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A startup company has implemented a new facial recognition system for a banking application for mobile devices. The application is intended to learn at run-time on the device to determine if the user should be granted access. It also sends feedback over the Internet to the application developers. The application deployment resulted in continuous restarts of the mobile devices. Which of the following is the most likely cause of the failure?
Correct Answer: D
\ Facial recognition applications involvecomplex computational tasks, including: * Feature Extraction- Identifying unique facial landmarks. * Model Training and Updates- Continuous learning and adaptation of user data. * Image Processing- Handling real-time image recognition under various lighting and angles. In this scenario, themobile device is experiencing continuous restarts, which suggestsa resource overloadcaused by excessive processing demands. * Mobile devices have limited computational power. * Unlike servers, mobile devices lack powerful GPUs/TPUs required for deep learning models. * On-device learning is computationally expensive. * The model is likely performingreal-time learning, which can overwhelm the CPU and RAM. * Continuous feedback transmission may cause overheating. * If the system is running multiple processes-training, inference, and network communication-it can overload system resources and cause crashes. * (A) The feedback requires a physical connection and cannot be sent over the Internet.#(Incorrect) * Feedback transmission over the internet is common for cloud-based AI services.This is not the cause of the issue. * (B) Mobile operating systems cannot process machine learning algorithms.#(Incorrect) * Many mobile applications use ML models efficiently. The problem here is thehigh computational intensity, not the OS's ability to run ML algorithms. * (C) The size of the application is consuming too much of the phone's storage capacity.#(Incorrect) * Storage issues typically result in installation failures or lag,not device restarts.The issue here isprocessing overload, not storage space. * AI-based applications require significant computational power."The computational intensity of AI- based applications can pose a challenge when deployed on resource-limited devices." * Edge devices may struggle with processing complex ML workloads."Deploying AI models on mobile or edge devices requires optimization, as these devices have limited processing capabilities compared to cloud environments." Why is Option D Correct?Why Other Options are Incorrect?References from ISTQB Certified Tester AI Testing Study GuideThus,option D is the correct answer, as thecomputational demands of the facial recognition system are too high for the mobile hardware to handle, causing continuous restarts.