Hallucination

Hallucinations occur because AI models are probabilistic engines designed to predict the next most likely token in a sequence based on training data, rather than accessing a database of facts. They can be caused by insufficient training data, overfitting, or the model's inherent objective to satisfy a prompt even when it lacks the necessary information. There are two main types: intrinsic hallucinations, which contradict the source material, and extrinsic hallucinations, which add information not present in the source that cannot be verified. Reducing hallucinations is a major area of research, involving techniques like Retrieval-Augmented Generation (RAG) and fine-tuning.