
Ferrari let me loose on their test track, then told me I drive ‘like an Englishman'
A Frenchwoman enjoying the same once-in-a-lifetime Ferrari track experience has just roared past me for the second time at Fiorano Circuit. A thinly veiled insult from my instructor follows. 'Are you very vigilant in your car at home?' asks Marcello Zani in the passenger seat. While others are hitting 140mph on the straight, I barely hit 110 as my eagerly anticipated 296 GTB 'hot lap' turns tepid. 'Be more crazy, like the others,' adds Zani with some disdain. 'You are very English.'
After trundling back into the garage, Zani's point is proven by boffins in a Ferrari data hub where Lewis Hamilton hones his somewhat superior skills. The analysts take me through my many shortcomings and explain that the majority of drivers in our motley crew of international journalists are demonstrably faster. A Spanish enthusiast and a Canadian contemporary with zero interest in cars score better across all analytics. I've let England down, and also my late uncle Blake, who rallied self-adapted Mini Coopers and Lancias with some regional success in the 1970s. This trip would have been his dream, but it is plain the petrol-headed pedigree has deserted his nephew.
A morning spent grappling with the 3.0L V6 Italian stallion has nevertheless been a hoot. It is a privilege to have super-smooth Zani sat alongside me to pass on his nuggets of experience from years racing in the GT3 European Championships.
The car itself, in glistening red of course, is an absolute beauty but any vain hope that I might look the part at are dashed immediately as I bang my helmet on the door while awkwardly attempting to stoop into the tightly fitted driver's cockpit. Zani looks at me and shoots a wry smile as I attempt to work out where the gear stick is. There isn't one. He gets the water sprinklers out for half an hour so we can try out some drifting. I fare better at that, largely drawing on my uncle Blake's lessons in handbrake turns in empty car parks in the 1990s.
But it is during the hot laps later, on the same track that Hamilton uses, that my inadequacies are laid bare. Lightning-quick reactions and balls of steel are required for the bends, with Zani instructing me to go hell for leather against all instincts wide into corners until he finally screams 'brake' over the radio. This car has a max speed of 205.1mph, but with me in charge, such numbers are academic.
Ferrari's bottomless pit of data
We are here at Maranello as Amazon Web Services, the world's biggest cloud computing company, is demonstrating how a digital revolution for Formula One and beyond in sport is gathering pace. To do so at the home of a tradition-steeped manufacturer, which still hand-builds its cars while robots take control, at rivals seems incongruous. But at the world's most famous sports car maker an old-meets-new mindset has taken over.
'I want to stress that this is a change in attitude, a change in culture, change in the way we do our daily work,' Alfonso Fuggetta, Ferrari's chief digital transformation officer, says. In a sport where marginal gains make a difference, Ferrari believe their partnership with AWS puts them in the fast lane as tech and AI shake up sport just as dramatically as daily life.
Despite early season struggles in Hamilton's first year with the prancing horse, there is a quiet confidence that things will eventually fall into place. Ferrari team principal Fred Vasseur spoke this week of his certainty that the Spanish Grand Prix technical directive will be a 'game-changer'.
Charles Leclerc – described by team-mates as 'the geeky one' – is paying particular interest in how Ferrari's bottomless pit of data can help him. Encouragingly, even during underwhelming race outcomes, Ferrari have been recording the fastest times in the pits this year after engineers responded to suggested tweaks from AI analysis of video footage, which was again proven by recording the fastest pit stop at Monaco last week: a two-second service on Leclerc's car.
'What leveraging data efficiently can do is help close those gaps,' explains Ruth Buscombe, an analyst, strategist and F1 commentator who started out at Scuderia Ferrari. 'A great example of that was last year's Italian Grand Prix in Monza, where the track was resurfaced, AWS were able to predict the tyre degradation. Charles Leclerc's Ferrari ends up with a one-stop race, with the Red Bull and the Mercedes doing a two-stop race.'
Teams and broadcasters are now utilising similar tech. Long gone are Murray Walker's often dicey predictions. Instead, the fan-obsessed F1 owners Liberty want viewers to be just as accurate in forecasting the drama. It is Ferrari, however, who are hoping to harness this data to the greatest effect.
'What is exceptional about Formula One is just the sheer amount of data,' explains Adrian DaLuca, a director of cloud acceleration at AWS. 'There are 1.1 million data points coming off 300 sensors in these F1 cars. Now, of course, if you look at just some of the basic telemetry on these cars, things like speed sensors, steering angles, engine speeds, these help tell some of the story. Working with Ferrari, most of those sensors are actually used to help guide their aerodynamic efficiency, help their race strategists, understand how they're using their tyres. So it's not just the data that is used to tell the story in the broadcast. It's the teams themselves.'
Senna was F1's fastest ever driver, data shows
Other sports have also taken notice. NFL and the Bundesliga are now also utilising cloud support. Data collected from American football players is at the forefront of tackling concussion injury worries. Cases have fallen around 40 per cent in recent years, with players now wearing different types of helmets for different positions. The company is now working with the sport to develop the first AI computer vision models that can detect and measure forces that cause concussions in the first place.
'Sports is inherently competitive, so they're all looking to each other, even outside of their own sport, to other leagues to see how data is being used and how technology is being used,' says Julie Souza, global head of sports at AWS. 'So absolutely, they're all learning from each other.'
Experts say 'undoubtedly' that generative AI could quickly help benefit football's contentious VAR technology. Fifa, Uefa and indeed the Premier League will be monitoring AWS's progress in F1 and in the Bundesliga, although none of the three have entered into any serious discussions with the company. For F1, however, there is no limit to what AWS believes it is capable of. The company was initially drafted in to convert the sport's huge store of data into easy-to-understand TV innovations. Battle forecasts, predicting when a chasing driver is within striking distance of the car in front, and a myriad of insights around pit strategy, helping predict to upcoming drama in a race, were introduced. Aggregated data confirms once and for all that Ayrton Senna is officially F1's fastest in 40 years, followed by Michael Schumacher and then Hamilton.
'AI is not a replacement for any engineer or driver'
The company's milestone was the 2022 redesign of the car. F1 employed a computational fluid dynamics design system on AWS's computing platform that reduces simulation time by 80 per cent, from 60 hours to 12 hours. The result was a 'wheel-to-wheel' new car that has helped herald a 30 per cent increase in overtaking in the sport. A host of new innovations are now in the pipeline, with talk even of lie-detector technology so teams can predict when a rival is issuing false information over the radio.
Such innovations are borderline unnerving but Buscombe delivers some reassurance that Ferrari can harness the future while holding on to its traditions. 'AI is not an all-singing, all-dancing replacement for any engineer or driver,' she says. 'What it does is help you do what you were already doing more efficiently and more accurately. If you look at the reality of Formula One, it's always been this way in terms of embracing technology historically. In short, what's the fastest way for me getting from point A to point B?'
It only takes a quick wander round Ferrari's base to conclude that purist philosophies remain safe. During our tour, we are taken to secret museum where Ferrari's spectacular F1 cars past and present are kept under lock and key. Hamilton's Ferrari will eventually come up for sale, we are told. It will fetch millions but you will need a garage already full of 20 Ferrari supercars even to apply.
Despite the cold logic of the AI and machine learning it is now harnessing, Ferrari hangs on to its uncompromising extravagances. As Enzo Ferrari once said: 'Racing is a great mania to which one must sacrifice everything, without reticence, without hesitation.'
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Finextra
an hour ago
- Finextra
What happens when money thinks for itself?
0 This content has been selected, created and edited by the Finextra editorial team based upon its relevance and interest to our community. This is an excerpt from The Future of European Fintech 2025: A Money20/20 Special Edition. The evolution of financial technology is characterised by increasing levels of simplicity, efficiency, and integration. We saw this in 2016, when Europe's second Payment Services Directive (PSD2) encouraged financial institutions to open up their data and infrastructures – paving the way for banking-as-a-service and embedded finance. Fast-forward to 2025, and preparations are already being made for PSD3 – and even deeper levels of functionality and harmonisation. But the technology's development is hardly linear, and every so often innovations land that spark a deep and wide cross-industry revolution. Few would argue that artificial intelligence (AI) lacks this potential, particularly in the world of financial services and product personalisation. 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At the same time, we are taking a considered and measured approach to make sure any AI usage is managed responsibly. 'That's why we've developed a set of ethical AI and data principles to ensure our systems are subject to human oversight, technically robust, free from unfair bias or discrimination. Privacy is a critical focus, particularly in light of [the European Union's General Data Protection Regulation (GDPR)] regulation, and our robust code of conduct ensures we evolve with new regulations while maintaining trust and transparency.' BNY Mellon's Carl Slabicki, executive platform owner, treasury services, added that for treasury clients, AI and big data can help deliver personalised cash management strategies, predictive analytics for liquidity forecasting, and customised risk management solutions. 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