Scenario modelling for AI is primarily at home in the fields of Artificial Intelligence, Automation, and Big Data and Smart Data. It describes a method for designing and testing different \u201ewhat-if\u201c situations for an AI. This allows one to test how well an AI reacts in various, even unexpected, situations. <\/p>\n
Scenario modelling is used to train artificial intelligence to act flexibly. For example, an AI in a factory can be shown several scenarios: What happens if a machine suddenly breaks down? Or how does it react to a sudden change in the supply of materials? All of these situations can be simulated on a computer, and the AI can learn from them without causing disruptions in reality. <\/p>\n
The great advantage for companies: risks can be identified and processes made safer. Scenario modelling for AI is therefore an important step in making intelligent systems reliable and enabling them to solve even unfamiliar problems independently.<\/p>","protected":false},"excerpt":{"rendered":"