New Delhi: A new peer-reviewed study has raised questions about how much artificial intelligence models really understand the difference between what is true and what someone merely believes. Researchers at Stanford University found that large language models (LLMs) often fail to separate factual knowledge from personal belief, and even more worryingly, struggle to recognize when a belief is false.

The findings, published in Nature Machine Intelligence , show that despite all the progress in AI, models like GPT-4o and DeepSeek R1 are still missing a key ingredient of human reasoning — the ability to know when something is factually wrong.

What the study found

The research team led by James Zou, associate professor at Stanford University, tested 24 popular large language models across

See Full Page