Google Cloud Professional Machine Learning Engineer — Question 293

You work for a media company that operates a streaming movie platform where users can search for movies in a database. The existing search algorithm uses keyword matching to return results. Recently, you have observed an increase in searches using complex semantic queries that include the movies’ metadata such as the actor, genre, and director.

You need to build a revamped search solution that will provide better results, and you need to build this proof of concept as quickly as possible. How should you build the search platform?

Answer options

• A. Use a foundational large language model (LLM) from Model Garden as the search platform’s backend.
• B. Configure Vertex AI Vector Search as the search platform’s backend.
• C. Use a BERT-based model and host it on a Vertex AI endpoint.
• D. Create the search platform through Vertex AI Agent Builder.

Correct answer: B

Explanation

The correct answer is B, as Vertex AI Vector Search is specifically designed to handle complex semantic queries and can efficiently manage the metadata associated with movies. While options A and C involve using language models, they do not focus on the vector search capabilities needed for improved query handling. Option D, while a valid tool, does not specifically address the requirement for advanced search capabilities as effectively as Vertex AI Vector Search does.