At Google, we are creating a world-class family of ML tools across all hardware and device types.

Posted by Xi Chen and Xiao Wang, Software Engineers, Google Research Advanced language models (e.g., GPT, GLaM, PaLM and T5) have demonstrated dive...

Posted by Santiago Balseiro, Staff Research Scientist, Google Research, and Associate Professor at Columbia University, and Vahab Mirrokni, Disting...

Posted by Cat Armato, Program Manager, Google This week, the 23rd Annual Conference of the International Speech Communication Association (INTERSPE...

Together, NVIDIA and Google are delighted to announce new milestones and plans to optimize TensorFlow and JAX for the Ampere and more.

Posted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research A long-standing problem in the intersection of computer vision an...

we’re excited to announce the collaboration between TFF and OpenMined - an OSS community dedicated to development of privacy-preserving technologies.

The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.

Startups building ML products and services require production-level infrastructure. TFX provides a framework that can help ML startups as they grow.

Posted by Yi Tay and Mostafa Dehghani, Research Scientists, Google Research, Brain Team Building models that understand and generate natural langua...

The TensorFlow roadmap for 2023 and beyond

Arm is making embedded ML more accessible with Arm Virtual Hardware (AVH). AVH offers a platform to test TFLM models without needing physical hardware

Intel and Google co-architected the TensorFlow PluggableDevice mechanism to enable TensorFlow models on Data Center GPU Flex Series.