August 11, 2020 —
A guest post by Mohamed Nour Abouelseoud, and Anton Kachatkou at Arm
We are excited to introduce a weight clustering API, proposed and contributed by Arm, to the TensorFlow Model Optimization Toolkit.
August 10, 2020 —
Posted by Andrea Skolik, Volkswagen AG and Leiden University
In early March, Google released TensorFlow Quantum (TFQ) together with the University of Waterloo and Volkswagen AG. TensorFlow Quantum is a software framework for quantum machine learning (QML) which allows researchers to jointly use functionality from Cirq and TensorFlow. Both Cirq and TFQ are aimed at simulating noisy intermediate-sc…
August 05, 2020 —
Posted by Josh Gordon, Developer Advocate
A new HarvardX TinyML course on edX.orgProf. Vijay Janapa Reddi of Harvard, the TensorFlow Lite Micro team, and the edX online learning platform are sharing a series of short TinyML courses this fall that you can observe for free, or sign up to take and receive a certificate. In this article, I’ll share a bit about TinyML, what you can do with it, and the …
August 03, 2020 —
Posted by Jonah Kohn and Pavithra Vijay, Software Engineers at Google
TensorFlow Cloud is a python package that provides APIs for a seamless transition from debugging and training your TensorFlow code in a local environment to distributed training in Google Cloud. It simplifies the process of training models on the cloud into a single, simple function call, requiring minimal setup and almost zero …
July 29, 2020 —
Posted by Pankaj Kanwar, Peter Brandt, and Zongwei Zhou from the TensorFlow Team
MLPerf, the industry standard for measuring machine learning performance, has released the latest benchmark results from the MLPerf Training v0.7 round. We’re happy to share that Google’s submissions demonstrate leading top-line performance (fastest time to reach target quality), with the ability to scale up to 4,000+…
July 27, 2020 —
Posted by Josh Gordon for the TensorFlow team
TensorFlow 2.3 has been released! The focus of this release is on new tools to make it easier for you to load and preprocess data, and to solve input-pipeline bottlenecks, whether you’re working on one machine, or many.
July 24, 2020 —
Posted by Marat Dukhan, Google Research
Leveraging the CPU for ML inference yields the widest reach across the space of edge devices. Consequently, improving neural network inference performance on CPUs has been among the top requests to the TensorFlow Lite team. We listened and are excited to bring you, on average, 2.3X faster floating-point inference through the integration of the XNNPACK libra…
July 20, 2020 —
Posted by Jocelyn Becker, Program Manager, TensorFlow Certificate
July 14, 2020 — Posted by Pohung Chen, Creative Technologist, Google Partner Innovation
July 13, 2020 —
Posted by Miguel de Andrés-Clavera, Product Manager, Google PI
In this post, I’d like to share with you a demo we built for (and had planned to show at) Google I/O this year with TensorFlow Lite. I wish we had the opportunity to meet in person, but I hope you find this article interesting nonetheless!
PixelopolisPixelopolis is an interactive installation that showcases self-driving miniature cars…
July 10, 2020 — Posted by Vivek Rathod and Jonathan Huang, Google Research
July 01, 2020 —
Posted by Ashwin Murthy, Software Engineer, TensorFlow team @ Google
OverviewEfficiency and performance are critical for edge deployments. TensorFlow Lite achieves this by means of fusing and optimizing a series of more granular TensorFlow operations (which themselves are composed of composite operations, like LSTM) into a single executable TensorFlow Lite unit.
Many users have asked us for more g…
June 29, 2020 —
Posted byTulsee Doshi, Andrew Zaldivar
As billions of people around the world continue to use products or services with AI at their core, it becomes more important than ever that AI is deployed responsibly: preserving trust and putting each individual user’s well-being first. It has always been our highest priority to build products that are inclusive, ethical, and accountable to our communities,…
June 26, 2020 — Posted by Khanh LeViet, TensorFlow Developer Advocate
June 24, 2020 — Posted by Shuang Song and David Marn
June 18, 2020 — A guest post by Niranjan Hasabnis, Mohammad Ashraf Bhuiyan, Wei Wang, AG Ramesh at Intel
June 17, 2020 —
Posted by Luiz Gustavo Martins, Beat Gfeller and Christian Frank
Pitch is an attribute of musical tones (along with duration, intensity and timbre) that allows you to describe a note as “high” or “low”. Pitch is quantified by frequency, measured in Hertz (Hz), where one Hz corresponds to one cycle per second. The higher the frequency, the higher the note.
June 09, 2020 —
A guest post by Michael Gielda of Antmicro
Every day more and more software developers are exploring the worlds of machine learning, embedded systems, and the Internet of Things. Perhaps one of the most exciting advances to come out of the most recent innovations in these fields is the incorporation of ML at the edge and into smaller and smaller devices - often referred to as TinyML.
June 08, 2020 —
Guest author Hannes Hapke, Senior Data Scientist, SAP Concur Labs. Edited by Robert Crowe on behalf of the TFX team
Transformer models and the concepts of transfer learning in Natural Language Processing have opened up new opportunities around tasks like sentiment analysis, entity extractions, and question-answer problems.
BERT models allow data scientists to stand on the shoulders of giants. Pr…
May 29, 2020 —
Posted by Soonson Kwon, Biswajeet Mallik, and Siddhant Agarwal, Program Managers
TensorFlow User Groups (or TFUGs, for short) are a community of curious, passionate machine learning developers and researchers around the world. TFUGs play an important role in helping developers share their knowledge and experience in machine learning, and the latest TensorFlow updates. Google and the TensorFlow tea…
