NCA-GENM NCA - Generative AI Multimodal Free Demo Questions – Try Before You Buy

Question 1

After fine-tuning a large language model (LLM) for generating legal documents, what is the most
effective way to assess whether the fine-tuning has improved the model’s performance for this specific
task?

A

Measuring the speed at which the fine-tuned model generates text, regardless of content accuracy

B

Evaluating the model’s output against a benchmark dataset of legal documents that it has never

seen before. C

Comparing the fine-tuned model’s output with that of a non-fine-tuned model on random text generation tasks.

D

Testing the fine-tuned model on a set of common, non-legal text generation tasks to measure

general improvement.

Correct Answer: B

Explanation:

Evaluating the model's output against a benchmark dataset of unseen legal documents ensures that the

fine-tuning improves performance for the specific legal task, making it a reliable method of assessment.

Question 2

To enhance the trustworthiness of an AI system used for healthcare diagnostics, which approach involving NVIDIA technologies is most appropriate?

A

Using NVIDIA GPUs to increase the speed of diagnosis without focusing on data security

B

Prioritizing the collection of large amounts of patient data over maintaining patient privacy.

C

Implementing NVIDIA Clara’s privacy-preserving federated learning to train the AI on sensitive patient data across multiple institutions without sharing the data

D

Training the AI solely on data from a single medical institution to streamline the process.

Correct Answer: C

Explanation:

NVIDIA Clara’s privacy-preserving federated learning allows AI models to be trained on sensitive data across multiple institutions without directly sharing patient data, enhancing both privacy and performance.

Question 3

You are deploying a multimodal AI system that integrates text, images, and voice commands to assist in
autonomous driving. The system must make real-time decisions based on input from various sensors in
different environments. Which strategy best ensures that the AI system remains reliable and trustworthy
in diverse driving conditions?

A

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

B

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

C

Using a generic AI model without customizing it for different environments.

D

Relying solely on data collected from one geographical region to train the AI system.

Correct Answer: D

Explanation:

NVIDIA's DRIVE platform provides robust simulation environments that allow for thorough testing and validation across different real-world scenarios, ensuring reliability in diverse conditions.

Demo NVIDIA NCA-GENM Exam Questions

After fine-tuning a large language model (LLM) for generating legal documents, what is the most
effective way to assess whether the fine-tuning has improved the model’s performance for this specific
task?

Measuring the speed at which the fine-tuned model generates text, regardless of content accuracy

Evaluating the model’s output against a benchmark dataset of legal documents that it has never

Comparing the fine-tuned model’s output with that of a non-fine-tuned model on random text generation tasks.

Testing the fine-tuned model on a set of common, non-legal text generation tasks to measure

general improvement.

Correct Answer: B

Evaluating the model's output against a benchmark dataset of unseen legal documents ensures that the

fine-tuning improves performance for the specific legal task, making it a reliable method of assessment.

To enhance the trustworthiness of an AI system used for healthcare diagnostics, which approach involving NVIDIA technologies is most appropriate?

Using NVIDIA GPUs to increase the speed of diagnosis without focusing on data security

Prioritizing the collection of large amounts of patient data over maintaining patient privacy.

Implementing NVIDIA Clara’s privacy-preserving federated learning to train the AI on sensitive patient data across multiple institutions without sharing the data

Training the AI solely on data from a single medical institution to streamline the process.

Correct Answer: C

NVIDIA Clara’s privacy-preserving federated learning allows AI models to be trained on sensitive data across multiple institutions without directly sharing patient data, enhancing both privacy and performance.

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

Using a generic AI model without customizing it for different environments.

Relying solely on data collected from one geographical region to train the AI system.

Correct Answer: D

NVIDIA's DRIVE platform provides robust simulation environments that allow for thorough testing and validation across different real-world scenarios, ensuring reliability in diverse conditions.

Demo Practice Mode

Demo NVIDIA NCA-GENM Exam Questions

After fine-tuning a large language model (LLM) for generating legal documents, what is the mosteffective way to assess whether the fine-tuning has improved the model’s performance for this specifictask?

Measuring the speed at which the fine-tuned model generates text, regardless of content accuracy

Evaluating the model’s output against a benchmark dataset of legal documents that it has never

Comparing the fine-tuned model’s output with that of a non-fine-tuned model on random text generation tasks.

Testing the fine-tuned model on a set of common, non-legal text generation tasks to measure

general improvement.

Correct Answer: B

Evaluating the model's output against a benchmark dataset of unseen legal documents ensures that the

fine-tuning improves performance for the specific legal task, making it a reliable method of assessment.

To enhance the trustworthiness of an AI system used for healthcare diagnostics, which approach involving NVIDIA technologies is most appropriate?

Using NVIDIA GPUs to increase the speed of diagnosis without focusing on data security

Prioritizing the collection of large amounts of patient data over maintaining patient privacy.

Implementing NVIDIA Clara’s privacy-preserving federated learning to train the AI on sensitive patient data across multiple institutions without sharing the data

Training the AI solely on data from a single medical institution to streamline the process.

Correct Answer: C

NVIDIA Clara’s privacy-preserving federated learning allows AI models to be trained on sensitive data across multiple institutions without directly sharing patient data, enhancing both privacy and performance.

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

Prioritizing the speed of decision-making over the accuracy of sensor interpretation

Using a generic AI model without customizing it for different environments.

Relying solely on data collected from one geographical region to train the AI system.

Correct Answer: D

NVIDIA's DRIVE platform provides robust simulation environments that allow for thorough testing and validation across different real-world scenarios, ensuring reliability in diverse conditions.

Demo Practice Mode

After fine-tuning a large language model (LLM) for generating legal documents, what is the most
effective way to assess whether the fine-tuning has improved the model’s performance for this specific
task?