Japanese Softbank announced that the humanoid Pepper robot will support Google's Android operating system. The Android Pepper robots will go on sale starting in July for developers. Ahead of the launch, starting today SoftBank Robotics is offering 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.

Robots and artificial intelligence have come an extended manner since a Roomba entered your home to vacuum your floor and Siri gave you recommendation on the simplest Italian restaurants in your parents' neighborhood. According to a 2013 University of Oxford study, half of yankee jobs can be automatic among ensuing 20 years. The study identified transportation, logistics and body jobs as the most liable to automation. Others assert it is only a matter of your time before robots replace academics, travel agents, interpreters and a host of other professions. Their predictions of what this would appear as if usually focus on 2 scenarios: a dystopia wherever humans now not have jobs or incomes, leading to increased financial gain difference and social upheaval, or a utopia where governments offer incomes to their voters, who can then be in a position to lead additional productive, creative and entrepreneurial lives.

This week Google held its I/O developer conference and presented its self-learning Artificial Intelligence engine, the Google Assistant. Google is following Amazon's example by releasing a smart speaker that will monitor the sound environment in order to receive messages from the user and help them quickly finishing tasks. Google Home is a bit like Amazons Echo. Since it is connected to the Google Assistant, it will learn your preferences and will make suggestions based on them. In the simultaneously released messaging App Allo, the Google Assistant will monitor your way of answering to questions and will learn in which situations you give which answers to suggest you the answer you could give before you start typing.

These last few months have presented some complicated security stories, and this week we took steps to untangle them. We looked at the many, many ways in which the FBI hacks people, revelations of which have been trickling out for decades. And we broke down just how hackers were able to lift 81 million from a Bangladeshi bank in a matter of hours--well short of their billion-dollar goal, but still a hefty sum, cleverly obtained. In the world of software, Google has finally offered end-to-end encryption in its messaging products. It's Allo and Duo, new chat and video apps that use the stalwart end-to-end encryption known as Signal. On Allo, end-to-end kicks in only when you're in incognito mode, which we guess is better than nothing.

Google is announcing a new messaging app today. It's called Allo and its main feature is a Google assistant that's built right in. Google says it'll be available later this summer -- for free -- on both iOS and Android. Allo (pronounced like "Aloe" and not like "'allo, guv'nor!") is a mobile-only app that you might think is meant to replace Google's other messaging app, Hangouts. Allo is explicitly meant to be a fresh start for Google's new communication's division (which also runs Hangouts and Project Fi). "It's really liberating to start from scratch sometimes," says Erik Kay, director of engineering, communications products.

In my last post, I discussed how human agents and human assisted virtual agents (HAVAs) can work together when machine learning and artificial intelligence are applied to customer care systems. Now let's take it a step further. In machine learning you often need to compare or "match" things. For example, when you are looking for the right answer in a database, you compare the question to the possible answers stored there. If you want to sort intents into buckets (so-called clustering) you need to compare them with each other and see how similar they are.

An early Google employee tests different apps in his recently remodeled San Francisco home. The home's automation system can be accessed by smart phone; the front door has an automated video doorbell. Facebook founder and chief Mark Zuckerberg created the world's largest media owner, with 1.6 billion users, but it does not produce content. DIGITAL technology has quickly knocked some of the world's biggest businesses off their perches and will soon make more radical changes to our everyday lives. Tech experts have been surprised by the speed that consumers have flocked to global online platforms such as Uber and Airbnb, and believe it's only the beginning -- with artificial intelligence and internet-connected homes among the next big growth areas.

Spring XD addresses the new demands of big data and real-time data pipelining, but it sets a foundation for much more. Data Science, Machine Learning and Predictive Analytics are becoming more common across industries. The most successful and innovative companies are currently exploring live data streaming scenarios instead of the traditional batch collection, storage, ETL-like transformations and offline analytical solutions. Two main reasons are demanding this change. First, some data is really only valuable in the moment it's connected--as the half-life of its business value degrades quickly.

Businesspeople need to demand more from machine learning so they can connect data scientists' work to relevant action. This requires basic machine learning literacy -- what kinds of problems can machine learning solve, and how to talk about those problems with data scientists. Linear regression and feature selection are two such foundational topics. Linear regression is a powerful technique for predicting numbers from other data. Imagine you have an imperative to predict basketball scores from game statistics, and you miraculously know absolutely nothing about basketball. The fact that a hoop is involved is news to you.

Global services juggernaut Accenture is partnering with IT and business process automation specialist IPsoft to build a new Accenture practice dedicated to bringing the power of artificial intelligence (AI) to global enterprises. Earlier this week, the partners announced the creation of an Accenture Amelia practice built around IPsoft's Amelia cognitive agent, an AI that emulates human intelligence and can communicate with natural language. IPsoft has positioned Amelia as "your first digital employee" -- one that can take on a wide range of service desk roles. "This cutting-edge new practice is going to give our clients more artificial intelligence firepower by accelerating their ability to apply AI to significantly improve their operations and create new growth opportunities for their business," says Paul Daugherty, CTO, Accenture. "One of the ways Accenture is going to do this is by using IPsoft's Amelia Platform to develop artificial intelligence strategies, solutions and consulting services for our clients in the banking, insurance and travel industries."