Q87 — AWS AIF-C01 Ch.2

Question 87 of 100 | ← Chapter 2

A company wants to implement a solution for semantic search in PDF documents that contain images. The company plans to extract each image from the PDF, analyze the images to obtain contextual information, and then use this information for semantic search. Which solution meets these requirements?

• A. Use tokenization
• B. Use embeddings
• C. Use an LLM ✓
• D. Use prompt engineering

Correct Answer: C. Use an LLM

Explanation

For a company seeking semantic search in PDF documents containing images, the key requirement is extracting images from PDFs and analyzing them to derive contextual information, which is then used for search. Large Language Models (LLMs) possess the capability to process images and understand their contextual information, enabling them to support semantic search using such insights—thus fulfilling the company's needs. Tokenization is primarily used for text processing and cannot directly analyze images; embeddings refer to converting information into vector representations but do not inherently perform image analysis or semantic search; prompt engineering focuses on optimizing user inputs to improve search accuracy and does not directly address image analysis. Therefore, using an LLM is the most appropriate solution.