How Machine Learning is turning the Automotive Industry upside down (EN)

How Machine Learning is turning the Automotive Industry upside down (EN)

10:45 - 11:15 | data.stage | Data & AI in Automotive

The automotive industry has mobilized the global economy for decades. German automobile manufacturers (OEMs) alone employ more than 1 million people worldwide and generate sales of more than USD 500 billion. Since a Google + Stanford team won the Darpa Self-Driving Vehicles Challenge 2006 with the help of machine learning, the industry has been undergoing rapid change. Machine learning opens up brand-new business models, from autonomous driving to smart production to personal assistance in the car. However, the use of machine learning requires a different infrastructure than that found in traditional OEMs. Technology-first companies like Waymo or Tesla threaten to overtake established OEMs with billion-dollar market capitalization.  Autonomous vehicles produce terabytes of data every day. This data can be immensely valuable in developing machine learning-driven functions. However, substantial challenges remain in the way of using this data. Visit this talk to hear about these challenges to help turn the automotive industry from a mechanical engineering to a software industry.

Jan Zawadzki, Project Lead Data Science, Carmeq GmbH