"You can use different algorithms to make machines intelligent. The technology that’s currently being discussed is called „machine learning“ or „deep learning“ – that is, the deep neural networks that can recognize patterns on their own and can then – via various learning methods – introduce those patterns to applications. For example: image recognition, speech recognition, that kind of thing.”
Dr. Wolfgang Hildesheim
"If I have algorithms here that quickly read me large amounts of data and also help engineers to find or to solve any contradictions involved, that certainly helps with production planning."
Dr. Michael May
"One big direction in applications is of course automation in robotics. Constructing robots, for example, which can plan their tasks without having been expressly programmed to do that.”
"We can see that production will continue to become ever more interconnected, and that data will be used increasingly to make production more resource-friendly and also more personalized."
Dr. Marco Huber
"At the moment, it’s always associated with a particularly high amount of manual effort, so of course that makes it expensive, but this trend is headed in the direction of producing these specialized products at a cost that is basically comparable to that of mass production. And that's where AI, machine learning, plays a key role, because it's all about automating and connecting different production systems.”
"And, last but not least, from my point of view, it’s a very important requirement that people should interact safely and reliably with machines! In a manner that makes work enjoyable.