Frank Kraemer

Frank is responsible for helping to drive global automotive industry enterprise data strategy. He is focused on establishing areas of application for the Red Hat OpenShift, the full-stack and software-defined computing platform used in areas of deep learning, data science and artificial intelligence. Specifically, he has been working on technologies related to autonomous vehicles, including HPC, AI/deep learning, data factory, validation, simulation, replay, synthetic data generation as well as GenAI/LLM, connected everything, smart mobility, digital twins and cloud computing.

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Presentation

Accelerate AV development with data-driven automotive AI

Developing AVs is a time-intensive and complex process that requires best-in-class data and AI training infrastructure. Companies developing software-defined vehicles need to accelerate time-to-market and minimize costs without sacrificing safety. Combining vehicle sensors, map data, telematics and navigation guidance using machine learning and data fusion techniques, data-driven development is not without its challenges. One of the biggest challenges is data collection and integrity, as data needs to be collected accurately and consistently to drive accurate decisions.