In embedded vision applications, doing AI inference at the edge is often required in order to meet performance and latency demands. But, AI inference requires massive computing power, which can exceed our overall power budget. In this episode of Chalk Talk, Amelia Dalton talks to Avery Williams of Microchip about using FPGAs to get the machine vision performance you need, without blowing your power, form factor, and thermal requirements.

Click here for more information about Microsemi / Microchip PolarFire FPGA Video & Imaging Kit