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NVIDIA NCA-GENM Exam Syllabus Topics:

NVIDIA Generative AI Multimodal Sample Questions:

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

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

2. You are working with a large dataset and want to visualize the distribution of a continuous variable. Which type of data visualization would be most appropriate?

A) Bar chart
B) Line chart
C) Histogram chart
D) Pie chart

3. What does 'modality alignment' refer to?

A) Addressing challenges related to missing or incomplete information across different modalities.
B) The integration of pretrained models to perform custom tasks involving different types of data.
C) Aligning different modalities within multimodal data to ensure meaningful connections and associations.
D) The process of integrating diverse data types such as text, images, audio, time series, and geospatial information.

4. How does the batch size influence VRAM consumption during inference with ML models on GPUs?

A) Decreasing the batch size reduces VRAM consumption.
B) Increasing or decreasing the batch size has the same impact on VRAM consumption.
C) Increasing the batch size reduces VRAM consumption because more data can be processed in parallel.
D) The batch size has no impact on VRAM consumption during inference.

5. 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 can only be addressed after the AI system has been deployed.
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 is irrelevant as long as the AI system produces accurate predictions.
D) Bias in data is not a concern for AI systems as they are designed to be neutral and objective.

Solutions: