Artificial intelligence is an important tool for Daimler
For nearly two years, Steven Peters has been building up an AI research team at Daimler AG. Daimler, a German automotive multinational, owns the Mercedes-Benz brand. It also owns or has shares in other brands such as Smart Automobile, Mercedes-AMG, and Detroit Diesel.
Dr.-Ing. Peters’ AI team covers the whole spectrum of automotive development.
What is artificial intelligence?
Artificial intelligence (AI) refers to software technologies that make devices act, think, and behave like human beings. Typical devices include, for example, robots and computers.
Many software engineers believe we can only call it AI if it performs at least as well as a human being. Performance, in this context, means computational accuracy, capacity, and speed.
Artificial intelligence also includes machine learning, which refers to ‘smart’ machines’ ability to learn as they go along, without human help. Another similar area of AI is statistical learning, which refers to a set of tools for understanding and modeling complex datasets.
“The main element of today’s AI is machine learning, which is also referred to as statistical learning. This means that AI is mathematics.”
“Cutting-edge IT and the availability of large amounts of data (big data) enable AI to find and use very complex patterns in a highly automated manner. Such pattern searches are also used to “understand” everyday scenes in photographs, for example.”
What does the Daimler team do?
For Daimler, AI has become an important tool. The AI team members are algorithm experts who are attempting to identify crucial driving patterns. They also use components, situations, and test data.
When they have found these patterns, they work closely with specialist development departments within Daimler. Their goal is to improve current functions or create entirely new ones.
Dr.-ing. Peters adds:
“We then test the first prototypes in cooperation with in-house users and customers. This aspect, in particular, makes AI a very interdisciplinary field in which algorithm experts work together with function developers, psychologists, and designers.”
How the Daimler team develops a system
If Daimler customers, for example, use a function repeatedly in a certain way, the team may study these patterns to develop a system.
The next time somebody requires that function, the system will have already predicted its use and subsequently will have adjusted itself automatically.
A theoretical example of this might be to include a system for heating a car seat.
Dr.-ing. Peters provides another example:
“Another interesting research task is to assess the emotions of the vehicle occupants. It would enable us to adjust the steadily growing range of entertainment and relaxation programs to the car occupants’ preferences.”
Daimler already using AI
Daimler is using artificial intelligence to improve knowledge transfer within the company. When new engineers join the company, the system helps them get their bearings and find their way around. It can do this because it already ‘knows’ every single vehicle design at Daimler.
Dr.-ing. Peter adds:
“In this way, we can train algorithms to permanently secure the wealth of experience that has been built up at the company over the decades.”
“Finding a solution to a problem might simply require the system to suggest that a new engineer contacts a certain experienced colleague, for example.”