NCA-GENM Question 153
Select 3You are tasked with optimizing a multimodal AI model used for real-time video analysis and text extraction. The model currently exhibits high latency and consumes excessive computational resources during deployment. Which of the following strategies would be most effective for improving the model's performance while maintaining accuracy and trustworthiness?
- A
Implement transfer learning with a pre-trained model to reduce the training time and computational requirements.
- B
Use hyperparameter tuning to optimize the model's architecture and reduce overfitting.
- C
Increase the model's complexity by adding more layers and parameters for better data representation.
- D
Conduct rigorous testing with diverse datasets to ensure fairness and robustness.
- E
Train the model from scratch using a large multimodal dataset to maximize its accuracy.
Show answer and explanation
Correct answers: A, B, D
Explanation
Optimizing a multimodal AI model for energy efficiency, trustworthiness, and accuracy requires a balanced approach. Transfer learning and hyperparameter tuning help reduce computational requirements while maintaining performance, and rigorous testing ensures the model remains fair and robust in diverse scenarios. Avoid strategies like increasing model complexity or training from scratch as they contradict the goal of resource efficiency.
- A. Correct.
Transfer learning leverages pre-trained models, which can significantly reduce computational overhead and training time while maintaining high accuracy, making it an effective optimization strategy.
- B. Correct.
Hyperparameter tuning can optimize the model's structure and performance, improving resource efficiency and reducing overfitting without sacrificing accuracy.
- C. Incorrect.
Increasing the model's complexity may improve representation but will likely worsen the computational efficiency and latency, contradicting the optimization goal.
- D. Correct.
Rigorous testing with diverse datasets ensures the model is trustworthy, fair, and robust, which is essential for a reliable multimodal AI system.
- E. Incorrect.
Training the model from scratch is resource-intensive and not ideal for optimization, especially when pre-trained models and transfer learning are available as alternatives.