Posted by Alan Kelly, Software Engineer
We are excited to announce that XNNPack’s Fully Connected and Convolution 2D operators now support dynamic range quantization. XNNPack is TensorFlow Lite’s CPU backend and CPUs deliver the widest reach fo…
Posted by Dustin Zelle – Software Engineer, Research and Arno Eigenwillig – Software Engineer, CoreML
This article is also shared on the Google Research Blog
Objects and their relationships are ubiquitous in the world around us, and rel…
Posted by Marat Dukhan and Frank Barchard, Software Engineers
CPUs deliver the widest reach for ML inference and remain the default target for TensorFlow Lite. Consequently, improving CPU inference performance is a top priority, and we are exci…
Posted by Surya Kanoria, Joseph Cauteruccio, Federico Tomasi, Kamil Ciosek, Matteo Rinaldi, and Zhenwen Dai – Spotify
Introduction
Many of our music recommendation problems involve providing users with ordered sets of items that satisfy users’…
Posted by Wei Wei, Developer Advocate
In our previous blog posts Building a board game app with TensorFlow: a new TensorFlow Lite reference app and Building a reinforcement learning agent with JAX, and deploying it on Android with TensorFlow Li…