Customer-Centric Innovation in Automotive

This session showcases how Porsche Engineering fosters innovation in the context of automotive engineering. Learn how NVIDIA technology helps push the frontiers of the automotive V-Model in terms of innovation depth and time-to-market. Learn about methods and components used throughout the vehicle development and validation process to ultimately enhance the customer experience in the car.

This session covers:

  • The development of a cloud-connected real-time ecosystem to enhance automotive engineering, focusing on three use cases: signal foundation model, AI-corrected GPS, and agentic AI-driven fleet diagnosis.
  • The signal foundation model transformed raw time series vehicle signals into searchable scenarios, enabling engineers to quickly find and understand specific driving events.
  • AI-corrected GPS improved position accuracy in high-dynamic driving situations, achieving a 95% error reduction using standard vehicle sensors.
  • Agentic AI-driven fleet diagnosis automated the detection and analysis of issues across development fleets, reducing the time to react and improving overall quality and efficiency.
  • The ecosystem shortened iteration cycles from weeks to minutes, allowing for continuous improvement and validation of AI models in real-world conditions.
  • This session emphasizes the importance of a unified, scalable, and traceable AI lifecycle from data collection to deployment, which accelerated the development and validation of new vehicle technologies.

Customer-Centric Innovation in Automotive