A Compact Machine Learning Accelerator HAT for your Raspberry Pi

AI for the Edge has been a promising playing field where several players are pushing for. Cloud computing has made it possible to train complex machine learning models for various application, although this seems to be working fine, the performance or the possibility of deploying AI applications on the Edge is enormous. AI on the Edge is expected to help reduces the latency involved in the roundtrip to the cloud, saves the bandwidth and cloud storage costs for enterprises, deploy ML models faster, and build robust, intelligent applications. Generally, Edge devices like the Raspberry Pi, Arduinos, and other embedded boards usually can’t run powerful AI applications. They have limited resources and computing power. Fortunately, this is changing with the introduction of AI Accelerators; modern processors that help assist the edge devices by taking over the complex mathematical calculations needed for running AI models. One of such AI accelerator processor is the Kendryte K210 which has seen deployments on different development […]

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