Generative AI has fundamentally reshaped our expectations of technology. We've seen the power of large-scale cloud-based models to create, reason and assist in incredible ways. However, the next great technological leap isn't just about making cloud models bigger; it's about embedding their intelligence directly into our immediate, personal environment. For AI to be truly assistive — proactively helping us navigate our day, translating conversations in real-time, or understanding our physical context — it must run on the devices we wear and carry. This presents a core challenge: embedding ambient AI onto battery-constrained edge devices, freeing them from the cloud to enable truly private, all-day assistive experiences.
To move from the cloud to personal devices, we must solve three critical problems:
The performance gap: Complex, state-of-the-art machine learning (ML) models demand more compute, far exceeding the limited power, thermal, and memory budgets of an edge device.
Complex, state-of-the-art machine learning (ML) models demand more compute, far exceeding the limited power, thermal, and memory budgets of an edge device. The fragmentation tax: Compiling and optimizing ML models for a diverse landscape of proprietary processors is difficult and costly, hindering consistent performance across devices.
Compiling and optimizing ML models for a diverse landscape of proprietary processors is difficult and costly, hindering consistent performance across devices. The user trust deficit: To be truly helpful, personal AI must prioritize the privacy and security of personal data and context.
Today we introduce Coral NPU, a full-stack platform that builds on our original work from Coral to provide hardware designers and ML developers with the tools needed to build the next generation of private, efficient edge AI devices. Co-designed in partnership with Google Research and Google DeepMind, Coral NPU is an AI-first hardware architecture built to enable the next generation of ultra-low-power, always-on edge AI. It offers a unified developer experience, making it easier to deploy applications like ambient sensing. It's specifically designed to enable all-day AI on wearable devices while minimizing battery usage and being configurable for higher performance use cases. We’ve released our documentation and tools so that developers and designers can start building today.