Q86 — AWS AIF-C01 Ch.3

Question 86 of 100 | ← Chapter 3

A company applies human-centered design to its AI application using Reinforcement Learning from Human Feedback (RLHF). The company wants to create a trustworthy training dataset that incorporates human feedback to improve its large language model (LLM) under development. Which solution meets these requirements?

• A. Use Amazon SageMaker built-in algorithms
• B. Use Amazon SageMaker Ground Truth ✓
• C. Use Amazon SageMaker Autopilot
• D. Use Amazon SageMaker Pipelines

Correct Answer: B. Use Amazon SageMaker Ground Truth

Explanation

Creating a trustworthy training dataset incorporating human feedback to enhance a large language model (LLM) requires efficient collection and processing of human judgments or annotations. Amazon SageMaker Ground Truth simplifies building high-quality, scalable ML training datasets—especially for tasks requiring human input or labeling. By leveraging SageMaker Ground Truth, the company can collect and integrate human feedback into RLHF-based training pipelines, thereby improving LLM performance.