Machine Learning/AI Use Case
Autonomous vehicles (AV) promise to change the face of driving, but the success of the industry rides on the ability to train AVs to operate flawlessly in all road conditions, weather types, and according to varied driving laws. Deep learning systems place a significant burden on storage and computational infrastructure because the rate of data acquisition and data processing mask any prior workloads. A single AV will generate over 40TB of data in 8 hours1 , a burden that multiplies with a fleet of training vehicles. Daily data collection is measured in multi-petabytes and must be ingested to the training data lake for pre-processing to support the training sets.