TLDR:
Researchers have developed a method to detect AI hallucinations stemming from words with multiple meanings. They use semantic entropy to determine the probability of hallucination without human supervision.
Key Points:
- AI models prone to hallucinations and false answers
- Oxford researchers target the issue using semantic entropy
- Semantic entropy helps detect hallucinations quickly and accurately
- Potential to increase trust in AI reliability
Full Article:
The AI boom has allowed consumers to use AI chatbots like ChatGPT, but these models are prone to hallucinations, delivering false and sometimes dangerous answers. Oxford researchers developed a method to detect confabulations in AI models by using semantic entropy, where the same words have different meanings. This method helps determine the probability of AI hallucinations without human supervision, thus increasing trust in AI reliability. While error detection tools can make AI more reliable, it’s still wise to double-check AI responses.