When LLMs Day Dream: Hallucinations And How To Prevent Them
Red Hat News, Wednesday, September 25th, 2024
Most general purpose large language models (LLM) are trained with a wide range of generic data on the internet.
They often lack domain-specific knowledge, which makes it challenging to generate accurate or relevant responses in specialized fields. They also lack the ability to process new or technical terms, leading to misunderstandings or incorrect information.
An "AI hallucination" is a term used to indicate that an AI model has produced information that's either false or misleading, but is presented as factual. This is a direct result of the model training goal of always predicting the next token regardless of the question. It can be difficult to tell whether information provided by AI contains learned facts or a hallucination. This is a problem when you're trying to use an LLM for critical purposes and applications such as those used in healthcare or finance.