OpenAI Realizes It Made a Terrible Mistake

OpenAI researchers claim they’ve identified why AI models “hallucinate” - fabricating incorrect answers instead of admitting uncertainty. The problem stems from binary training systems that reward correct guesses while penalizing admissions of ignorance, incentivizing models to guess rather than acknowledge limitations. The researchers argue that evaluation methods optimize AI to be “good test-takers” where lucky guesses outperform honest uncertainty, creating pressures toward hallucination during training. OpenAI proposes modified evaluation systems that penalize confident errors more than expressions of uncertainty and provide partial credit for appropriate acknowledgment of limits. However, real-world effectiveness remains questionable as users report OpenAI’s latest GPT-5 model continues making significant factual errors despite claims of improvement, while the AI industry invests tens of billions in technology still fundamentally challenged by reliability issues.​​​​​​​​​​​​​​​​