When computers and machines learn from collected data and derive an action from it, one speaks of Artificial Intelligence (AI). The term machine learning is also used in the machine sector.
In private life, one example is that of users of music streaming services. Here an algorithm constantly learns from the behaviour of the user:
- What music does he listen to?
- How often does he hear it?
- Which of the resulting recommendations does he accept?
As a result of this AI, the user hears his favourite music.
An example from the industry shows the economic potential of this technology: For an energy chain, the manufacturer predicts the expected service life under specified conditions of use. Sensors in the energy chain send real-time usage data to a computer around the clock, which may also process environmental parameters such as temperature and humidity. This data automatically synchronises a software and then issues an always current expected operating time of the energy chain. If a critical value is reached for the system, it automatically triggers an alarm or an action, e.g. by shutting down systems. The software decides what to do from the data it gets.
Despite all technology, it is still the case that a system can only be as intelligent as the human being who initially programmed its algorithms. And with all further development through permanent learning, scenarios of machines dominating the world emerge only in the imagination of science fiction writers.