An AI model uses a curated library of visual shapes to add meaning to content. The shapes are linked to specific content sections. This ensures consistent visuals and broad compatibility across different devices.
By Pawan Nayar · from the LLOS AI Learning record
An AI model uses a curated library of visual shapes to add meaning to content.
The shapes are linked to specific content sections. This ensures consistent visuals and broad compatibility across different devices.
A developer can add a `visual_match` object to the section's JSON data. This object tells the system which visual shape to use. It specifies a `slot` and an `index` for the shape. The `slot` defines the general meaning of the shape. The `index` picks a specific shape from that meaning group. This system ensures visuals are consistent and load correctly.
A developer is building a lesson about sentence structure. The developer adds a `visual_match` object to the lesson's JSON. For the `base_content` section, the developer sets `slot` to `structure_build`. For the `visual_mental_model` section, the developer sets `slot` to `focus_eye`. This makes sure the correct visual appears at the top of each panel.
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.
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An AI model uses a curated library of visual shapes to add meaning to content. The shapes are linked to specific content sections. This ensures consistent visuals and broad compatibility across different devices.