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Rethink Your IoT Architecture Using AI at the Edge
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Rethink Your IoT Architecture Using AI at the Edge

Thanks to the proliferation of IoT devices, enterprise data volumes are exploding. Traditionally, the sensitive data IoT devices gather has largely been stored in the cloud. But given the latency between data centers and end-users, that arrangement is becoming untenable. When dealing with pressing operational needs, organizations can struggle to rely on remote servers to process their data. Cloud data security is a further complication. Given these concerns, it’s no wonder many enterprises are looking to the edge. That is, they need to process data locally to support real-time decision-making. In essence, they need faster processing than the cloud allows.

The next-generation of employees doesn’t like to wait around. They want those devices to make decisions sooner rather than later. But the need to process data with minimal latency isn’t just a matter of impatience. In the case of autonomous vehicles, as well as many medical and industrial applications, the need for IoT systems to make automated decisions as quickly as possible is a necessity.

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