According to Andrej Karpathy (@karpathy), large language models (LLMs) should be viewed as simulators rather than entities with their own opinions. He emphasizes that when exploring topics using LLMs, users achieve more insightful and diverse outputs by prompting the model to simulate the perspectives of various groups, rather than addressing the LLM as an individual. This approach helps businesses and researchers extract richer, multi-dimensional insights for market analysis, product development, and academic studies. Karpathy also highlights that the perceived 'personality' of LLMs is a statistical artifact of their training data, not genuine thought, which is critical for organizations to consider when integrating LLMs into decision-making workflows (source: @karpathy, Twitter, Dec 7, 2025).