Efficient Sequence Modeling for On-Device ML

Posted by Arun Kandoor, Software Engineer, Google Research

The increasing demand for machine learning (ML) model inference on-device (for mobile devices, tablets, etc.) is driven by the rise of compute-intensive applications, the need to keep certain data on device for privacy and security reasons, and the desire to provide services when a network connection may not be available. However, on-device inference introduces a myriad of challenges, ranging from modeling to platform support requirements. These challenges relate to how different architectures …

machine learning ml modeling nlp on-device learning open source