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Industrial Generative AI for Next-Generation Race Analytics: A Case Study on Andretti Autosport
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 汽车
- 建筑与基础设施
适用功能
- 维护
- 质量保证
用例
- 预测性维护
- 车辆到基础设施 (V2I)
服务
- 数据科学服务
- 测试与认证
挑战
比赛会产生大量数据——每辆车大约 1 TB。 Andretti Autosport 一直在寻找更好的方法来分析数据,以获得竞争优势。他们的目标是什么?使用专有的 Zapata 生成人工智能技术升级现有的数据分析基础设施,以推动他们的比赛策略并赢得更多比赛。
关于客户
Andretti Autosport 是一支希望增强决策能力并赢得更多比赛的赛车团队。他们每辆车都会生成大量数据,并正在寻求更好的方法来分析这些数据以获得竞争优势。他们与 Zapata 合作升级其分析基础设施并利用生成式人工智能技术。
解决方案
Zapata 开始升级 Andretti 的分析基础设施并试点先进的工业生成人工智能应用程序和技术。该团队可以在 Orquestra 上测试新设备和算法的性能,并轻松切换到提供最佳性能的后端。 Orquestra 平台部署于 Andretti Autosport | Zapata 计算竞赛分析指挥中心 (RACC),提供结合数据湖集成、云和仪表板的混合基础设施来推动决策。工程师正在测试机器学习和优化中的各种用例。
运营影响
相关案例.
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