Question 1

You are experimenting with different AI model architectures for a multimodal project that integrates text, image, and audio data. One model architecture shows high accuracy on the training set but fails to generalize well to the validation set. What is the most appropriate next step to evaluate and improve this model?

Options :

A : Switch to a more complex model architecture with additional layers.

B : Increase the number of epochs to further train the model.

C : Reduce the size of the training set to decrease overfitting.

D : Use cross-validation to better evaluate the model’s generalization.

Answer: D

Question 2

A tech company is deploying a multimodal AI system that combines video surveillance, audio analysis, and motion sensors to enhance security in a large industrial facility. The system works well during the day but struggles at night when there is limited lighting and more background noise. Additionally, the system consumes a significant amount of energy, leading to higher operational costs. What is the most likely cause of the system's poor performance and high energy consumption at night?

Options :

A : The video model is not optimized for low-light conditions.

B : The multimodal fusion strategy is not adapting to different environmental conditions effectively.

C : The AI models are running continuously at full capacity without energy optimization.

D : The system’s audio model is overfitting to daytime noise patterns.

Answer: B

Question 3

You are managing a production-level conversational AI application deployed with Helm in a Kubernetes cluster. You need to perform a rolling update to the ASR service without causing downtime. What is the best strategy to achieve this?

Options :

A : Disable readiness probes during the update to prevent pods from being marked as unavailable.

B : Configure the maxUnavailable and maxSurge parameters in the Helm chart to control the rolling update process.

C : ) Increase the number of replicas before starting the update to ensure availability.

D : Deploy the updated ASR service as a new Helm release, then manually switch traffic to the new service.

Answer: B

Question 4

In developing a generative AI system, how can you balance the need for data privacy with the importance of obtaining data consent to ensure the ethical use of personal information?

Options :

A : Prioritizing the AI system’s performance over user privacy concerns.

B : Ensuring that all data collection processes are transparent and that explicit consent is obtained from users before using their data.

C : Collecting as much data as possible without informing users to improve AI accuracy.

D : Using default settings that automatically opt users into data sharing without their explicit knowledge.

Answer: B

Question 5

Your company is developing a multimodal AI application that combines text, image, and audio inputs. As part of the rapid development process, you are tasked with integrating a text-to-image model from HuggingFace and experimenting with it to see if it meets your needs. How can you most efficiently pull in and start experimenting with a text-to-image model from HuggingFace using the Transformers API?

Options :

A : Utilize the transformers.Pipeline with the text-to-image task and load the model directly from the HuggingFace repository.

B : Download the model-s code and modify it to suit the text-to-image task within your application.

C : Use the AutoModelForVision class to load the text-to-image model and begin testing.

D : Use the AutoModelForImageAndText class to load the model and start experimenting.

Answer: A

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