Artificial intelligence is a promising technology which is already surrounding us with different useful applications like voice control, or computer vision. And in the automotive industry, it’s playing its part in the development of automated vehicle technology and advanced vehicle interior solutions. But there are still some drawbacks to this maturing technology.

This paper accompanies a FISITA online event about AI & Hybridisation Techniques, addressing new techniques such as Bayesian approaches, hybridisation techniques, the fusion of artificial intelligence and deterministic models, or new amorphic technologies. These are the technologies of the future and will set up new trade-offs that will benefit product designers and end users.

Learn more about techniques, applications and research challenges of uncertainty quantification which play a central role in reducing the impact of uncertainty in both optimisation and decision-making processes.

Examine how the problem of reconstructing a high-resolution colour image from burst of low-resolution raw pictures can addressed with a hybrid algorithm that retains the interpretability of the Lucas-Kanade approach to image alignment and iterative solutions to inverse problems but can be implemented in a feed-forward neural network, with parameters learned end to end.

And find out how Neuromorphic Computing can address the need for low power devices that are capable of advanced intelligence while reducing the number of specialized silicon chips and integration complexity.