AWS Certified Cloud Practitioner
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An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images. Which type of FM should the AI practitioner use to power the search application?
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Community
RRitesh
A
Multi-modal embedding model
B
Text embedding model
C
Multi-modal generation model
D
Image generation model
Explanation:
Explanation
Why A is correct:
- A multi-modal embedding model is specifically designed to handle multiple types of data (text, images, audio, etc.) and convert them into vector embeddings in a shared semantic space.
- For a search application that needs to handle both text and image queries, a multi-modal embedding model can create embeddings for both modalities that are comparable, enabling cross-modal search capabilities.
- This allows users to search with text and find relevant images, or search with images and find relevant text content.
Why other options are incorrect:
- B. Text embedding model: Only handles text data and cannot process or understand image content.
- C. Multi-modal generation model: While it can handle multiple modalities, it's designed for generation tasks (creating content) rather than search/retrieval tasks.
- D. Image generation model: Only handles image generation and cannot process text queries or create comparable embeddings for search.
Key Concept: Multi-modal embedding models create vector representations of different data types in a shared space, enabling cross-modal similarity search and retrieval.
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