GENERATIVE-AI-LEADER · Question #81
Sundale Electronics launched a generative AI support assistant, and after going live they observe that the assistant often produces fluent responses that fail to address customers' questions about…
The correct answer is C. Relevance. The correct option is Relevance because the training data does not adequately cover the new smart thermostats so the model generates fluent responses that are not aligned with the users Relevance measures how well the data used matches the target task and information needs…
Question
Sundale Electronics launched a generative AI support assistant, and after going live they observe that the assistant often produces fluent responses that fail to address customers' questions about their newly introduced smart thermostats. The model was trained on a large set of generic support logs collected over the past six years, and that set contains very little information about the latest devices. Which data quality attribute is most likely deficient and causing these off target replies?
Options
- AConsistency
- BTimeliness
- CRelevance
- DCompleteness
How the community answered
(25 responses)- A4% (1)
- B8% (2)
- C72% (18)
- D16% (4)
Explanation
The correct option is Relevance because the training data does not adequately cover the new smart thermostats so the model generates fluent responses that are not aligned with the users Relevance measures how well the data used matches the target task and information needs. Since the dataset consists mostly of older generic support logs and contains little content about the newest devices, the model lacks pertinent examples. This misalignment leads to answers that sound good but do not address the specific queries about the latest thermostats.
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