What does "Grounding" refer to in model guidance?

"Grounding" in model guidance specifically refers to the process of connecting the AI's output to verified information. This is essential for ensuring that the generative model produces responses that are not only coherent but also factually accurate and relevant to the context in which it is used. By grounding outputs in reliable data, the model can provide users with trustworthy information and minimize the risks associated with generating misleading or incorrect content.

For instance, when an AI system generates textual responses, grounding helps ensure that the facts included in those responses are based on documented knowledge or data, which improves the credibility of the output. This method serves as a bridge between the model's generative capabilities and the real-world information that users seek, fostering a more effective interaction between humans and artificial intelligence.