Posted by the TensorFlow teamTensorFlow 2.20 has been released! For ongoing updates related to the multi-backend Keras, please note that all news and releases, starting with Keras 3.0, are now published directly on keras.io. You can find a complete list of all changes in the full release notes on GitHub.| The TensorFlow Blog
Posted by Alan Kelly, Software EngineerWe 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 for ML inference and remain the default target for TensorFlow Lite. Consequently, improving CPU inference performance is a top priority. We quadrupled inference performance in TensorFlow Lite’s XNNPack backend compared to the single precision baselin...| The TensorFlow Blog
Posted by Marat Dukhan and Frank Barchard, Software Engineers| The TensorFlow Blog
Posted by Wei Wei, Developer Advocate| The TensorFlow Blog
Posted by Alan Kelly, Software EngineerOne of our previous articles, Optimizing TensorFlow Lite Runtime Memory, discusses how TFLite’s memory arena minimizes memory usage by sharing buffers between tensors. This means we can run models on even smaller edge devices. In today’s article, I will describe the performance optimization of the memory arena initialization so that our users get the benefit of low memory usage with little additional overhead.| The TensorFlow Blog
Posted by Angelica Willis and Akib Uddin, Health AI Team, Google ResearchHow researchers at Google are working to expand global access to maternal healthcare with the help of AI| The TensorFlow Blog