In Edge AI, real-time decision-making involves processing data locally on devices near the data source, enabling immediate responses without relying on cloud connectivity. This reduces latency and enhances privacy. In contrast, Embedded AI integrates AI capabilities directly into devices, often with limited computational resources. While both aim for quick decision-making, Edge AI typically handles more complex tasks due to its proximity to data sources, whereas Embedded AI focuses on specific, predefined functions. For a deeper understanding, consider enrolling in an embedded system and AI course.
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