From a technical perspective, this phenomenon is inherent to how these models operate. The generation process relies on probability: at each step, the model predicts the most likely next word based on the preceding context.14 Essentially, with each new word generated, the model assigns a probability to it, favoring words with higher probabilities. If the probability at any point drops too low, the model stops generating text. While this probabilistic approach is fundamental, it can lead to factually incorrect outputs—a consequence generally undesirable, unless the goal is creative or fictional writing.