NCA-GENM Question 130
Select 3A company plans to deploy a generative AI multimodal model for processing both text and image data. The model requires high computational power for training and real-time inferencing. Which combination of system components would best meet their needs?
- A
NVIDIA GPUs with Tensor Cores optimized for AI workloads
- B
High-speed NVMe SSDs for faster data processing and storage
- C
A standard CPU-only server designed for general-purpose computing
- D
A large memory pool (RAM) to handle multimodal data processing
- E
An integrated development environment (IDE) like Jupyter Notebook for training
Show answer and explanation
Correct answers: A, B, D
Explanation
Deploying a generative AI multimodal model requires a combination of hardware components that can handle the high computational and data processing demands. NVIDIA GPUs with Tensor Cores are critical for AI workloads, high-speed NVMe SSDs reduce I/O bottlenecks, and a large memory pool ensures smooth handling of multimodal data. A standard CPU-only setup or the use of an IDE is insufficient for meeting these performance needs.
- A. Correct.
NVIDIA GPUs with Tensor Cores are specifically designed to handle the computational demands of AI workloads, including generative AI multimodal models. They provide the necessary performance for both training and inference tasks.
- B. Correct.
High-speed NVMe SSDs ensure that large datasets, such as images and text, can be accessed quickly, reducing latency during training and inferencing.
- C. Incorrect.
While a standard CPU-only server can handle some workloads, it lacks the computational power needed for training and inferencing large-scale generative AI models efficiently.
- D. Correct.
A large memory pool is essential for handling multimodal data (e.g., text and images) during processing, especially when dealing with large datasets or batch operations.
- E. Incorrect.
While an IDE like Jupyter Notebook is useful for development and experimentation, it is not a system component required to meet the performance needs for deploying a multimodal generative AI model.