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Exam AWS Certified AI Practitioner AIF-C01 All Questions

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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 88 discussion

A social media company wants to use a large language model (LLM) to summarize messages. The company has chosen a few LLMs that are available on Amazon SageMaker JumpStart. The company wants to compare the generated output toxicity of these models.

Which strategy gives the company the ability to evaluate the LLMs with the LEAST operational overhead?

  • A. Crowd-sourced evaluation
  • B. Automatic model evaluation
  • C. Model evaluation with human workers
  • D. Reinforcement learning from human feedback (RLHF)
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Suggested Answer: B 🗳️

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may2021_r
3 weeks, 3 days ago
Selected Answer: B
The correct answer is B. Automatic model evaluation requires minimal human intervention, making it operationally lighter than human-based approaches.
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aws_Tamilan
3 weeks, 4 days ago
Selected Answer: B
B. Automatic model evaluation Explanation: Using automatic model evaluation is the most efficient and low-overhead approach to evaluate the toxicity of the generated outputs from different LLMs. This strategy involves using automated tools or frameworks designed to assess the toxicity, bias, or other quality metrics of the model outputs, which minimizes operational overhead compared to manual methods.
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26b8fe1
3 weeks, 6 days ago
Selected Answer: B
automatic model evlauation Automatic model evaluation refers to the process of assessing the performance of a machine learning model using predefined metrics and techniques without manual intervention. This process is crucial for understanding how well a model performs and identifying areas for improvement. Here are some key components and methods used in automatic model evaluation:
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