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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

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

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

Question 2

You are developing a GenAI-Multimodal system that uses data from various sources. What is one potential issue you need to consider in relation to bias in data?

A. Bias in data is not a concern for AI systems as they are designed to be neutral and objective.
B. The data used to train the AI system may not be representative of the population it is intended to serve.
C. Bias in data can only be addressed after the AI system has been deployed.
D. Bias in data is irrelevant as long as the AI system produces accurate predictions.

Question 3

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

A. It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
B. It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
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.

Question 4

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

A. It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
B. It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
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.

Question 5

In multimodal machine learning, what does 'early fusion' refer to?

A. Ignoring certain modalities and only using one modality for analysis and prediction.
B. Integrating different modalities at the beginning of the model pipeline.
C. Implementing the model in the early stages of development of the ML solution.
D. Training separate models for each modality and then combining their predictions.

Solutions: