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Ferrari is using IBM’s AI to create F1 superfans
Two years ago, IBM realized there was one glaring omission in its roster of sports partnerships: Formula One. Formula One has become one of the world’s most popular sports, especially in the U.S., where Netflix’s “Drive to Survive” documented the working lives of F1 drivers and turned them into mainstream celebrities. The tech-centric sport has also become ahot ticket for tech companieslike AWS, Oracle, and Anthropic, which partner with teams for sponsorship visibility and to provide data analytics and AI tools that can deliver a competitive edge. So when IBM went looking for its next major sports partnership, it’s no wonder the company picked F1 and one of its most iconic teams,Scuderia Ferrari HP. “They’re the winningest team in history,” Kameryn Stanhouse, IBM’s Vice President of Sports and Entertainment Partnerships, told TechCrunch. At the heart of this partnership, however, is what has led other teams to start working with tech giants: access to more sophisticated tech solutions that can help them make the most of, especially, artificial intelligence. In fact, one of the best parts of sports, Stanhouse said, is how much data is available and can be used to help people get comfortable with AI. “They actually see how it serves them,” she said of how AI is used in sports storytelling. The IBM-Ferrari partnership centers on that idea of storytelling, enhancing fan engagement by overhauling the technology powering the Ferrari fan app. To help with this, Ferrari hired Stefano Pallard in the newly titled role “head of fan development,” who said the challenge the team wanted to tackle was not just reaching fans, but “making each of them feel like we know them.” “That starts with taking the data we get from the track and turning it into content that is easy to follow and engaging,” he told TechCrunch. Teamsprocess millions of data pointsper second during each race, capturing every movement of the driver and the car. Turning this into content that fans can engage with is just one way that advanced enterprise AI can help businesses better interact with their consumers. Among the 11 teams, Ferrari is one of the few (alongside the likes of McLaren and Williams) to have a standalone fan app strategy rather than lean on social media or the official F1 platforms instead, showing how the sport is slowly starting to capitalize on its growing global fandom. Some of the changes to the Ferrari app were simple, like offering it in Italian. Even though Ferrari is an Italian company and many of its fans are Italian, their fan app was not available in Italian until the IBM partnership. Stanhouse said the old Ferrari fan app was a place where people went to find race details and then leave. This new app has games where fans can play with others in the app, new AI-written race summaries, more behind-the-scenes stories about the team and the drivers, a place to make predictions, and an AI companion for fans to ask questions. “There are two drivers, but did you know it takes 24 people working simultaneously in two seconds to change a tire?” Stanhouse said, adding that storytelling helps fans feel closer to the team. Unlike other sports apps IBM has built, Stanhouse said the Ferrari app’s main focus is storytelling because it wants fans to stay engaged with it all year long, rather than for a few weeks a year, as with tournaments like the Masters. Engagement data for the app has been trending upward since IBM came into the scene, Stanhouse said, citing a 62% increase in engagement over race weekends as an example. Pallard said the team then uses AI to analyze engagement signals in the app, such as which content people like to read and the sentiment of the messages fans send. “That helps us understand what resonates most with the Tifosi [the fan nickname for Ferrari] and it directly informs how we shape our storytelling and how we deliver content,” he said. The team hopes to dive deeper into personalization and create more immersive fan experiences. The app developers also took into account Ferrari’s fanbase, which is much more diverse than it was even five years ago. F1 releasedstats last year showingthat 75% of new fans were women, many of whom were Gen Z. A particular draw for women is the F1 Academy, an all-female racing series that aims to develop the next generation of women drivers. But these new fans, much like the old, are after one thing — more. “They are asking for more data, more insight, more features, and we have to be able to deliver that,” Pallard said. “With IBM, the vision for the next five years is to make every fan feel like the experience was built for them, whether they have been with us for 30 years or 30 days. That is how you build loyalty that lasts.”
57 minutes ago
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Elon Musk has given up on solar power (on Earth)
Has Elon Musk given up on Tesla’s Master Plans, on the electrified economy, on solar power as we know it? From theSpaceX IPO filingreleased yesterday, it sure seems like it. A recap for those not enmeshed in the Musk-verse: Tesla has releasedfour Master Plansover the years, and while details have varied, the through line has been electrification of the economy. Musk put it best in his first edition: “the overarching purpose of Tesla motors…is to help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy.” But recently, one of Musk’s companies, xAI, has embraced the mine-and-burn hydrocarbon economy, usingdozens of unregulated natural gas turbinesto power its data centers with plans tobuy $2.8 billion more, effectively cementing the fossil fuel’s role in the company’s AI operations. It’s a curious turn for a businessman who built his empire on clean energy — and who has no qualms directing his companies to buy from one another. SpaceX spent $131 million on 1,279 Cybertrucks, and xAI has spent $697 million in the last two years on Tesla Megapacks, it’s grid-scale battery storage systems that the company will use to manage peak loads. But so far, xAI hasn’t bought a materially significant number of solar panels from Tesla. Solar power isn’t missing in the SpaceX filing, it’s just all concentrated on space, which the company touts as the future of data center power. Terrestrial solar garners a few mentions — not as a power source for xAI data centers but instead to show how much better SpaceX thinks space-based solar will be. It’s no secret that Musk and other Silicon Valley executives have become obsessed with space-based solar power. SpaceX says that space-based solar arrays can generate “more than five-times the energy” of terrestrial ones thanks to 24/7 illumination. As AI data centers have run into opposition here on Earth, CEOs like Musk have started mulling big server racks in space powered by that 24/7 sunshine. Hammer, meet nail. Even if SpaceX is able to bring down the cost of boosting a data center into orbit, the economics arechallenging at best. Power prices for Starlink satellites are multiples higher than what a terrestrial data center typically spends, and protecting chips from the rigors of space won’t be easy or cheap. It’s also not clear whether AI training can be distributed across multiple satellites, leaving a significant chunk of AI work earthbound. It’s not just one problem that SpaceX needs to solve, but many. It’s likely that Musk considers xAI’s current data centers as stopgaps, that once SpaceX is able to loft gigawatts worth of servers into orbit — probably just a few years away, in his mind — he’ll scrap what’s here on the ground, natural gas turbines included and not have to think about NIMBYs anymore. The risk, of course, is that he’s wrong. It’s not just NIMBYs that Musk is worried about, though. He’s clearly concerned that computing demands from AI will quickly outstrip what we can provide here on Earth. Sprinkled throughout the SEC filing are references to “terawatt-scale annual AI compute growth,” which will require power to match. That’s a stunning figure when you consider that all the world’s data centers use around40 gigawatts today. This is Musk’s “first principles” thinking in action. At some point, he assumed the world will need an additional terawatt worth of compute every year, and he worked back from there. “We believe that third-party estimates on data center demand are constrained by the practical supply limitations that exist in a terrestrial context and the power shortage may be far greater than what research estimates suggest,” the company argues. Possible? Sure, I suppose. But consider that humanity today usesabout 35,000 terawatt-hoursof energy annually, or about 4 terawatts on a continuous basis. Energy demand has risen lately, and for AI, it probably is in an phase of exponential growth, which could either continue or level off. We have no way of knowing at this point, but if there’s one thing Musk is good at, it’s spotting a trend at its inflection point and extrapolating wildly. Here’s where Musk’s problems settle back down to Earth. I’m no rocket scientist, but I suspect that shipping solar panels on a flatbed truck uses less energy than sending them into orbit. Plus, space-ready solar panels will need to be manufactured at unprecedented scale. Not insurmountable problems, but also maybe a distraction. We’ve barely scratched solar’s potential here on Earth, for example. The perfect doesn’t have to be the enemy of the good. There’s plenty of room to improve things here on Earth even while we chase after our dreams in the stars. Just three years ago, Musk and his colleagues at Tesla released the “Master Plan Part 3,” which thoughtfully outlined a “plan to eliminate fossil fuels.” A good starting point might be xAI’s data centers.
4 hours ago
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'India Cannot Build Deeptech on Hype Alone'
While India looks to be a leader in AI and semiconductors, investor Aditya Vuchi suggests focusing on practical applications and real customer needs.
12 hours ago
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AI is being used to resurrect the voices of dead pilots
In the latest sign of these AI-heavy times, the National Transportation Safety Board temporarily removed access to its docket system after discovering that voices of pilots who were killed in a UPS plane crash last year had been re-created using AI and were circulating on the internet. The NTSB is prohibited by federal law from including cockpit audio recordings in its docket system, which otherwise contains troves of data on investigations and has historically been open to the public. But the accident docket for this flight included a spectrogram file of the voice recorder. A spectrogram uses a mathematical process to turn sound signals, including low and high frequencies, into an image. Scott Manley, a popular YouTuber whose channel combines physics, astronomy, and video games,noted on Xthat it could be possible to reconstruct audio from the megabytes of data encoded in that image. And that’s what happened. People took the spectrogram, along with the publicly available transcript, to create approximations of the cockpit voice recorder audio from UPS Flight 2976 in Louisville, Kentucky,according to the NTSB. They used AI tools like Codex, according to posts on social media. The agencyrestoredpublic access to the docket system on Friday but kept 42 investigations closed pending review — including the one related to Flight 2976.
16 hours ago
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