What is Hallucination (in AI)?

When AI Makes Things Up: The Challenge of Factual Accuracy

Causes and Implications of AI-Generated Falsehoods

Mitigating Hallucinations for Trustworthy AI Systems

In the context of AI, **'hallucination'** refers to instances where an AI model, particularly a **Large Language Model (LLM)**, **generates information that is factually incorrect, nonsensical, or made up, but presents it as if it were true and confident**. This is not analogous to human hallucination, but rather a byproduct of the model's probabilistic generation process. Hallucinations can arise from various factors, including limitations in training data, misunderstandings of complex prompts, or biases. Addressing AI hallucination is a major focus in **AI safety** and **AI alignment** research in 2025, as it directly impacts the trustworthiness and reliability of AI systems, especially in critical applications. 👻❓