Kick-Starting AI in Production

Increasing computing power and better data bases with simultaneously decreasing costs for computing and storage capacities represent the basis for the use of Machine Learning (ML) in production. As a result, ML methods are increasingly being used in production. ML methods can be used to train artificial intelligence (AI) systems, which the majority of companies hope will increase their productivity. Challenges on the path to AI systems in in-house production include identifying promising application areas, recognising the associated learning tasks, and uncovering suitable data sets.