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lock_openFree sampleGenerative AI fundamentalsmedium
A support team sends the same prompt to a hosted LLM many times a day and gets noticeably different wording each time. They want answers to stay closely on-message and vary far less, without demanding byte-for-byte identical output. Which change best achieves this?
- ALower the temperature toward 0.2 so the model concentrates on the highest-probability tokens.check_circle Correct
- BRaise the temperature toward 1.0 so the model considers a wider spread of next tokens.
- CIncrease the maximum output-token limit so each answer has room to finish completely.
- DRaise top-p toward 1.0 so the model samples from the full probability distribution.
Lowering temperature concentrates output on the most-probable tokens, reducing run-to-run variation. Temperature scales how sharply the model favours its most-probable tokens. Lowering it toward 0 concentrates probability mass on the top tokens, so the same prompt produces closely similar, on-message wording each time without forcing fully identical output.
Why A is correct: Correct. A low temperature sharpens the distribution toward the likeliest tokens, so wording stays consistent run to run while still allowing slight variation.
lock_openFree sampleGenerative AI fundamentalsmedium
A developer is tuning a model's top-p (nucleus) sampling value and wants to be sure they understand its effect. Which statement best describes how top-p selects the tokens the model samples from?
- AIt caps the total number of tokens the model is allowed to generate in the response.
- BIt restricts sampling to the smallest set of top tokens whose cumulative probability reaches p.check_circle Correct
- CIt sets a fixed random seed so the same prompt always returns the same response.
- DIt scales the model's confidence by reweighting every token's probability before sampling.
Top-p sampling draws from the smallest set of tokens whose cumulative probability reaches p. Top-p, or nucleus sampling, ranks tokens by probability and keeps the smallest set whose cumulative probability reaches the threshold p, discarding the long tail. The model then samples only from that nucleus, so a lower p narrows the candidate set.
Why B is correct: Correct. Nucleus sampling keeps the smallest group of most-likely tokens whose probabilities sum to p, then samples only from that group.
lock_openFree sampleGenerative AI fundamentalsmedium
An application caches model responses using the exact prompt text as the cache key, to avoid paying for repeated identical calls. For the cache to be useful, the same prompt must return the same answer. Which setting makes the output deterministic?
- ASet top-p to 1.0 so the model can draw from every available token at each step.
- BUse a larger model with more parameters and a wider context window for the call.
- CSet the temperature to 0 so the model always selects the highest-probability token.check_circle Correct
- DRaise the temperature to 0.8 to make the cached answers more natural and fluent.
Temperature 0 produces greedy, deterministic decoding suitable for caching identical prompts. With temperature 0 the model decodes greedily, always taking the single highest-probability token rather than sampling. The same prompt therefore yields the same output every call, which is exactly what a prompt-keyed response cache depends on.
Why C is correct: Correct. Temperature 0 forces greedy decoding: the single most-probable token is chosen at each step, so the same prompt yields the same answer.
Frequently asked questions
- How many questions are on the AIF-C01 exam?
- The AWS Certified AI Practitioner (AIF-C01) exam has 65 questions and runs for 90 minutes. The format is multiple choice and multiple response.
- What score do I need to pass AIF-C01?
- The pass mark is 700 / 1000. Examworthy gives you a per-domain readiness score so you can see which domains are holding you back before you book.
- How much does the AIF-C01 exam cost?
- The exam costs 100 USD to sit. Practising on Examworthy is free to start, with a worked explanation on every question.
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- Every practice question carries a worked explanation and a per-distractor rationale, mapped to the official blueprint domains. You learn why each answer is right or wrong, not just the letter.
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Examworthy is not affiliated with or endorsed by Amazon Web Services. All questions are original, blueprint-aligned practice material. We never reproduce live exam items. AIF-C01 and related marks belong to their respective owners.
