When we first heard about Google's Android Things platform in 2016 (and even earlier when it was Project Brillo) the idea was that it could bring additional intelligent capabilities to all kinds of electronics. However, in the years since AI helpers like Google Assistant have moved control and smarts to the cloud, while the smartest devices in your home are still just... speakers and displays. Now Google has announced that it's "refocusing" Android Things on those two types of devices. Over the past year, Google has worked closely with partners to create consumer products powered by Android Things with the Google Assistant built-in. Given the successes we have seen with our partners in smart speakers and smart displays, we are refocusing Android Things as a platform for OEM partners to build devices in those categories moving forward. Therefore, support for production System on Modules (SoMs) based on NXP, Qualcomm, and MediaTek hardware will not be made available through the public developer platform at this time.

At first glance, Google's new Home Hub looks like any other smart display featuring the company's Assistant platform. It features both voice and touch inputs, giving consumers the option to manually control their smart home, watch YouTube videos and see appointments for the week ahead. However, underneath the hood, Google has done things a little differently. Unlike Lenovo, JBL and LG, Google's Home Hub doesn't run a stripped-down version of Android -- in fact, it's closer to a Chromecast. The revelation comes by way of Ars Technica's Ron Amadeo.

Tensor Processing Unit (TPU), an application specific integrated circuit, designed by Google for accelerating machine learning workloads, is going to be available at the edge. These tailor-made chips complement Cloud TPUs by inferencing machine learning models deployed at the edge. Google has also announced Cloud IoT Edge, an edge computing platform that extends Google Cloud's data processing and machine learning to edge devices. Google is the latest entrant into the edge computing market. The key competitors of Google Cloud – Amazon and Microsoft – have a comprehensive edge computing strategy.

Google is bringing its internet of things (IoT) data processing capabilities to edge environments to accommodate enterprises that are unable to rely on cloud for latency or regulatory purposes. In this e-guide, we give you the top 10 key facts you need to know about the General Data Protection Regulation according to privacy lawyer and KuppingerCole analyst, Karsten Kinast. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

Google is bringing its internet of things (IoT) data processing capabilities to edge environments to accommodate enterprises that are unable to rely on cloud for latency or regulatory purposes. See how your organisation can accelerate a move off-premise with the help of PaaS. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

This project explores how to apply Machine Learning to IoT. In more details, as IoT platform, we will use Android Things and as Machine Learning engine we will use Google TensorFlow. Nowadays, Android Things is in a stable version named Android Things 1.0 and ready to be used in the production systems. As you may know already Raspberry Pi is one of the supported platforms for development and prototyping with Android Things 1.0. This tutorial using Android Things 1.0 with Raspberry Pi, anyway, you can easily move to other supported platforms without changing the code. During this tutorial about how to apply Machine Learning to IoT, the IoT platform is Android Things Raspberry Pi.

From smart speakers like the Google Home and Amazon Echo to the Roomba autonomous vacuum cleaner, there are a growing number of smart A.I.s and robots we can call on to perform different tasks in our homes. A new collaboration between innovation studio Deeplocal and Google's Internet of Things (IoT) framework Android Things wants to add another robotic helping hand to the mix -- and we mean that quite literally. Called HandBot, it's a D.I.Y. robotic hand which can recognize your hand gestures and mimic them back to you, or compete against you in a classic game of rock-paper-scissors. To do this, it uses some smart machine learning-based image recognition, courtesy of an built-in camera that feeds it images of your movement. "We teamed up with Deeplocal to build a series of demos to help inspire and show what developers can build by harnessing the power and potential of Android through the ease of the Android Things platform," Melissa Daniels, a program manager at Android Things, told Digital Trends.

The Internet of Things is going to get noisier. Qualcomm is launching its Home Hub platform with support for Android Things and Google Assistant. At CES 2018, the big tech trade show in Las Vegas, Qualcomm unveiled its purpose-built platforms and system modules for home devices that are enabled with the artificial intelligence of Google Assistant. The Home Hub platform is based on the Qualcomm SDA624 and SDA212 system on chips (SoCs). The idea is to make it easy for Qualcomm's customers to create devices for the Internet of Things, which makes everyday objects smart and connected.

Google served up a bevy of announcements, technologies and goodies for developers, but it also highlighted a much larger strategy where the search giant still organizes the world's information, but also begins creating systems that'll add context, delight you and potentially provide more insights. Artificial intelligence and machine learning is Google's competitive advantage and will be embedded everywhere. Google CEO Sundar Pichai talked AI non-stop during his Google I/O keynote and he's rearchitecting the company to be "AI-first." The extent of Google's AI reach is everywhere from Google Photos to Google Assistant to Google Cloud Platform to damn near every other product or service the search giant has. Google's AI efforts will even tap into human resources as it pivots to target job searches.

TensorFlow is an open source software library for machine learning, developed by Google and currently used in many of their projects. An easy, fast, and fun way to get started with TensorFlow is to build an image classifier: an offline and simplified alternative to Google's Cloud Vision API where our Android device can detect and recognize objects from an image (or directly from the camera input). In this article, we will create an Android app that can recognize video-game characters. An official TensorFlow Android image classifier sample is available on the main GitHub repository. However, if you want to build it, it will take you some time, as you'll need to install the NDK, Bazel, and the total build time with Android Studio will take around 40 minutes.