NCA-GENM Question 75
Select 3A research team is developing a multimodal generative AI model that combines image and text data. During the evaluation phase, they notice that the model underperforms when generating captions for specific types of images. Which factors should the team consider to identify relationships or trends affecting the model's performance?
- A
The distribution of image types in the training dataset
- B
The quality and diversity of captions in the training dataset
- C
The computational power used during model training
- D
The alignment between the text and image features in the dataset
- E
The version of the generative AI framework being used
Show answer and explanation
Correct answers: A, B, D
Explanation
For a multimodal generative AI model, identifying relationships and trends involves analyzing the dataset's composition, including the balance and alignment of the modalities (e.g., text and images). An imbalanced or misaligned dataset may lead to poor performance in certain scenarios. While computational power and framework versions are important for training efficiency and feature availability, they are not directly linked to the dataset's relationships or trends.
- A. Correct.
The distribution of image types in the training dataset is crucial, as an imbalance in image types can lead to biases in the model's performance.
- B. Correct.
The quality and diversity of captions in the training dataset significantly affect the model's ability to generate meaningful and accurate outputs.
- C. Incorrect.
While computational power affects training efficiency, it does not directly influence the relationships and trends affecting model performance.
- D. Correct.
The alignment between the text and image features is critical for a multimodal model as it ensures the data modalities are effectively correlated during learning.
- E. Incorrect.
The version of the generative AI framework affects feature availability and optimization but is not directly related to relationships or trends in the dataset.