When Japanese mobile phone company SoftBank offered 1000 of its emotionally intelligent Pepper robots for the consumer market last summer, the entire run sold out in under a minute. At CES this year, SoftBank announced that IBM would be bringing Watson's artificial intelligence to Pepper, a bid to ready the robot for broad adoption in the home.

SoftBank Robotics Corp. ("SoftBank Robotics") and SoftBank Corp. ("SoftBank") today announced that its humanoid robot'Pepper' will support Google's Android, and that presales of models for developers will begin from July 2016. Ahead of the presales launch, starting today SoftBank Robotics will offer a beta version of'Pepper SDK for Android Studio', a software development kit that enables the development of RoboApps on the Android platform. By making Pepper compatible with Android, Android application developers will be able to utilize their existing knowledge and technologies to develop RoboApps for Pepper. With the high number of Android developers around the world, the possibilities for Pepper RoboApp developers will greatly increase with Android support. SoftBank Robotics will continue to provide its SDK, 'Choregraphe'.

Google has revealed a new personal assistant for around the house that can control, run and organise your entire home using just your voice. The device, a voice-activated speaker called Google Home forms the centre of a Google plan to use artificial intelligence in computing to help give every user "their own individual Google" by becoming personal to them, according to the firm's chief. CEO Sundar Pichai used the keynote presentation at the firm's I/O developer conference in California to reveal new apps, software and a voice activated personal assistant that take advantage of new, more intelligent Google software that is better at understanding context. Mr Pichai said of the new Google Home personal assistant connects to WiFi and can control other connected appliances: "Computing is poised to evolve beyond just phones. It will be about the context. The new, more intelligent software also focuses on understanding context to answer queries and has been built into the existing Google ...

Google used its I/O 2016 event to talk up its work in areas including machine learning and virtual reality, with head Sundar Pichai stating that "we are pushing ourselves really hard so that Google is evolving, and staying ahead of our users". A significant amount of time was dedicated to the growing importance of voice-driven services, with the executive stating that 20 per cent of queries from US mobile users are already made in this way. "Given how differently users are engaging with us, we want to push ourselves and deliver rich information in the context of mobile," he said. Driving this is Google Assistant, which it described as "conversational", and more like a context-aware two way dialogue. This, it said, is enabled by its natural language processing technology – "our ability to do conversational understanding is far ahead of what other assistants can do".

SoftBank Robotics Corp. said Thursday it has expanded opportunities for app developers to use Google's Android platform for its humanoid robot Pepper. It hopes to encourage more programmers to develop apps for the device. An Android-ready Pepper model will go on sale in July, though only for developers, and on Thursday an Android development toolkit was made available for download, Fumihide Tomizawa, SoftBank Robotics chief, told a news conference at the firm's headquarters in Tokyo. Previously, there was a development platform specially designed for Pepper, but it was not based on Android. Tomizawa said the number of developers could increase 100-fold, as there are only several thousand Pepper app designers but hundreds of thousands of Android coders.

Pepper is finally coming to America. SoftBank said today that its chatty humanoid robot, unveiled with great fanfare by the company's founder and CEO Masayoshi Son two years ago, is expected to debut in the North American market later this year. SoftBank also announced that a new developer portal is now available to anyone interested in creating applications for the robot. And tomorrow at Google I/O, SoftBank engineers will take the stage, along with Pepper, to introduce a tool that they hope will entice more developers to build apps for the robot: an Android SDK. "We're so excited to see what the development community can bring on to our platform," Steve Carlin, vice president of marketing and business development for SoftBank Robotics America, told IEEE Spectrum, adding that "ultimately what is going to really power Pepper is the creativity of this community."

Picking the perfect emoji for a text message can be tough – but now SwiftKey has a new keyboard that can do it for you. Called Swiftmoji, this keyboard uses the firms predictive artificial intelligence technology to automatically suggest the right emoji based on what you've typed. SwiftKey, acquired by Microsoft earlier this year, released the keyboard for beta testing in Google Play this week. Although the firm has yet to share any details, the description on Google Play says it will suggest the right emoji and present them to you in one of two ways: 'Emoji Prediction Row', places the suggestions above the keyboard and the other shows you the list in the chat area of your texting application Swiftmoji is a predictive keyboard uses the firms AI technology to automatically suggest the right emoji based on what you've typed. The first, called'Emoji Prediction Row', places the suggestions above the keyboard, which you can then drag into the text box or anywhere else on the screen. And the other shows you the list in the chat area of your texting application.

"Machine learning" will pave the way to delivering better experiences including "how quickly we can put apps on the X1 platform," Comcast EVP and chief technology officer Tony Werner explained here in an introductory overview at the Imagine Park opening session on Monday. He envisioned "a ton of very cool apps," comparing the ability of DOCSIS 3.1 to replace "a backhoe or forklift" in implementing new services for cable operators. "I love Full Duplex," Werner enthused about a symmetrical multi-gigabit project underway at CableLabs and being demoed here by Nokia, before he scooted off stage to support other Comcast executives at the opening of their nearby booth on the INTX show floor. As fellow panelist and visionary Andy Lippman, senior scientist and Associate Director of the Massachusetts Institute of Technology Media Lab, showed his "Ultimate Media" project, Werner quickly noted that, "You don't have all the online sources loving it." Werner cited the prioritization for certain news sources within the MIT algorithm.

Qualcomm (NASDAQ: QCOM) announced a few days ago that its subsidiary Qualcomm Technologies will offer OEMs its first machine learning SDK for running their own neural network models on devices powered by Snapdragon 820 SoCs. The devices include smartphones, cars and drones among many others. With the introduction of the new Snapdragon Neural Processing Engine SDK, we are making it possible for myriad sectors, including mobile, IoT and automotive to harnesses the power of Qualcomm Snapdragon 820 and make high-performance, power efficient on-device deep learning a reality. Qualcomm said in its Q2 earnings call that the company is broadening its presence in "adjacent opportunities," i.e., in adjacent markets where it has growth opportunities. The company has such opportunities in the sectors Brotman mentioned, as presented above in bold.

Qualcomm, Inc. (NASDAQ:QCOM) is bringing neural networks to its Snapdragon 820 chips. The chipmaker has announced that it will be shipping out software development kits later in 2016 giving its chips some new smart features. Qualcomm is making use of its 820 system on a chip's "heterogeneous compute capabilities" with its Qualcomm Snapdragon Neural Processing Engine built atop of the company's Zeroth Machine Intelligence Platform. Developers can use the SDK to turn Qualcomm's chip into a deep learning machine on which to develop and compile neural network models. The potential applications for portable deep learning in mobile devices are inexhaustible.