You are adding a new on-device ML feature to a consumer device. The feature improves personalization, but the device has tight RAM and flash limits, and the model must coexist with other system workloads.
How do you handle resource constraints (RAM, flash) when adding features?
You are adding a new on-device ML feature to a consumer device. The feature improves personalization, but the device has tight RAM and flash limits, and the model must coexist with other system workloads.
How do you handle resource constraints (RAM, flash) when adding features?