Generative AI's impact is growing, but true assistance requires it to run on personal devices. The challenge lies in embedding complex AI onto power-constrained edge devices for private, all-day use. This requires solving performance gaps, hardware fragmentation, and user trust issues. Google introduces Coral NPU, a full-stack platform designed for private, efficient edge AI devices. It offers an AI-first hardware architecture built for ultra-low-power, always-on AI, minimizing battery drain on wearables. Coral NPU reverses traditional chip design by prioritizing the ML matrix engine for efficient on-device inference. The architecture uses RISC-V compliant IP blocks for minimal power consumption, reaching 512 GOPS at a few milliwatts. It features an open and extensible design with a scalar core, vector execution unit, and a matrix execution unit. Coral NPU provides a unified developer experience with seamless integration with modern compilers and ML frameworks. The platform is optimized for both encoder-based architectures and small transformer models, aiming to bring LLMs to wearables. Target applications include contextual awareness, audio and image processing, and user interaction, all with hardware-enforced privacy. Coral NPU is building an ecosystem through partnerships, like with Synaptics, to create open standards for intelligent devices.