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Andretti Autosport is a well-known racing team that competes in various racing events. The team is always on the lookout for innovative ways to gain a competitive edge over their rivals. They generate a significant amount of data during races, approximately 1 terabyte per car, and were looking for better ways to analyze this data to enhance their race strategy and win more races. They aimed to upgrade their existing data analytics infrastructure by incorporating advanced AI techniques. The team partnered with Zapata to leverage their proprietary Generative AI techniques and the Orquestra platform to achieve this goal.
Andretti Autosport, a renowned racing team, was grappling with the challenge of effectively analyzing the massive amount of data generated during races, approximately 1 terabyte per car. The team was in search of innovative ways to leverage this data to gain a competitive edge and win more races. The primary objective was to upgrade their existing data analytics infrastructure by incorporating proprietary Zapata Generative AI techniques to drive their race strategy. The challenge was not only to manage and analyze the vast amount of data but also to make real-time strategic decisions based on the insights derived from the data.
In response to the challenge, Zapata began upgrading Andretti’s analytics infrastructure in 2022, piloting advanced Industrial Generative AI applications and techniques. The Orquestra® platform was deployed within the Andretti Autosport | Zapata Computing Race Analytics Command Center (RACC), a mobile engineering environment. This hybrid infrastructure combined data lake integration, cloud, and dashboards to drive decision-making, all managed with Orquestra. Engineers from both Zapata and Andretti worked together to test various use cases in machine learning and optimization. The solutions being tested included a machine learning model for strategic tire change decisions, advanced analytics for fuel consumption optimization, and a predictive model for anticipating yellow flags based on various factors.
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