ginterpretary
**ginterpretary** is a term used in the context of generative artificial intelligence (AI) and natural language processing (NLP) to describe the interpretability of outputs generated by models such as large language models (LLMs). Unlike traditional AI systems, which often rely on opaque neural networks, generative models produce human-like text, code, or other forms of output that may appear coherent but lack clear, transparent reasoning. The term highlights the challenge of understanding how these models arrive at their responses, particularly when they generate plausible but incorrect, biased, or nonsensical outputs.
The interpretability gap in generative AI arises because these models learn patterns from vast datasets rather
Researchers and practitioners often explore methods to improve interpretability, such as prompting models to explain their