Asymptotic AI joins IGLAD accident database consortium to help strengthen automotive safety

We are now part of the accident data project IGLAD (Initiative for the Global harmonisation of Accident Data) where international safety experts from industry, government and research have build up an unparalleled database of global in-depth real world accident data within the last decade. Asymptotic is proud to be part of this unique source of safety expertise helping strengthen the development of safe automatic driving functionality based on real world data.

Asymptotic joins SAFER to contribute to a sustainable and safe transport system

We are excited to join SAFER – Vehicle and Traffic Safety Centre at Chalmers to contribute to a sustainable and safe transport system. We will aid SAFER in their vision towards zero accidents by providing our tools for data quality checking, robustness control, edge case analysis and anomaly detection available in the collaborative research projects at SAFER.

Asymptotic aims to discuss and help applying machine learning to research projects in the SAFER consortium and they plan to disseminate and utilize SAFER’s research by bringing knowledge to real-world use.

MALIN LEVIN, SAFER

Innovative Startups project: Fast and scalable pipeline to enable AI with big data

We are proud to have finalized our project funded by the Vinnova Innovative Startups initiative.

Thanks to the support from Vinnova, we have achieved our goals of enriching the technical functionalities of our AI platform and expanding our network. As a result, we have implemented two key components using the state-of-the-art deep learning technology and established several strategic partnerships with complementary expertise. We are looking forward to our journey ahead together with our partners!

The full public report can be found at Vinnova’s webpage.