There's plenty of lip service paid to the need to mobile-enable the enterprise, but actually making that happen is a little more complicated. That's where PowWow Mobile hopes to help. The startup on Wednesday launched SmartUX, a platform that taps machine learning to help companies turn their legacy Web and Windows apps into mobile-optimized ones without writing any code. Along the way, PowWow promises that it can save months of development time and more than 70 percent of development costs. The platform's core tool is SmartUX Studio.

Some knowledge workers fear they are next in line to be made obsolete by artificial intelligence (AI). Automation, which impacted manufacturing and blue collar jobs, is beginning to encroach on areas previously considered strictly within the realm of human intelligence and judgement -- advisory services for financial services firms, fraud identification, disease diagnosis, editing and structured article creation, and language translation. When first introduced, sophisticated tax software appeared to threaten the jobs of income tax preparers. But it turned out to only be effective for relatively uncomplicated returns. According to the Washington Post, tax preparers -- most using intelligent software to do their work -- completed the same number of returns in 2011 as they did a decade earlier.

Imagine workers who don't pay taxes, with no IRS worries. Or who don't get paid for overtime. Now, imagine a robot on the job. "Robotics will be a revolution for our economy and in the way we think and act," said Randy Bateman, an economist who is the CEO and president of Balcones Investment Research. Bateman, appearing recently on a futuristic panel discussion titled "Will a Robot Take Your Job?" at the libertarian Cato Institute in Washington, expects the robotics industry to spearhead the next great transformative stage of our workforce.

Amid surging investment in artificial intelligence over the past few years and continuing concern about the implications of the technology, the White House announced on Tuesday that it intends to hold a series of workshops and form an inter-agency working group to examine the benefits and risks of AI. In a blog post, Ed Felten, Deputy US Chief Technology Officer, framed the issue in a way that excludes speculative scenarios presenting AI as a threat to humanity, a concern raised by the likes of Stephen Hawking and Elon Musk. While worries about runaway malevolent AI are often raised in public discussions of the technology, real AI research is more mundane, as in Google's effort to improve the conversational capabilities of its software by feeding it romance novels. "Today's AI is confined to narrow, specific tasks, and isn't anything like the general, adaptable intelligence that humans exhibit," said Felten. "Despite this, AI's influence on the world is growing. The rate of progress we have seen will have broad implications for fields ranging from healthcare to image- and voice-recognition."

Unexpected convergent consequences…this is what happens when eight different exponential technologies all explode onto the scene at once. This post (the third of seven) is a look at virtual and augmented reality. Future posts will look at other tech areas. And be sure to read the first two posts if you haven't already: When the World Is Wired: The Magic of the Internet of Everything Where Artificial Intelligence Is Now and What's Just Around the Corner An expert might be reasonably good at predicting the growth of a single exponential technology (e.g., the Internet of Things), but try to predict the future when AI, robotics, VR, synthetic biology, and computation are all doubling, morphing and recombining… You have a very exciting (read: unpredictable) future. This year at my Abundance 360 Summit I decided to explore this concept in sessions I called Convergence Catalyzers.

Machines have already started their march towards artificial intelligence. Deep Learning and Neural Networks are probably the hottest topics in machine learning research today. Companies like Google, Facebook and Baidu are heavily investing into this field of research. Researchers believe that machine learning will highly influence human life in near future. Human tasks will be automated using robots with negligible margin of error. I'm sure many of us would never have imagined such gigantic power of machine learning.

Sentiment analysis is a powerful example of how machine learning can help developers build better products with unique features. In short, sentiment analysis is the automated process of understanding if text written in a natural language (English, Spanish, etc.) is positive, neutral, or negative about a given subject. Nowadays, we have many instances where people express opinions and sentiment: tweets, comments, reviews, articles, chats, emails and more. One popular example is Twitter, where real-time opinions from millions of users are expressed constantly. Companies use sentiment analysis on Twitter to discover insights about their products and services.

Despite gripes about the usefulness of Facebook chatbots, "tens of thousands" of developers are building them, Messenger's head of product Stan Chudnovsky revealed onstage at TechCrunch Disrupt NY. And, 5,000 Shopify merchants are now distributing order confirmations and shipping alerts via Messenger, showing e-commerce companies are eager to reach the app's nearly one billion users. These bots are getting pretty chatty. One of the more recent high-profile chatbots introduced on the Messenger platform, Activision's Call of Duty bot, saw engagement soar to nearly 6 million messaged exchanged between users in its first week of existence. The problem is that if bots get spammy, they could drown out people's friends in Messenger.

This five-fingered robot hand can learn how to perform dexterous manipulation -- like spinning a tube full of coffee beans -- on its own, rather than having humans program its actions.University of Washington Robots today can perform space missions, solve a Rubik's cube, sort hospital medication and even make pancakes. But most can't manage the simple act of grasping a pencil and spinning it around to get a solid grip. Intricate tasks that require dexterous in-hand manipulation -- rolling, pivoting, bending, sensing friction and other things humans do effortlessly with our hands -- have proved notoriously difficult for robots. Now, a University of Washington team of computer scientists and engineers has built a robot hand that can not only perform dexterous manipulation but also learn from its own experience without needing humans to direct it. Their latest results are detailed in a paper to be presented May 17 at the IEEE International Conference on Robotics and Automation.

Neural networks provide the possibility to solve complicated non linear problems. They can be used in various areas such as signal classification, forecasting timeseries and pattern recognition. A neural network is a model inspired by the human brain and consists of multiple connected neurons. For getting a deeper understanding, I recommend checking out Neural Networks and Deep Learning. Within the last years, multiple Javascript frameworks were developed that can help you to create, train and use Neural Networks for different purposes.