Google Professional Machine Learning Engineer
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A toy manufacturer is experiencing a significant surge in demand and is looking to implement an ML model to minimize the time quality control inspectors spend on identifying product defects. The factory's environment is characterized by unreliable Wi-Fi connectivity, and there is an urgent need for rapid defect detection to maintain production efficiency. Given these constraints, which of the following models would be the most suitable for deployment on edge devices within the factory to ensure fast and efficient defect detection without relying on constant Wi-Fi connectivity? (Choose one correct option)
Explanation:
Correct Option:
B. AutoML Vision Edge mobile-low-latency-1 model: This model is specifically designed for edge device deployment, offering the low latency required for rapid defect detection in environments with unreliable Wi-Fi. Its efficiency and speed align perfectly with the manufacturer's need for quick and reliable performance.
Incorrect Options:
A. AutoML Vision Edge mobile-versatile-1 model: While this model offers versatility, it may not be optimized for the low-latency performance critical in this scenario. C. AutoML Vision model: This model typically requires a stable cloud connection, making it unsuitable for the factory's unreliable Wi-Fi conditions. D. AutoML Vision Edge mobile-high-accuracy-1 model: Although this model focuses on high accuracy, it may not meet the low-latency requirements necessary for the rapid defect detection needed here.