InfoQ Homepage Google Content on InfoQ
-
Android Architecture Components 1.0: Lifecycle, LiveData, ViewModel and Room
Google has made available Android Architecture Components 1.0, a collection of libraries to design “robust, testable, and maintainable apps.” The current components are Lifecycle, LiveData, ViewModel and Room with others on the way.
-
Kotlin Use for Android Apps is Growing, Getting More Google Support
In the six months since Google announced official support for Kotlin as a first-class language for Android development, Kotlin usage has more than doubled, writes Google product manager James Lau, and more than 17% of Android Studio 3.0 projects now use Kotlin.
-
Microsoft, Google, and Mozilla Team Up for Web Documentation
In a coordinated announcement, three major browser vendors have agreed to consolidate their individual web API reference documentation into Mozilla's MDN and have formed an advisory group to guide future efforts. The groups will start using MDN as a single point of truth for web platform documentation and reference.
-
Google Aims to Demonstrate Quantum Supremacy with a 50-Qubit Processor
In a paper published in Nature, Google has revealed its plans to demonstrate that quantum computers can perform a computational task beyond the capability of a classical computer, a claim known as quantum supremacy. Key in Google’s plan is building a 50-qubit processors to solve quantum sampling problems.
-
Google Releases Android Instant Apps SDK 1.1
A few months after its introduction at Google I/O 2017, the Android Instant Apps SDK reaches version 1.1, bringing configuration APKs for binary size optimization and a new API to keep user context when transitioning to an installed app from an instant app.
-
Google Announces Firestore, a Document Database
Google has announced Cloud Firestore, a document database for mobile, web and server applications.
-
Google Open Sources Abseil, a Collection of C++ and Python Utilities
Google has made available a number of C++ libraries they use internally for many of their projects. Python ones are to follow soon.
-
ARCore is Google’s Second Take on Augmented Reality
After launching Project Tango a few years ago, Google has announced a new augmented reality (AR) initiative, ARCore, which aims to bring AR to millions of Android devices.
-
Go 1.9 Introduces Type Aliases, Improves Runtime and Tooling
The biggest change in recently released Go 1.9 is improved support for gradual code repair through the use of type alias declarations. Go 1.9 also improves the garbage collector and the compiler.
-
Google Researcher Invented New Technology to Bring Neural Networks to Mobile Devices
Recently, many companies released applications that use deep neural networks. For applications that should run without internet access, must be fast and responsible, or in which privacy is a concern, using networks on servers is not possible. Google researcher Sujith Ravis invented a novel way to train two neural networks, of which one efficient network can be used with mobile applications.
-
Android 8.0 Oreo Is Here. Developers Are Recommended to Test Their Apps
Google has released the final version of Android 8.0 Oreo. The source code was published to AOSP and system images were made available for supported Nexus and Pixel devices. Android 8.0 comes with several changes that can affect how existing applications function.
-
Overview of Changes in Tensorflow Version 1.3
Although it has only been a month since the release of version 1.2.1, there have been many changes to the software in version 1.3. Developers can find an extensive release report on the Github page of Tensorflow. This article will list the most important changes developers have to know about before and after upgrading to Tensorflow v1.3.
-
Researchers Improve State of the Art in Image Recognition Using Data Set with 300 Million Images
Researchers improved the state of the art results on several benchmarks with models trained on a generated data set with 300 million images instead of the 1 million normally used. To test what happens with more train data, Google created an internal dataset of 300 million images. They labelled the data automatically in a noisy way. The conclusion is that more training data indeed helps.
-
Google Released Facets: A Visualisation Tool for Big Data
Google open-sourced Facets: a data visualisation tool to explore data for machine learning scientists. Facets aim is to make big data set understandable and interpretable. Facets wants to be the visualisation tool researchers use to find nuances and insights in large data sets.
-
Google Uses Machine Learning to Identify Intrusive Android Apps
Google uses a clustering algorithm to automatically analyze Android apps and detect which ones can be considered intrusive, write Google security engineers Martin Pelikan, Giles Hogben, and Ulfar Erlingsson.