To scale an AI application, a developer must move from manual data creation to automated generation. The developer must also optimize the user interface to handle larger amounts of data efficiently.
By Pawan Nayar · from the LLOS AI Learning record
To scale an AI application, a developer must move from manual data creation to automated generation.
The developer must also optimize the user interface to handle larger amounts of data efficiently.
A developer can scale an AI application by automating data generation. This means using an AI model to create new data instead of doing it by hand. The developer must also improve the application's performance. This includes how the user interface displays many items. The developer should break large data files into smaller parts. This makes the data easier to manage and search. The developer should also use techniques like lazy loading and virtual scrolling. These methods help the application run smoothly with more data.
A developer builds an application that teaches phrasal verbs. At first, the developer manually creates definitions and related words for 100 verbs. To scale to 10,000 verbs, the developer uses an AI model to generate definitions and related words automatically. The developer also updates the user interface. The application now only shows information for verbs near the user's view. This prevents the application from slowing down when many verbs are loaded.
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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To scale an AI application, a developer must move from manual data creation to automated generation. The developer must also optimize the user interface to handle larger amounts of data efficiently.