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Answer: When the new solution requires each model to make a prediction for every record
The engineer's observation about the new solution being less time efficient during inference is most directly applicable when the new solution requires each of the three models to compute a prediction for every record. This approach multiplies the computation needed for inference across the dataset. Even if each model's latency is similar to the original, requiring all models to predict for each record triples the computational work, increasing the total time required to process the same number of records. Options A, C, D, and E do not directly address the scenario's constraints or imply an increase in computational load as described in option B.
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A data scientist has developed three new models for a machine learning problem, replacing a single model solution. All models have similar prediction latency. However, a machine learning engineer suggests the new solution will be less time efficient during inference. Under what condition is the engineer's observation correct? Choose the best answer.
A
When the new solution's models are larger in size than the original model
B
When the new solution requires each model to make a prediction for every record
C
When the new solution's models have higher average latency than the original
D
When the new solution uses conditional logic to select a model for each prediction
E
When the new solution uses fewer feature variables than the original model