In order to train and test artificial intelligence (AI) in an efficient and scalable way, a lot of relevant data is needed. For this purpose, real data is typically collected in real traffic. However, this data must then be manually labeled for validation and training in a very time-consuming and cost-intensive manner. Apart from that, only a part of the situations can be mapped in this way. If data from critical traffic situations or accidents are necessary, the limits of real data are quickly reached.
This is where synthetic data and BIT Technology Solutions comes into focus. With synthetic data, the most diverse and also the most dangerous traffic situations can be modeled in order to train AI-based functions and thus make the mobility of the future safer. The focus in KI Data Tooling are sensor effects which are developed together with the project partners.
At the event “Durch Kooperation an die Spitze – Die Automobilbranche gestaltet den digitalen Wandel” held by Bundesministerium für Wirtschaft und Energie (BMWi) und des Verband der Automobilindustrie (VDA) e.V., one of the central topics was: Data and AI as the key to success for autonomous driving. During the event, there were several places where data from our Datafactory were presented for illustration.