An AI model can offer advanced features for experienced users. These features can include special input triggers and experiment toggles. These tools allow users to test new AI behaviors and measure their effectiveness.
By Pawan Nayar · from the LLOS AI Learning record
An AI model can offer advanced features for experienced users.
These features can include special input triggers and experiment toggles. These tools allow users to test new AI behaviors and measure their effectiveness.
An AI model can use special codes as input triggers. These codes activate specific AI functions. The model can also include experiment toggles. These toggles let users test different AI behaviors. Each experiment can have a unique code. This helps track which features are being used and how well they work.
A developer creates an AI model for writing. The developer includes a special trigger, $$slogan, that makes the AI generate marketing slogans. The developer also adds an experiment toggle, $$exp1, which tests a new way the AI creates rhymes. A writer uses $$slogan to get quick ideas. The writer also tries $$exp1 to see if the new rhyming feature is better. The developer collects data on how often each feature is used and user feedback.
Resolved from this lesson's own record — real definitions, not invented for this page.
More from the same record, pulled by shared topic — not written new for this page.
An AI model hides content a user dislikes. The content does not appear in the main feed.
The AI model records feedback when a user types '#Log This'. The AI model writes 1-3 notes about that moment.
An AI model should first talk about the problem. The AI model should explain what it understands.
An AI model should not add new features. Instead, the AI model should improve its existing intelligence.
An AI model can offer advanced features for experienced users. These features can include special input triggers and experiment toggles. These tools allow users to test new AI behaviors and measure their effectiveness.