Question 1

You are testing the effectiveness of a multimodal AI model designed to predict stock market trends using financial news articles, social media sentiment, and historical stock prices. The model performs well during periods of market stability but shows significant accuracy drops during market volatility. What approach should you take to improve the model's performance during volatile periods?

Options :

A : Reduce the complexity of the model to avoid overfitting to stable market conditions.

B : Incorporate additional data sources such as real-time trading volumes and macroeconomic indicators to provide more context during volatile periods.

C : Focus training exclusively on periods of market stability to ensure consistent accuracy.

D : Apply data augmentation techniques to artificially increase the size of the dataset during stable periods.

Answer: B

Question 2

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 3

You are designing a multimodal AI system for a smart city project that monitors traffic, air quality, and public safety using video feeds, sensor data, and social media analysis. The system needs to operate continuously with high accuracy while minimizing energy consumption across multiple edge devices. Which strategy should you prioritize to achieve the best balance between energy efficiency and system performance?

Options :

A : Implement model pruning to reduce the size of the neural networks used in the system.

B : Increase the frame rate of video feeds to capture more detailed data.

C : Deploy separate models for each data modality (video, sensor, social media) without integration.

D : Use high-resolution sensors to improve the accuracy of air quality measurements.

Answer: A

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

You are deploying a multimodal AI system that combines text, images, and audio to assist in emergency response decision-making. The system will be used by various agencies across different countries. Which approach will most effectively ensure that the AI system provides reliable and unbiased recommendations in diverse scenarios?

Options :

A : Using a single, high-quality dataset from a leading country with advanced emergency response systems.

B : Training the model exclusively on data from regions where it will be deployed.

C : Incorporating real-time feedback from users in different regions to continuously adapt the model.

D : Implementing strict usage guidelines to limit the system’s decision-making to only certain types of emergencies.

Answer: C

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