One characteristic that sets Edge AI apart from Embedded AI is connectivity. Devices using Edge AI must be connected in order to communicate with networks or cloud servers for data aggregation, model updates, or further processing. This makes use of cloud resources and allows for real-time decision-making. On the other hand, embedded AI functions autonomously, requiring little to no connectivity and processing all AI functions on the device. Because of its independence, embedded artificial intelligence (AI) is perfect for settings with little to no network connection, guaranteeing reduced latency and improved data privacy. It is essential to comprehend these processes in order to create reliable AI solutions. Take an Embedded System course now to learn more!
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