Free NVIDIA NCA-GENM Exam Dumps Questions & Answers

Assume you need to implement a multimodal pipeline to diagnose brain cancer type using MRI scans and their corresponding radiology reports. What do you need to include in the ablation study?

• A.Directly combining MRI scans and radiology reports into a single input stream without preprocessing or modality-specific adjustments.
• B.Training a deep learning model using the images in the dataset to find outliers and enhancing the quality of MRI scans using image processing techniques.
• C.More advanced natural language processing techniques to interpret radiology reports, ignoring the MRI scans' diagnostic value.
• D.Implementing separate unimodal pipelines for each modality to ensure the data is informative and the model design is accurate.

What are some methods to overcome limited throughput between CPU and GPU?

• A.Upgrade the GPU to a higher-end model.
• B.Using techniques like memory pooling.
• C.Increase the clock speed of the CPU.
• D.Increase the number of CPU cores.

You are conducting an experiment to evaluate the performance of different AI models. What is the purpose of AI model evaluation?

• A.To study the impact of AI models on human behavior.
• B.To analyze the cost-effectiveness of AI model development.
• C.To determine the best AI model architecture.
• D.To determine the ethical implications of AI model usage.

What does mixed-precision training refer to?

• A.Training a model using multiple precision levels, such as using both single-precision and double- precision floating-point numbers.
• B.Training a model using different types of data, such as text, images, audio, time series, and geospatial information.
• C.Training a model using incomplete or missing information from different modalities.
• D.Training a model using diverse data types while addressing challenges related to missing or incomplete information.

Which of the following best describes the purpose of GAN (Generative Adversarial Networks)?

• A.To optimize decision-making processes based on historical data.
• B.To produce new data that is similar to the training data.
• C.To optimize search algorithms for faster data retrieval.
• D.To classify and categorize data based on patterns and features.