Posted by Josh Gordon for the TensorFlow team. Dear readers, The TensorFlow blog has moved to https://blog.tensorflow.org. Please visit us there in the future. Thank you to our readers, and to our many guest authors who have created an incredible collection of content representing a diverse body of work. Thanks also to Medium for a great couple of years. Although we’ve decided to move our blog, articles from the global TensorFlow community — including students, researchers, and companies large and small — will remain an important part of it. In the future, new articles will be published on htt ..read more

Guest post by Aakanksha Chowdhery, Software Engineer Why does “Yo Google” not work with Google Assistant? After all, it’s only one word different from the phrase “Ok Google”. It’s because Google Assistant is listening for two specific words — or Wake Words. Wake Words are critical to the design of low-power machine learning to process data with a computationally inexpensive model to “wake up” the device for full processing. Audio wake words, such as “Ok Google”, are widely used to wake up AI assistant devices before they process speech using more computationally expensive machine learning mode ..read more

Whether you’re en route to TensorFlow World or you’re unable to make it, learn more below about our new demo experience and explore new GitHub code repos. Be sure to follow #MissionToTensorFlowWorld on Twitter to see this experience in action! Celebrating the 50th anniversary of the Apollo 11 mission, the first manned mission to land on the Moon, Mission to TensorFlow World is TensorFlow’s latest space game experience that leverages the entire product ecosystem: TensorFlow Core, TensorFlow.js, TensorFlow Lite, and TensorFlow Extended (TFX) to control a spacecraft traveling through space. Each ..read more

Posted by Daniel Smilkov, Sandeep Gupta, and Vishy Tirumalashetty TensorFlow.js is an open-source library that lets you define, train, and run machine learning models in Javascript. The library has empowered a new set of developers from the extensive JavaScript community to build and deploy machine learning models and enabled new classes of on-device computation. TensorFlow.js runs in all major browsers, server-side in Node.js, and as of recently, in WeChat and React Native providing hybrid-apps access to ML without having to leave the JS ecosystem. Today, we are excited to bring a new way for ..read more

Earlier this year, we announced TensorFlow 2.0 in alpha at the TensorFlow Dev Summit. Today, we’re delighted to announce that the final release of TensorFlow 2.0 is now available! Learn how to install it here. TensorFlow 2.0 is driven by the community telling us they want an easy-to-use platform that is both flexible and powerful, and which supports deployment to any platform. TensorFlow 2.0 provides a comprehensive ecosystem of tools for developers, enterprises, and researchers who want to push the state-of-the-art in machine learning and build scalable ML-powered applications. https://medium ..read more

A Guest Post by Rodolfo Bonnin from the Mercado Libre Applied Machine Learning team Introduction Mercado Libre is the leading marketplace platform in Latin America, reaching millions of users selling and buying tens of millions of different items a day. From a shipping perspective, one of the most important pieces of information for an item is dimensions and weight since they are used for predicting costs and forecasting the occupancy of the fulfillment centers. As a user-driven marketplace, this information is not always available, and we have found that we can optimize our pipeline by predic ..read more

Guest post by Keith Chan and Vincent Zhang from OliveX Engineering team Introduction OliveX is a Hong Kong-based company focused on fitness-related software, serving more than 2 million users since we first launched in 2018. Many of our users are elderly and our Baduanjin app helps them practice Baduanjin while minimizing the possibility of injury. To achieve that, we utilize the latest artificial intelligence technology in our app to automatically detect Baduanjin practicing moves and provide corresponding feedback to our users. Goals and requirements Baduanjin is a popular exercise that cons ..read more

Posted by Kevin Haas, Zhitao Li, and Robert Crowe on behalf of the TFX team TensorFlow Extended (TFX) is a platform for creating production-ready ML pipelines. TFX was created by Google and provides the backbone of Google’s ML services and applications, and we’ve been open sourcing TFX for everyone who needs to create production ML pipelines. TFX can be extended and customized in several ways, including developing new components and including them in your pipeline. A TFX pipeline is a series of TFX components, each of which performs a separate task, which are sequenced as a directed acyclic gr ..read more