The term "neural control variables" is particularly at home in the fields of artificial intelligence, automation and Industry and Factory 4.0. It describes certain settings or inputs that an artificial neural network can use to specifically control its decisions or adapt them to different situations.
Imagine that a robot in a factory has to perform various tasks, such as screwing in screws or sorting parcels. So that it can work flexibly and safely, it receives so-called neuronal control variables from outside. These variables give the robot precise instructions on how it should behave - for example, how much force it should apply when tightening the screws. This allows the robot to be quickly and easily adapted to different tasks or products without having to reprogramme its entire "brain".
Neural control variables therefore help to make artificial intelligence systems smarter and more flexible. They are like a slider for machines to prepare them for new challenges and make day-to-day work in industry easier.
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