Volkswagen : Artificial neural networks can solve problems that other algorithms fail to solve. They process large amounts of complex data. This is enormously important for the development of autonomous driving. ...

For a long time, the Asian board game Go was considered one of the last bastions of human intelligence and intuition. It is far more complex than chess: it is said that there are more possible combinations in one game than there are atoms in the universe. But this fortress was also stormed in 2016: a neural network was trained for months using Deep Learning, a special type of neural network that can learn particularly well on its own. It played more than 30 million games. And then defeated the previous Go World Champion, Lee Sedol from South Korea, who claimed the number one spot for a decade.

'That was the breakthrough,' says Hochrein. 'The basic idea for artificial neural networks had been around for a long time, but now advances in computer science have combined with advances in computing power. As far as autonomous driving is concerned, Hochrein is optimistic: 'Level 5, i.e. fully automated driving, is basically feasible, but it is a highly complex task to get it safely on the road.' You shouldn't just rely on neural networks - classic programs are also suitable for certain tasks. 'Neural networks are not a remedy for everything,' says Hochrein, 'but they are enormously important for the development of autonomous and assisted driving.'