This implementation is specifically optimized for the Apple Neural Engine (ANE), the energy-efficient and high-throughput engine for ML inference on Apple silicon. It will help developers minimize the impact of their ML inference workloads on app memory, app responsiveness, and device battery life. Increasing the adoption of on-device ML deployment will also benefit user privacy, since data for inference workloads remains on-device, not on the server.