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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Core AI and Machine Learning Fundamentals | - Machine learning basics
|
| Topic 2: NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Topic 3: Responsible and Trustworthy AI | - Ethical AI principles - Bias and safety considerations |
| Topic 4: Multimodal AI Systems | - Multimodal model design - Cross-modal learning
|
| Topic 5: Generative AI Concepts | - Generative models
|
NVIDIA Generative AI Multimodal Sample Questions:
1. In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?
A) K-means clustering
B) Generative adversarial network (GAN)
C) Decision tree
D) Support vector machine (SVM)
2. What is a common method to reduce the computational cost of deep learning models during inference?
A) Adding more convolutional filters.
B) Pruning weights or neurons.
C) Increasing the batch size.
D) By replacing activation functions in some neurons with simpler ones.
3. Which of the following tasks can be performed using the transformer LLM encoder model?
A) Speech recognition
B) Generating code
C) Semantic analysis
D) Image generation
4. Which of the following is a component of the Content Authenticity Initiative?
A) Content credential
B) Content validity
C) Ethical AI development
D) Data encryption
5. In the context of multimodal machine learning, what does 'data fusion' refer to?
A) Separating different modalities of data into distinct representations.
B) Combining different modalities of data into a single representation.
C) Removing missing or incomplete information from different modalities.
D) Evaluating the quality of diverse data types in multimodal machine learning.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: B |
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