What Are AI Hallucinations? And How To Improve Accuracy in Pipelines

AI hallucinations occur when models generate outputs that are precise yet incorrect, often due to insufficient training data or conflicting information, leading to erroneous conclusions. New strategies are needed to design systems that can detect these hallucinations before they reach users. In large language models, hallucinations present a complex issue, as AI can produce confident outputs that may contradict factual information. For instance, AI models might provide incorrect answers due to a lack of reliable data or conflicting training information.