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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Generative AI Concepts | - Generative models
|
| Multimodal AI Systems | - Cross-modal learning
|
| NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Responsible and Trustworthy AI | - Bias and safety considerations - Ethical AI principles |
| Core AI and Machine Learning Fundamentals | - Machine learning basics
|
NVIDIA Generative AI Multimodal Sample Questions:
Which technique is commonly used to speed up AI model training and inference on hardware accelerators?
- A. Dropout
- B. Quantization
- C. Model enlargement
- D. Data augmentation
Correct Answer: B 🗳️
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Which of the following best describes the purpose of GAN (Generative Adversarial Networks)?
- A. To optimize search algorithms for faster data retrieval.
- B. To produce new data that is similar to the training data.
- C. To optimize decision-making processes based on historical data.
- D. To classify and categorize data based on patterns and features.
Correct Answer: B 🗳️
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In the transformer architecture, what is the purpose of positional encoding?
- A. To remove redundant information from the input sequence.
- B. To add information about the order of each token in the input sequence.
- C. To encode the semantic meaning of each token in the input sequence.
- D. To encode the importance of each token in the input sequence.
Correct Answer: B 🗳️
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What does 'modality alignment' refer to?
- A. The process of integrating diverse data types such as text, images, audio, time series, and geospatial information.
- B. Addressing challenges related to missing or incomplete information across different modalities.
- C. Aligning different modalities within multimodal data to ensure meaningful connections and associations.
- D. The integration of pretrained models to perform custom tasks involving different types of data.
Correct Answer: C 🗳️
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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 optimize the training process.
- C. To generate new data based on the training set.
- D. To distinguish between real and generated data.
Correct Answer: D 🗳️
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