Don’t let data drift derail edge compute machine learning models

Diagram showing Ekya’s architecture. Video data flows from a series of cameras into specialized, lightweight inference models and shared resource pools before reaching the edge.

Edge computing has come of age, with deployments enabling many applications that process data from IoT sensors and cameras. In 2017, we identified the symbiotic relationship between edge computing and video analytics in an article, noting that live video analytics is the “killer app” for edge computing. Edge devices come in various shapes and sizes but are inherently resource-constrained relative to

 

 

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