NVIDIA : NCA-GENM Questions & Answers
Updated: Oct 24, 2026
No. of Questions: 58 Questions & Answers with Testing Engine
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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Multimodal Data | 15% | - Data preprocessing, fusion, and representation - Multimodal model architectures and integration - Characteristics of text, image, and audio data |
| Topic 2: Core Machine Learning and AI Knowledge | 20% | - Neural network architectures relevant to multimodal systems - Generative AI principles and techniques - Fundamental concepts of machine learning and deep learning |
| Topic 3: Data Analysis and Visualization | 10% | - Visualization techniques for model behavior and results - Analyzing multimodal datasets and outputs - Interpretation of generative AI outputs |
| Topic 4: Performance Optimization | 10% | - Scalability and deployment considerations - Hardware acceleration with NVIDIA platforms - Model efficiency and inference optimization |
| Topic 5: Trustworthy AI | 5% | - Reliability, fairness, and safety in generative systems - Ethical considerations and responsible use - Robustness and error mitigation |
| Topic 6: Software Development and Engineering | 15% | - Development workflows for generative AI applications - Libraries, frameworks, and tools for multimodal AI - Best practices for building and maintaining systems |
| Topic 7: Experimentation | 25% | - Model training, fine-tuning, and evaluation - Experiment design and methodology - Metrics and validation strategies for generative models |
NVIDIA Generative AI Multimodal Sample Questions:
How does CLIP understand the content of both text and images?
- A. By converting text and images into a frequency domain for comparison.
- B. By translating images into text and comparing them with the prompt.
- C. Through a database of predefined images with their descriptions.
- D. Using contrastive learning to match images with text descriptions.
Correct Answer: D 🗳️
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In a Generative Adversarial Network (GAN), what is the role of the discriminator?
- A. To calculate the loss function and update the generator.
- B. To generate new data based on the training set.
- C. To optimize the training process.
- D. To distinguish between real and generated data.
Correct Answer: D 🗳️
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What role does 'late fusion' play in multimodal machine learning?
- A. It refers to the process of combining multiple modalities at the decision level.
- B. It refers to the process of combining multiple modalities at the training stage.
- C. It refers to the process of combining multiple modalities at the feature level.
- D. It refers to the process of combining multiple modalities at the preprocessing stage.
Correct Answer: A 🗳️
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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.
Correct Answer: C 🗳️
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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. Pie chart
- B. Histogram chart
- C. Bar chart
- D. Line chart
Correct Answer: B 🗳️
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