Free NCA-GENM Mock Exam – Practice Online Confidently

You are working on a multimodal AI project that involves integrating image data with textual descriptions for a product recommendation system. Under the supervision of a senior team member, you are tasked with writing a Python script to preprocess the image data and textual data before they are fed into the model. After running your preprocessing script, the model’s performance on the test set is significantly lower than expected. What is the most likely issue with your preprocessing script?

You are tasked with improving a multimodal neural network used for predicting patient outcomes based on medical imaging, lab results, and clinical notes. The current model struggles with learning complex features due to the depth of the network. Which benefit of residual connections would most directly address this problem?

You are tasked with fine-tuning an ASR model for deployment in a noisy industrial environment. Which approach would most effectively improve the model's performance in this scenario?

You are responsible for maintaining a multimodal generative AI system that processes customer service requests by analyzing both text and voice inputs. The system must categorize the requests, generate appropriate responses, and then forward them to the relevant department. However, the system is struggling with the accurate categorization of requests when the voice data contains background noise. What is the best approach to improve the system’s performance in this scenario?

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?