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TL;DR 135 — November 15th, 2018

#AndroidDevSummit

The Android Dev summit happened last week at the Computer History Museum in Mountain View, California. The team celebrated 10 years of Android and shared updates to Kotlin, Jetpack, Android Studio, App Bundles and, of course, talked about Foldables. Click here for all the details and a link to the session videos.

AI Hub and Kubeflow Pipelines

Last week the team introduced both the AI Hub and Kubeflow Pipelines to help make AI simpler, faster, and more useful. AI Hub has plug-and-play ML content, including pipelines, Jupyter notebooks, TensorFlow modules, and more. Kubeflow Pipelines is a new component of Kubeflow that packages ML code just like building an app so that it’s reusable to other users across an organization. For more details on both, head on over to the link.

Cloud Scheduler

Cloud Scheduler is a fully managed cron job service that allows any application to invoke batch, big data, and cloud infrastructure operations. Essentially a modern, managed cron service for automated batch jobs. And it’s now available. A link to the quickstart is on the post.

Containerd in Google Kubernetes Engine

Containerd is an industry-standard container runtime and Docker’s core runtime component. It’s now available in beta on Container-Optimized OS for Kubernetes Engine 1.11. Example commands and a link to the user guide are on the post.

2018 Go User Survey

The 2018 Go user survey is open for responses until November 30th. Please click through the post to share your perspective and help us create the best programming language that fits the needs and desires of the people closest to it: that’s you!

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TL;DR 134 — November 8th, 2018

G Suite Developer Hub

The G Suite Developer Hub is now available. It provides a single view of your projects, helping you create new automation scripts, view shared projects, and check on service statuses. For more details and screenshots, head on over to the post.

Node.js 10 available for App Engine

Node.js 10 is now available in beta on App Engine standard environment and it’s now the default version on the flexible environment. For more about Node.js on App Engine, take a look at the post.

BERT: State-of-the-Art Pre-training for Natural Language Processing

We recently open sourced a new technique for Natural Language Processing pre-training called Bidirectional Encoder Representations from Transformers, or BERT. With it, you can train your own state-of-the-art question answering system in about 30 minutes on a single Cloud TPU, or in a few hours using a single GPU. As usual, the post goes into some depth and has a link to the paper.

AdaNet: Fast and Flexible AutoML with Learning Guarantees

We recently introduced AdaNet, a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on our recent reinforcement learning and evolutionary-based AutoML efforts to be fast and flexible while providing learning guarantees. Definitions, details, and a link to the GitHub are all on the post.

Google at EMNLP 2018

The annual conference on Empirical Methods in Natural Language Processing was held last week in Brussels. Google had a strong presence with several of our researchers presenting on a diverse set of topics, including language identification, segmentation, semantic parsing, and question answering. For links to these papers and the new datasets we shared, head on over to the post.