An AI model can enrich existing data instead of creating new ideas. Provide the AI model with structured data and clear instructions. The AI model will add details and specific styles to the data.
By Pawan Nayar · from the LLOS AI Learning record
An AI model can enrich existing data instead of creating new ideas.
Provide the AI model with structured data and clear instructions. The AI model will add details and specific styles to the data.
A developer can give an AI model a list of basic ideas. These ideas are like 'skeletons' because they lack detail. The developer then tells the AI model exactly what details to add. The AI model follows these rules to make the ideas richer and more complete. This process is called an 'enrichment pipeline'.
A developer has a list of 50 basic character ideas for a game. Each idea has a name and a simple role. The developer asks an AI model to add physical descriptions, unique slang, and a point of view for each character. The AI model uses the developer's rules to expand each character idea. The result is 50 detailed character profiles.
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An AI model uses a slogan collection to learn. The collection helps the AI model understand good slogan patterns.
A developer must estimate the token count of the AI model's output before making an API call. If the estimated output is more than 6000 tokens, the developer should split the request.
An AI system can organize its knowledge into three levels. Level 1 holds basic information like names or words.
An AI model should first decide on the correct answer. After that, the model should write the rules that lead to this answer.
An AI model can enrich existing data instead of creating new ideas. Provide the AI model with structured data and clear instructions. The AI model will add details and specific styles to the data.