with limited overtaking opportunities, who

0:27:44.760 --> 0:27:46.560
<v Speaker 6>was the best overtaker, who was the best of all

0:27:46.560 --> 0:27:49.320
<v Speaker 6>these traits. You then apply those traits and rankings to

0:27:49.680 --> 0:27:52.879
<v Speaker 6>different tracks and different cars where you know different Some

0:27:52.960 --> 0:27:55.200
<v Speaker 6>different cars are better for a late breaker, some different

0:27:55.240 --> 0:27:57.159
<v Speaker 6>cars are better for a you know, on straits and

0:27:57.160 --> 0:28:00.240
<v Speaker 6>so on. So you can simulate, You could hypothetically our

0:28:00.280 --> 0:28:03.359
<v Speaker 6>fans to simulate any scenario. You could say, who's going

0:28:03.400 --> 0:28:07.840
<v Speaker 6>to win in Monaco on a nineteen eighty model car.

0:28:08.560 --> 0:28:10.760
<v Speaker 6>You can put a current driver in a nineteen eighty

0:28:10.800 --> 0:28:12.720
<v Speaker 6>car equally, so you can do all sorts of fun

0:28:12.840 --> 0:28:13.600
<v Speaker 6>and simulations.

0:28:15.080 --> 0:28:16.240
<v Speaker 4>And that's just the beginning.