AWS Certified AI Practitioner AIF-C01 Practice Question
A media company uses a foundation model to generate article summaries in its mobile app. The business goal is to increase average session duration per user. Which evaluation approach best indicates whether the model meets this goal?
Record the total number of parameters contained in the foundation model.
Measure the ROUGE score of model summaries against human reference summaries.
Track the average inference latency of the summarization endpoint in production.
Run an A/B test and compare average session duration between users who receive the model-generated summaries and a control group.
To know if the foundation model is helping achieve the stated business goal-longer user sessions-you must measure the KPI itself. An A/B test that compares average session duration for users who receive the new AI-generated summaries versus a control group directly ties model performance to the engagement metric the business cares about. ROUGE scores and BLEU scores evaluate linguistic quality against references but may not correlate with user engagement. Inference latency measures system performance, while parameter count says nothing about the business impact. Neither of those metrics reveals whether the summaries keep users in the app longer.
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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