AI hallucinations produce confident but false outputs, undermining AI accuracy. Learn how generative AI risks arise and ways to improve reliability.

AI models such as ChatGPT “hallucinate”, or make up facts, mainly because they are trained to make guesses rather than admit a lack of knowledge, a new study reveals. Hallucination is a major concern ...

100 vibe citations spotted in 51 NeurIPS papers show vetting efforts have room for improvement GPTZero, a detector of AI ...

If you’ve ever asked ChatGPT a question only to receive an answer that reads well but is completely wrong, then you’ve witnessed a hallucination. Some hallucinations can be downright funny (i.e. the ...

The use of artificial intelligence (AI) tools — especially large language models (LLMs) — presents a growing concern in the legal world. The issue stems from the fact that general-purpose models such ...

When an Air Canada customer service chatbot assured a passenger that they qualified for a bereavement refund—a policy that didn't exist—nobody suspected anything. The passenger booked their ticket ...

Humans are misusing the medical term hallucination to describe AI errors The medical term confabulation is a better approximation of faulty AI output Dropping the term hallucination helps dispel myths ...

In Davos, our AI & Tech Editor Aayush Ailawadi spoke with Cathy Li, Head of the Centre for AI Excellence at the World Economic Forum, about the Golden Age of AI, AI hallucinations, AGI, and ...

Forbes contributors publish independent expert analyses and insights. Jason Alan Snyder is a technologist covering AI and innovation. This voice experience is generated by AI. Learn more. This voice ...