Why always-on, secure edge AI is scaling
summary
Argues that edge AI must be always-on low-latency and running on-device for security and privacy, not tethered to the cloud, and that this enables new hardware like smart glasses and neural sensors on the arm which are already being controlled in prototype demos. Claims these on-device stacks reduce latency and data exposure, scale across consumer devices, and places Arm IP at the center of future edge-AI platforms.
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