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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

1. In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?

A) It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
B) It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
C) It ensures that AI systems are transparent in their decision-making processes.
D) It requires AI systems to be developed with an ethical consideration for societal impacts.

2. Assume you need to implement a multimodal pipeline to diagnose brain cancer type using MRI scans and their corresponding radiology reports. What do you need to include in the ablation study?

A) Directly combining MRI scans and radiology reports into a single input stream without preprocessing or modality-specific adjustments.
B) Implementing separate unimodal pipelines for each modality to ensure the data is informative and the model design is accurate.
C) More advanced natural language processing techniques to interpret radiology reports, ignoring the MRI scans' diagnostic value.
D) Training a deep learning model using the images in the dataset to find outliers and enhancing the quality of MRI scans using image processing techniques.

3. You have a dataset containing information about sales performance for different regions in the last ten years.
Which type of data visualization would be most appropriate to compare the sales performance across regions on a year-by-year basis?

A) Pie chart
B) Scatter plot
C) Bar chart
D) Line chart

4. In experimentation, how does data augmentation contribute to improving model accuracy?

A) It improves the interpretability of the model by providing additional insights into the data.
B) It has no impact on model accuracy and is primarily used for data visualization purposes.
C) It helps in increasing the size of the dataset, leading to better generalization of the model.
D) It reduces the complexity of the model, making it easier to train and evaluate.

5. Which of the following best describes the role of machine learning in handling multimodal data?

A) To reduce the amount of data needed for accurate predictions.
B) To eliminate the need for human intervention in data analysis.
C) To enable models to learn from and interpret diverse data types.
D) To focus on textual data analysis.

Solutions: