Formula E and Google Cloud were officially rewarded with a Guinness World Record for the most participated in-person generative AI hackathon, with 1,130 people involved in the all-day event just a day before its 2024 Hankook London E-Prix last weekend.
The AI hackathon provided participants the opportunity to leverage Google Cloud’s cutting-edge AI tools – Vertex AI and Gemini 1.5 Flash – to tackle critical challenges. Teams collaborated to explore the all-electric racing series’ and Google Cloud’s innovations, while gaining insights from their experts during talks and interactive breakout sessions.
The 1,130 participants also got up close to the final pre-race preparations of the 11 world-class racing teams including the likes of Jaguar TCS Racing, NEOM McLaren and TAG Heuer Porsche Formula E race teams during pitlane tours and watching the series’ final practice session before the race.
Ancoris emerged as the winner of the hackathon by impressively completing three challenges which earned them a special mention from Jeff Dodds, CEO, Formula E, with their standout achievement being an innovative podcast agent.
The event’s panel of judges included: Eric Ernst, VP Technology at Formula E, Jeff Dodds, CEO, Formula E, Enrique Rodriguez, CTO at Liberty Global, John Abel, Technical Director, Office of the CTO at Google Cloud and Rich Radley, Director of Customer Engineering, Google Cloud.
Eric Ernst, Head of Technology at Formula E comments: “This hackathon marks a milestone in Formula E’s AI journey and we are thrilled to officially be Guinness World Record holders. In collaboration with Google Cloud, the hackathon exceeded all expectations, delivering a unique, immersive experience and vibrant atmosphere like no other. At Formula E, we champion innovation, inclusivity and openness. The event was all about giving a diverse range of participants an opportunity to engage with AI technology and live race data in a high-stakes environment, aiming to establish Formula E as the world’s most innovative and fastest-accelerating sport. What a way to set the scene for tomorrow’s race.”
John Abel, Technical Director, Office of the CTO at Google Cloud adds: “It is an exciting time for AI innovation and it has been amazing to see Google Cloud and Formula E come together to pull off the largest AI-focused event of its kind. With 60% of participants not having direct skills in AI, our record breaking hackathon was about bridging this gap and demonstrating the practical, real-world capabilities of generative AI, encouraging participants to think creatively about future possibilities in motorsports and beyond.”
He also said: “The winning team Ancoris from the Formula E hackathon built and demoed an amazing Vertex Agent which consumed a 2 hour race and made a 2min summary podcast. Not only did it summarise the race (in any language required) but by enriching the LLM with driver data and future events set the scene for the next race. It was amazing to see the innovation in less than 8 hours of development.”
The challenges asked the participants to focus on:
- Fan Engagement: Develop a personalised “matchmaker” app or bot that analyses fan preferences to recommend teams and drivers aligned with their values.
- Future Car: Rebuild and enhance the Driverbot using Google’s latest AI features, including multimodal approaches, to provide drivers with quick visual insights into their performance.
- Safety: Develop an AI system to identify on-track incidents quickly and alert race control, especially in areas with potential CCTV blind spots.
- Sustainability: Design an AI-powered “Sustainability Scorecard” that allows users to compare the Formula E GEN3 car’s sustainability with any other vehicle.
- Operations: Create a voice-powered debrief bot that transcribes spoken feedback into actionable insights, revolutionising post-event analysis.
- Diversity and Inclusion: Develop an AI prototype to provide real-time captioning, translation, or audio descriptions of race visuals for fans with disabilities.
- Vision Highlight Reel & Content Creation: Develop an AI system to detect overtakes, sync them with telemetry data, identify cars, and generate timecodes for highlight reels, or design an AI system to automate post-race content creation, such as VOD summaries and podcasts, in multiple languages.
