AWS Certified AI Practitioner AIF-C01 Practice Question
A company wants a generative-AI chatbot that rewrites a product feature list into a polished marketing blurb. Brand managers insist that the text must be identical every time when the same prompt is used. Which built-in limitation of large language models is most likely to prevent the team from meeting this requirement?
Fluctuating token pricing that changes operating costs over time
Cold-start latency that increases response time on the first invocation
The need for multilingual training data to avoid linguistic bias
Nondeterministic sampling that produces different token sequences for identical prompts
Large language models rely on probabilistic sampling when generating the next token. Even with the same prompt, the model may sample different high-probability tokens, leading to slightly different wording on each run. This stochastic behavior is known as nondeterminism. While settings such as temperature can reduce variability, they cannot eliminate it completely. The other options are unrelated: token pricing affects cost, cold-start latency affects response time, and multilingual data affects bias, not output repeatability.
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AWS Certified AI Practitioner AIF-C01
Fundamentals of Generative AI
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