An AI model pays most attention to information at the end of a list. Important rules placed at the end will override earlier instructions. This is called the recency effect.
By Pawan Nayar · from the LLOS AI Learning record
An AI model pays most attention to information at the end of a list.
Important rules placed at the end will override earlier instructions. This is called the recency effect.
An AI model often remembers the last things it reads best. This is called the recency effect. If a user puts important rules at the end of a prompt, the AI model will follow those rules more strongly. These final rules can change or override earlier instructions.
A developer gives an AI model instructions. The developer puts creative settings at the beginning of the prompt. The developer then puts strict rules, like banned words, at the end. The AI model will follow the strict rules at the end. It will ignore some of the creative settings from the beginning.
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The AI model's internal data structure needs to be reviewed. The data that defines a 'voice' or style should be separated.
The AI model saw special formatting in the instructions. This formatting made the instructions look like important text.
A developer includes parameters in a prompt. These parameters help the AI model understand the task.
The AI model needs to treat each instruction as a separate, important guide. If a user gives a phrase, the AI model should use that phrase directly.
An AI model pays most attention to information at the end of a list. Important rules placed at the end will override earlier instructions. This is called the recency effect.