MLS-C01 Question #292: Real Exam Question with Answer & Explanation

Question

A company needs to deploy a chatbot to answer common questions from customers. The chatbot must base its answers on company documentation. Which solution will meet these requirements with the LEAST development effort?

Options

• AIndex company documents by using Amazon Kendra. Integrate the chatbot with Amazon Kendra
• BTrain a Bidirectional Attention Flow (BiDAF) network based on past customer questions and
• CTrain an Amazon SageMaker Blazing Text model based on past customer questions and
• DIndex company documents by using Amazon OpenSearch Service. Integrate the chatbot with

Explanation

To deploy a chatbot that answers common questions based on company documentation with the least development effort, Amazon Kendra should be used to index the documents and integrate with the chatbot.

Common mistakes.

• B. Training a custom Bidirectional Attention Flow (BiDAF) network requires significant machine learning expertise, data preparation, and development effort, which contradicts the goal of achieving the solution with the least development effort.
• C. Amazon SageMaker BlazingText is a built-in algorithm primarily for word embeddings, text classification, and sentiment analysis, and it is not designed to directly power a natural language question-answering chatbot over documentation.
• D. While Amazon OpenSearch Service is a robust search engine, integrating it with a chatbot for natural language question answering from documents requires substantial custom development for semantic search and answer extraction capabilities, unlike the out-of-the-box functionality offered by Amazon Kendra.

Concept tested. Amazon Kendra for intelligent search and Q&A chatbots

Reference. https://aws.amazon.com/kendra/

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