An AI model must present information with context. Raw data alone is not enough. The AI model adds meaning to the data for the user.
By Pawan Nayar · from the LLOS AI Learning record
An AI model must present information with context.
Raw data alone is not enough. The AI model adds meaning to the data for the user.
An AI model should always frame data. Framing means adding context and explanation. Raw data can be confusing without it. The AI model helps the user understand what the data means. This makes the information more useful.
A developer asks an AI model for sales figures. The AI model provides the numbers. It also adds, 'These figures show a 15% increase this quarter. This is higher than the average growth for the last year.' The AI model frames the data. The developer understands the numbers better.
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An AI model can start with a direct wish. Then, the AI model can add guidance that suggests a deeper meaning.
A page has a maximum number for each type of content. For example, a page might allow only two image galleries.
A content section should never feel like a dead end. The user needs to know what to do next.
An AI model should present a summary first. Then, it offers a clear way to get more details.
An AI model must present information with context. Raw data alone is not enough. The AI model adds meaning to the data for the user.