Challenges of Deep Learning in the Automotive Industry

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Challenges of Deep Learning in the Automotive Industry

Event: AutoSens Brussels

| Session date: Thursday 19th September

Session date: Thursday 19th September

, 2019

Development of Autonomous Driving ECUs requires sophisticated neural networks built up from massive training data sets in the process known as Deep Learning. The lifecycle of AD product development will be described, and specific challenges identified. • Data acquisition and conversion from in-car R&D formats into suitable DL formats • Leveraging open-source tools for data management • Using a wide range of analytics / AI frameworks against a common data set • Analysing petabytes of sensor data natively, without converting and copying • Optimising storage infrastructure to get the most out of CPU / GPU / IPU accelerators