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The company wants to increase its use of managed artificial intelligence (AI) and machine learning (ML) services as well as serving content closer to racing fans.

The Helicopter Racing League runs its services in a public cloud provider, and initial video recording and editing is performed in the field and then uploaded to the cloud for additional processing on virtual machines. The company has truck-mounted mobile data centers deployed to race sites. An object storage system is used to store content. The deep learning platform TensorFlow is used for predictions, and it runs on VMs in the cloud.

The company is focused on expanding the use of predictive analytics and reducing latency to those watching the race. They are particularly interested in predictions about race results, mechanical failures, and crowd sentiment. They would also like to increase the telemetry data collected during races. Operational complexity should be minimized while still ensuring compliance with relevant regulations.

Specific technical requirements include increasing prediction accuracy, reducing latency for viewers, increasing post-editing video processing performance, and providing additional analytics and data mart services.