Probabilistic programming is a term from the fields of artificial intelligence, industry and Industry 4.0, as well as big data and smart data. It describes a modern method with which computers and machines can calculate probable outcomes instead of relying on fixed rules. This means they learn from data how likely different events are to occur, and can therefore make better and more flexible decisions.<\/p>\n
Unlike classic programmes that always do the same thing step by step, probabilistic programming works with probabilities. This allows a system, for example, to calculate multiple possibilities and incorporate uncertainties.<\/p>\n
A vivid example: A company uses sensors in its manufacturing process to monitor machinery. Instead of stopping each machine only when an actual fault occurs, a probabilistic program calculates how likely a fault is in the near future. To do this, it considers various data such as temperature, vibration, or production volume. This allows maintenance to be scheduled precisely when it's most needed \u2013 minimising breakdowns and saving costs.<\/p>\n
Probabilistic programming therefore helps companies to deal with uncertainties and make intelligent, data-driven decisions.<\/p>","protected":false},"excerpt":{"rendered":"