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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Multimodal AI Systems | - Multimodal model design - Cross-modal learning
|
| Topic 2: Core AI and Machine Learning Fundamentals | - Machine learning basics
|
| Topic 3: NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Topic 4: Responsible and Trustworthy AI | - Bias and safety considerations - Ethical AI principles |
| Topic 5: Generative AI Concepts | - Generative models
|
NVIDIA Generative AI Multimodal Sample Questions:
1. What does 'kernel fusion' refer to in the context of AI model optimization?
A) Combining multiple kernels into a single kernel for faster computation.
B) Optimizing model inference by reducing the number of computations by pruning.
C) Applying multiple layers of kernels to improve model accuracy.
D) Using kernel functions to optimize model hyperparameters.
2. What is the significance of using a U-Net like architecture in denoising diffusion probabilistic models?
A) To detect noisy objects in input images.
B) To segment noisy patches in input images.
C) To generate new images from pure noise.
D) To classify input images as noisy or clean.
3. Which technique involves leveraging pre-trained models to achieve efficient results with less data and computation?
A) State management and composition
B) Transfer learning
C) Prompt engineering
D) Neural network integration
4. In a Generative Adversarial Network (GAN), what is the role of the discriminator?
A) To optimize the training process.
B) To calculate the loss function and update the generator.
C) To generate new data based on the training set.
D) To distinguish between real and generated data.
5. 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) Histogram chart
B) Bar chart
C) Line chart
D) Pie chart
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: A |
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