Uncertainty Quantification plays a particularly central role in the fields of Artificial Intelligence, Big Data and Smart Data, as well as Industry and Industry 4.0. This involves systematically identifying, measuring, and accounting for uncertainties in data, models, or forecasts.<\/p>\n
Imagine a company using artificial intelligence to forecast demand for its products. Although the software works with a vast amount of data, there are always fluctuations \u2013 for example, due to sudden changes in the weather or new trends. Uncertainty quantification helps to make these uncertainties visible. Instead of simply stating a fixed figure, such as \u201e1,000 units will be sold next month\u201c, the model also indicates how certain this prediction is \u2013 for example: \u201eWith an 80% probability, we will sell between 900 and 1,100 units.\u201c<\/p>\n
Uncertainty quantification thus ensures greater transparency and better decision-making. Companies can better assess risks, develop robust plans, and react more flexibly. Thus, uncertainty quantification becomes an important tool for managers and decision-makers in the digital world.<\/p>","protected":false},"excerpt":{"rendered":"