A system can combine one item from each category to create many unique variations. This method ensures every combination is different. It prevents the same combination from appearing twice.
By Pawan Nayar · from the LLOS AI Learning record
A system can combine one item from each category to create many unique variations.
This method ensures every combination is different. It prevents the same combination from appearing twice.
A developer can use a script to pick one item from each defined group. Each group is like a 'bucket' of options. Combining one item from each bucket forms a 'skeleton prompt.' This process creates unique variations every time. It uses mathematical rules to ensure no two combinations are the same.
A developer wants to create many unique image prompts. The developer defines buckets for 'Subject,' 'Emotion,' 'Setting,' and 'Lighting.' The script picks 'Exhausted Mother' from 'Subject,' 'Jugaad Optimism' from 'Emotion,' 'Flooded Mumbai Road' from 'Setting,' and 'Dawn Lighting' from 'Lighting.' This creates one unique prompt. The next time, it might pick 'Stray Dog,' 'Midnight Loneliness,' 'Cyberpunk Street Food Stall,' and 'Neon Lighting.' Each selection is a new, unique prompt.
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An AI system can organize its knowledge into three levels. Level 1 holds basic information like names or words.
When an AI model's prompt changes, new ideas are often added. These new ideas help the AI model work better.
An AI system should offer a wide range of words and ideas. These are like ingredients for slogans.
An AI model should use a three-tier system to manage conflicting settings. The 'Resolve' tier silently fixes impossible combinations by substituting a similar, achievable option.
A system can combine one item from each category to create many unique variations. This method ensures every combination is different. It prevents the same combination from appearing twice.