十月 20, 2022 — Posted by the TensorFlow teamWe’ve started planning the future of TensorFlow! In this article, we’d like to share our vision.We open-sourced TensorFlow nearly seven years ago, on November 9, 2015. Since then, thanks to thousands of open-source contributors and our incredible community of Google Developer Experts, community organizers, researchers, and educators around the globe, TensorFlow has co…
Posted by the TensorFlow team
We’ve started planning the future of TensorFlow! In this article, we’d like to share our vision.
We open-sourced TensorFlow nearly seven years ago, on November 9, 2015. Since then, thanks to thousands of open-source contributors and our incredible community of Google Developer Experts, community organizers, researchers, and educators around the globe, TensorFlow has come to define its category.
Today, TensorFlow is the most-used machine learning platform, adopted by millions of developers. It’s the 3rd most-starred software repository on GitHub (right behind Vue and React) and the most-downloaded machine learning package on PyPI. It has brought machine learning to the mobile ecosystem: TFLite now runs on four billion devices (maybe on yours, too!). TensorFlow has also brought machine learning to the Web: TensorFlow.js is now downloaded 170 thousand times weekly.
Across Google's product lineup, TensorFlow powers virtually all production machine learning, from Search, GMail, YouTube, Maps, Play, Ads, Photos, and many more. Beyond Google, at other Alphabet companies, TensorFlow and Keras enable the machine intelligence in Waymo's self-driving cars.
In the broader industry, TensorFlow powers machine learning systems at thousands of companies, including most of the largest machine learning users in the world – Apple, ByteDance, Netflix, Tencent, Twitter, and countless more. And in the research world, every month, Google Scholar is indexing over 3,000 new scientific publications that mention TensorFlow or Keras.
Today, our user base and developer ecosystem are larger than ever, and growing!
We see the growth of TensorFlow not just as an achievement to celebrate, but as an opportunity to go further and deliver more value for the machine learning community.
Our goal is to provide the best machine learning platform on the planet. Software that will become a new superpower in the toolbox of every developer. Software that will turn machine learning from a niche craft into an industry as mature as web development.
To achieve this, we listen to the needs of our users, anticipate new industry trends, iterate on our APIs, and work to make it increasingly easy for you to innovate at scale. In the same way that TensorFlow originally helped the rise of deep learning, we want to continue to facilitate the evolution of machine learning by giving you the platform that lets you push the boundaries of what's possible. Machine learning is evolving rapidly, and so is TensorFlow.
Today, we're excited to announce we've started working on the next iteration of TensorFlow that will enable the next decade of machine learning development. We are building on TensorFlow's class-leading capabilities, and focusing on four pillars.
We want TensorFlow to serve as a bedrock foundation for the machine learning industry to build upon. We see API stability as our most important feature. As an engineer who relies on TensorFlow as part of their product, as a builder of a TensorFlow ecosystem package, you should be able to upgrade to the latest TensorFlow version and immediately start benefiting from its new features and performance improvements – without fear that your existing codebase might break. As such, we commit to full backwards compatibility from TensorFlow 2 to the next version – your TensorFlow 2 code will run as-is. There will be no conversion script to run, no manual changes to apply.
We plan to release a preview of the new TensorFlow capabilities in Q2 2023 and will release the production version later in the year. We will publish regular updates on our progress in the meantime. You can follow our progress via the TensorFlow blog, and on the TensorFlow YouTube channel.
We want to hear from you! For questions or feedback, please reach out via the TensorFlow forum.
十月 20, 2022 — Posted by the TensorFlow teamWe’ve started planning the future of TensorFlow! In this article, we’d like to share our vision.We open-sourced TensorFlow nearly seven years ago, on November 9, 2015. Since then, thanks to thousands of open-source contributors and our incredible community of Google Developer Experts, community organizers, researchers, and educators around the globe, TensorFlow has co…