An AI practitioner wants to use a foundation model (FM) to design a search application.

A multi-modal embedding model is the correct type of foundation model (FM) for powering a search application that handles queries containing both text and images.

Multi-Modal Embedding Model:

Can process and integrate different types of data (e.g., text and images) into a common representation space, enabling a unified search capability.

Suitable for applications where queries or content involve multiple data modalities.

Why Option A is Correct:

Handles Multiple Modalities: Supports both text and image data, aligning with the application's requirement.

Improves Search Relevance: Allows for more accurate and relevant search results across different types of input data.

Why Other Options are Incorrect:

B. Text embedding model: Only handles text data, not images.

C. Multi-modal generation model: Focuses on generating outputs rather than embedding for search tasks.

D. Image generation model: Only handles image data, not suitable for text queries.