What role do 'limits' play in guiding the output of an LLM?

Limitations are crucial in guiding the output of a Large Language Model (LLM) because they establish the boundaries of what is considered acceptable in terms of the content it generates. These limits ensure that the outputs align with ethical standards, compliance requirements, and user expectations, preventing the model from producing harmful, irrelevant, or inappropriate content. By defining these boundaries, limits help to maintain the quality and relevance of responses, ensuring that the LLM operates within a safe and constructive framework. In this way, they are vital for controlled and responsible usage of the technology, fostering trust among users while allowing for meaningful engagement.

While other aspects of output control, such as creativity and response length, exist, the primary function of these limits is to delineate the safe and responsible range within which the model can generate its responses.