LLMs do not hallucinate - they simply do what they are supposed to do

The article discusses the issue of 'hallucination' in language models (LLMs), which can generate false information while being confident in its accuracy. The author points out that despite the advancements in technology, LLMs have a tendency to produce text that should not always be considered reliable. Key causes of this phenomenon are highlighted, including how models learn from data and their limitations in analyzing context. Furthermore, the article explores the differences between perception and reality, emphasizing that LLMs lack the ability to understand or verify facts in the same way humans do. The author suggests that users should be aware of these limitations and apply critical thinking when engaging with information provided by LLMs to avoid misinformation. Additionally, the importance of further research and development of LLMs is emphasized to enhance their reliability in representing and processing information.