Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?
A . A more complex model
B . Guaranteed availability of enough space
C . Increase in data bandwidth consumption
D . Reduction in latency
Answer: D
Explanation:
Latency is the time delay between a request and a response. Latency can affect the performance and user experience of an application, especially when real-time or near-real-time responses are required. Deploying a deep learning model as an embedded model on edge devices can reduce latency, as the model can run locally on the device without relying on network connectivity or cloud servers. Edge devices are devices that are located at the edge of a network, such as smartphones, tablets, laptops, sensors, cameras, or drones.
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