OpenAI Admits: AI Hallucinations Stem from Fundamental Training Flaws

OpenAI has published a paper revealing that the 'hallucinations' in its large language models aren't accidental; they're a consequence of fundamental flaws in the training methodology. Models are trained to prioritize guessing over admitting ignorance, as this yields higher scores in current evaluation systems. The paper uses the example of finding a researcher's birthday to demonstrate how the training mechanism leads to incorrect answers. OpenAI acknowledges that mainstream evaluation methods reward this 'hallucinatory' behavior and states it's improving training mechanisms, such as prompting models to more frequently respond with 'I don't know,' but completely resolving the issue remains a challenge.