Within the last years, the sector of artificial intelligence (AI) has gained crucial impulses by hardware and software advances. Today, with modern graphic processors very large artificial neuronal networks (ANNs) can be executed in real time. New algorithms for machine learning within such ANNs are capable to discover also structural features from rsp. within these data by their own (deep learning). The victory of the AlphaGO ANN against the GO world champion Lee Sedol in 2016 has proven this in an impressive way.
With the new techniques of data mining and deep learning, data can be processed in principle in their native format by an ANN. The very expensive, prior manual acquisition of data models and inference rules, as required for rule-based expert systems, can be omitted. This is a quantum leap in the economic viability of such AI systems. It is also a necessary prerequisite in order to process very large data sets (big data) in the age of digitization and the internet of things (IOT).
We have decade-long experiences in the sector of artificial intelligence. These experiences enable us to design for our customers the effective applications of AI technologies in a purposeful and cost-efficient way. For technical systems, the application targets will be a reduction of costly downtimes by demand driven, predictive maintenance. In the healthcare area, the focus is on the avoidance of health hazards and/or very fast interventions just in case. For marketing purposes, the profiling of successful customers will be utilized for a tailored promotion of other customers and interested parties.