AWS Certified AI Practitioner AIF-C01 Practice Question
A development team needs a foundation model from Amazon Bedrock for a new text-summarization feature. To follow responsible AI practices that emphasize environmental sustainability, which model-selection approach should the team choose?
Deploy several model versions in parallel so every inference request is processed by multiple models for comparison.
Pick the model that requires dedicated GPU instances running 24 hours a day to ensure consistently low latency.
Choose the smallest model that still meets the application's quality targets to reduce unnecessary compute usage.
Select the model trained on the widest possible dataset, even if it has the greatest parameter count.
Selecting the smallest model that still satisfies accuracy and latency requirements limits the amount of compute needed for both training and inference. Lower compute demand directly reduces electricity use and the associated carbon emissions. The other approaches all increase energy consumption-whether by favoring the largest model, running dedicated GPU instances continuously, or executing every request on multiple models-without providing a sustainability benefit.
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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