section_path: Features and limitations/Limitations/Hallucination
section_name: Hallucination
paragraph_text: Hallucination
  
  OpenAI stated ChatGPT "sometimes writes plausible-sounding but incorrect or nonsensical answers". This behavior, referred to as hallucination, is common for large language models.
  
  In an article for The New Yorker, science fiction writer Ted Chiang compared ChatGPT and other LLMs to a lossy JPEG picture:
  
  Think of ChatGPT as a blurry JPEG of all the text on the Web. It retains much of the information on the Web, in the same way, that a JPEG retains much of the information of a higher-resolution image, but, if you're looking for an exact sequence of bits, you won't find it; all you will ever get is an approximation. But, because the approximation is presented in the form of grammatical text, which ChatGPT excels at creating, it's usually acceptable. It's also a way to understand the "hallucinations", or nonsensical answers to factual questions, to which large language models such as ChatGPT are all too prone. These hallucinations are compression artifacts, but they are plausible enough that identifying them requires comparing them against the originals, which in this case means either the Web or our knowledge of the world. When we think about them this way, such hallucinations are anything but surprising; if a compression algorithm is designed to reconstruct text after ninety-nine percent of the original has been discarded, we should expect that significant portions of what it generates will be entirely fabricated.
  
  Journalists and scholars commented on ChatGPT's tendency to hallucinate. When CNBC asked ChatGPT for the lyrics to " Ballad of Dwight Fry ", ChatGPT supplied invented lyrics rather than the actual lyrics. Writers for The Verge cited the seminal 2021 research paper " On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 " by Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Margaret Mitchell, comparing ChatGPT to a " stochastic parrot ", as did Professor Anton Van Den Hengel of the Australian Institute for Machine Learning. In a similar vein, philosopher Michael Hicks of the University of Glasgow described it as "bullshit".