NCA-GENM Question 117
Single answerYou are assisting a senior team member in deploying a multimodal generative AI model. During the evaluation phase, the team observes that the model's performance degrades significantly when handling large input datasets. What action should you prioritize under supervision to ensure scalability and reliability of the model?
- A
Optimize the model's hyperparameters and retrain it with a smaller subset of the dataset.
- B
Implement batch processing techniques to handle large input datasets more efficiently.
- C
Add more GPU nodes to the deployment environment without modifying the model.
- D
Reduce the model's parameters to decrease computational complexity.
Show answer and explanation
Correct answer: B
Explanation
Batch processing techniques are commonly used to handle large input datasets efficiently in generative AI workflows. This approach ensures the model can scale while maintaining reliability and performance, making it the most suitable choice in this scenario.
- A. Incorrect.
While optimizing hyperparameters can improve model performance, it does not directly address scalability issues when handling large datasets. Retraining on a smaller dataset might also lead to a loss in generalization.
- B. Correct.
Implementing batch processing techniques is a practical solution for managing large datasets. It ensures efficient resource utilization and improves the model's ability to scale.
- C. Incorrect.
Adding more GPU nodes may improve performance but does not address underlying scalability issues. Without efficient data handling mechanisms like batching, resource usage may remain suboptimal.
- D. Incorrect.
Reducing the model's parameters might decrease computational complexity, but it could lead to a loss in accuracy and does not specifically solve the problem of handling large datasets.