Volkswagen AG opened the highly specialised research centre known as Data:Lab Munich around five years ago with a focus on data analytics. The current challenge is developing artificial intelligence.
Professor Patrick van der Smagt can break down complex topics in a way that most people can understand them. That is a useful skill to have when explaining what artificial intelligence and machine learning are – principles which underpin the work of software for stock market forecasting, analysing the social media activity of an account, or recognition of natural language.
Algorithms are only powerful if they are properly fed. That is the daily challenge for the artificial intelligence (AI) research team led by van der Smagt at Volkswagen’s Data:Lab Munich. “In contrast to social networks, if you’re trying to do something like quality control for automotive components you don’t have a stock of what’s called annotated data. So we have to teach the systems how to analyse comments, determine contexts, and draw the best possible conclusions on their own”. The algorithms process information in a series of steps and combine it with what they have already learned plus historical data sets. In so doing, the systems improve continuously, becoming increasingly good at identifying patterns and regularities.
From data analysis to artificial intelligence
Data:Lab Munich was founded in late 2013 – at a time when artificial intelligence had a much lower public profile than it does today. The initial focus was on data analytics; since then the team has grown to approximately 80 specialists made up of programmers, IT specialists, physicists and mathematicians, who are pursuing research and development in the field of machine learning. This field is of interest to Volkswagen because artificial intelligence is becoming ever-more relevant to the industry, to the point where it now represents an increasingly important competitive factor.
“We assess every single AI-based application to see how helpful it can be”, says Martin Hofmann, CIO of the Volkswagen Group. “Our aim is to use AI to provide even better support for our teams at factories and offices, because that will generate lasting benefits for the entire company”. “We’re the anchor point for the field of artificial intelligence at the Volkswagen Group”, explains Firas Lethaus, head of Deep & Machine Learning. “All the brands and departments in our company can make use of our expertise. We also turn around and approach them with our ideas on where and how machine learning can be applied to their operations. The idea behind all of this is to give them the necessary tools to make faster and better decisions”.
Some applications are already being used in areas like sales planning. Algorithms can predict which car models will sell especially well in certain seasons in particular regions, providing a substantial basis of data with which to make strategic decisions. Another example is the aftersales business. Which replacement parts are in especially high demand where and when? For example, in hilly regions cars have greater wear on their brakes. The system concludes from this that the relevant warehouses need to carry more brake discs to meet demand.
Journey into the future
Data:Lab teams have now developed more than 100 AI applications, many of which are going through trial runs in very different parts of the company. One of these relates to analysis of the camera images recorded in fields such as quality assurance or autonomous driving. “It doesn’t really matter to a neural network what it sees. It derives contexts on the basis of pixel data. The challenge consists of structuring the data in such a way that they are sufficiently robust to prompt the right actions in specific situations. If a car camera sees that a cyclist is crossing the street, the system can’t tell from the pixels where the cyclist will be in the next five seconds. That’s much too complex. But the dynamics of the movement can be abstracted from the image”, explains van der Smagt.
But the Data:Lab’s journey into the future has just begun. The next steps will aim to develop self-learning systems that offer people the best possible basis for their decisions. They are on the right track, but there’s still a long way to go.
Source: Volkswagen AG