Posted by the TensorFlow team TensorFlow 2.17 has been released! Highlights of this release (and 2.16) include CUDA update, upcoming Numpy 2.0, and more. For the full release notes, please click here. Note: Release updates on the new multi-backend Keras will be published on keras.io, starting with Keras 3.0. For…
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 for ML inference and remain the default target for TensorFlow Lite. Consequently, improving CPU…
Posted by the TensorFlow team TensorFlow 2.16 has been released! Highlights of this release (and 2.15) include Clang as default compiler for building TensorFlow CPU wheels on Windows, Keras 3 as default version, support for Python 3.12, and much more! For the full release note, please click here. Note: Release…
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 relationships can be as important to understanding an object as its own attributes viewed…
Posted by the TensorFlow team We are releasing a hot-fix for an installation issue affecting the TensorFlow installation process. The TensorFlow 2.15.0 Python package was released such that it requested tensorrt-related packages that cannot be found unless the user installs them beforehand or provides additional installation flags. This dependency affected…
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 excited to announce that we doubled floating-point inference performance in TensorFlow Lite’s XNNPack…
Posted by the TensorFlow team TensorFlow 2.15 has been released! Highlights of this release (and 2.14) include a much simpler installation method for NVIDIA CUDA libraries for Linux, oneDNN CPU performance optimizations for Windows x64 and x86, full availability of tf.function types, an upgrade to Clang 17.0.1, and much more! For…
Posted by Sharbani Roy – Senior Director, Product Management, Google We're back with the third annual Women in Machine Learning Symposium on December 7, 2023! Join us virtually from 9:30 am to 1:00 pm PT for an immersive and insightful set of deep dives for every level of Machine Learning experience. The Women in…
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’ listening preferences and intent at that point in time. We base current recommendations on previous…
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 Lite, we demonstrated how to train a reinforcement learning (RL) agent…