Cogging : A Missing Term in A.I. - Redefining Understanding in Large Language Models

Large Language Models (LLMs) have dramatically increased the capabilities of AI solutions by being able to generate human-like text in response to prompts. However, a misconception has arisen that these models "think" or "understand”. This misconception is perpetuated by continued inappropriate use of the words ‘think’ and ‘understand’. This paper addresses this misconception and inappropriate use by introducing the terms "cog" and "cogging" as replacements when referring to the operations of LLMs. The proposed terminology aims to clarify that LLMs generate statistically coherent responses without possessing consciousness, intentionality, or true understanding. Adopting "cog" and "cogging," provides a more accurate framework for discussing the capabilities and limitations of LLMs, ultimately contributing to a clearer understanding of artificial intelligence in both academic and public discourse.