An AI model's output must change based on user settings. The model should not always use the same vocabulary for a specific voice, regardless of the input.
By Pawan Nayar · from the LLOS AI Learning record
An AI model's output must change based on user settings.
The model should not always use the same vocabulary for a specific voice, regardless of the input.
An AI model's 'voice' should only control the writing style, like sentence structure and rhythm. It should not control the specific words or content. A separate system must check if the user's input topic is similar to the voice's usual topics. If the topics do not match, the AI model must avoid using words strongly linked to that voice.
A user asks an AI model to write about 'traffic' in the voice of a philosopher known for writing about 'order'. The AI model should use the philosopher's writing style. However, the AI model should not use words like 'order' or 'chaos' unless the user's input also relates to these ideas. This prevents the AI model from always writing about 'order' when using that philosopher's voice.
More from the same record, pulled by shared topic — not written new for this page.
The AI model's internal data structure needs to be reviewed. The data that defines a 'voice' or style should be separated.
An AI model should use rare words from different difficulty levels. This means not just using words that are a little uncommon.
An AI model's 'voice' setting defines how sentences are built. It also defines the special ways sentences change or turn.
The AI model saw special formatting in the instructions. This formatting made the instructions look like important text.
An AI model's output must change based on user settings. The model should not always use the same vocabulary for a specific voice, regardless of the input.