Training Data-hungry AI Algorithms

20AVEP09_05

09/01/2020

Authors Abstract
Content

Large-scale data refinement is key to bringing more sophisticated automated-driving functions to series production.

Training the algorithms of Artificial Intelligence (AI)-based systems for autonomous or highly automated driving requires enormous volumes of data to be captured and processed. The algorithms must be able to master numerous challenges so that self-driving cars can detect all essential details of their environment, make the right decisions and safely take people to their destination.

Why does training require this much data? AI-based systems enable quick progress, but this progress slows down after a certain point. It must be ensured that systems can also sensibly and reliably handle rare events. Bringing sophisticated AI-based driving functions to the road safely therefore requires a growing amount of ever higher-quality data.

Meta TagsDetails
Pages
5
Citation
Rödler, D., "Training Data-hungry AI Algorithms," Mobility Engineering, September 1, 2020.
Additional Details
Publisher
Published
Sep 1, 2020
Product Code
20AVEP09_05
Content Type
Magazine Article
Language
English