AIF-C01 Applications of Foundation Models Practice Question
An enterprise deploys a foundation model on Amazon Bedrock with a knowledge base. Users report that the model is returning outdated information. What is the most likely cause?
⚠ Common exam trap
Watch out — candidates often confuse model versioning (Option B) with data freshness, but the question specifically ties the symptom to the knowledge base, making the refresh cycle the critical factor.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The knowledge base data source is not refreshed
When a knowledge base is attached to a foundation model on Amazon Bedrock, the model retrieves information from the data source to augment its responses. If the data source is not refreshed, the model will return outdated information even if the model itself is current. Option C directly addresses this by identifying the stale data source as the root cause.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model was fine-tuned
Why it's wrong here
Fine-tuning alters model weights for style or task behaviour; it does not refresh factual content, so stale knowledge-base data still surfaces. It is tempting because fine-tuning is the usual remedy for poor task performance, and would be correct if the model ignored domain format rather than returning old facts.
- ✗
The model is not the latest version
Why it's wrong here
Bedrock serves current foundation model versions; version age does not govern retrieval, so stale knowledge-base documents remain the source of outdated answers. It is tempting because upgrading models often fixes capability gaps, and would be correct if the model lacked a feature present only in a newer release.
- ✓
The knowledge base data source is not refreshed
Why this is correct
Stale source content propagates directly into retrieval: Amazon Bedrock knowledge bases sync from the configured data source, so unchanged documents keep returning outdated chunks regardless of model capability. Refreshing or re-syncing the data source satisfies the freshness constraint the stem describes.
- ✗
The inference parameters are incorrect
Why it's wrong here
Inference parameters such as temperature and top-p shape randomness and length, not factual currency, so retrieval still returns stale documents. It is tempting because tuning parameters is a common fix for odd outputs, and would be correct if answers were malformed or inconsistent rather than outdated.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AIF-C01 question from scratch — 862 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.