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According to the developers, the “AutoML tool” democratizes the application of AI and ML, because it makes the methods accessible to a broad mass. The initial situation at many companies: Currently available ML tools and their capabilities overwhelm classic automation and mechanical engineering experts, because they usually do not have the knowledge to develop appropriate models.

That is why data scientists take over the data analysis and model building – as already described above. Their expert knowledge is necessary to apply AI or ML methods to the data and develop models that can, for example, detect anomalies and predict errors. Of course, the data scientist works closely with the machine builder or operator during model development to interpret the relationships found in the data in engineering terms, as well as to identify features relevant to model building.

In the future, Weidmüller’s tool will also run on the Swedish company Crosser’s low-code platform for edge analytics.