Fascinating, but there is a grain of truth at the core of this article. In Western culture we have fairy tales, Aesop's fables and the Bible. In Eastern culture, they have Hinduism, Buddhism and their own brand of stories and fables steeped in morality and ethics. However, one must remember that humans are deeply flawed creatures, which doesn't even start to include those who are mentally unbalanced or just plain psychotic. Just look at the news headlines and you will see that crime and unethical behavior has been with us since the dawn of civilization some 13,000 years ago.

"AlphaGo is really more interesting than either Deep Blue or Watson, because the algorithms it uses are potentially more general-purpose," said Nick Bostrom of Oxford University's Future of Humanity Institute. Creating "general" or multi-purpose, rather than "narrow", task-specific intelligence, is the ultimate goal in AI -- something resembling human reasoning based on a variety of inputs, and self-learning from experience. "So, if the machine can do new things when needed, then it has'true' intelligence'," Bostrom's colleague Anders Sandberg told AFP. In the case of Go, Google developers realised a more "human-like" approach would win over brute computing power. AlphaGo uses two sets of "deep neural networks" containing millions of connections similar to neurons in the brain.

I've been reading and thinking about the future a lot recently, and decided to spend a week "nerding out" at Singularity University, to satisfy my curiosity. It was a great event, featuring experts from across the entire spectrum of technology and innovation. In this post I'll share the ideas I've been developing for some time -- based on my own research as well as time at spent at SU -- on how we should think about the future and the myriad opportunities it presents. I am extremely optimistic about our future being a world where powerful technologies solve some of our biggest challenges across a range of industries from medicine to transportation to energy and many others. This will result in a significantly better standard of living for all as well as many remarkable inventions, in the same way that we live significantly better and different lives than our great great grandparents did.

The rainwater collection system, solar panel farm and security robot are already up and running at The Edge building in Amsterdam. The interactive desk is a research project by Arup called "It's All About The Desk." The digital algae canopy is developed by the London-based ecoLogicStudio, who provided the footage. The system of surgically-implanted chips is operate by Epicenter, a hi-tech office block in Stockholm.

It doesn't look like a place to make groundbreaking discoveries that change the trajectory of society. But in these simulated, claustrophobic corridors, Demis Hassabis thinks he can lay the foundations for software that's smart enough to solve humanity's biggest problems. "Our goal's very big," says Hassabis, whose level-headed manner can mask the audacity of his ideas. He leads a team of roughly 200 computer scientists and neuroscientists at Google's DeepMind, the London-based group behind the AlphaGo software that defeated the world champion at Go in a five-game series earlier this month, setting a milestone in computing. It's supposed to be just an early checkpoint in an effort Hassabis describes as the Apollo program of artificial intelligence, aimed at "solving intelligence, and then using that to solve everything else."

The Japan eSports Association, which promotes the competitive playing of video games, is nudging the sector toward professional status. JeSPA uses the term e-sport to refer to video games ranging from shootout arcade games to team-based tournaments set on a virtual pitch. It is hard to put a figure on the number of enthusiasts worldwide, but around 100 million are thought to play regularly and seriously. The tournament wound up with finals in five games on March 12 and 13 in Toyosu, Tokyo. The finale was a round of the fighting game "Guilty Gear Xrd -Sign-," which attracted 350 players and roughly 1,000 spectators, while more than 10,000 people followed it on Dwango's Nico Nico Live website.

Truth is, nobody can stop you from showing your friends all the messages you get on dating sites, especially the creepy PMs women get all the time due to the gender disparity in many services. Maybe you want to ask them what they think of your prospective date based on your conversation or to warn them off talking to this person who's been harassing you on the app for months. But making eavesdropping an actual feature in a dating app is alarming. A lot of people would consider inviting friends to watch a private convo from behind a cloak of invisibility a betrayal of trust and a huge violation of privacy. The app's creator, Alejandro Ponce, told TechCrunch that he believes men would still join his service despite the feature's existence, though, because "boys will be wherever girls are."

Businesses increasingly use machine-learning models to recognize patterns in big data and to implement data-driven decision-making. In this webinar, you will learn how Domino serves as a platform for experimentation and collaboration, and facilitates the creation and distribution of machine-learning models. We will give you an introduction on how to use Plotly--an interactive data visualization tool--to share the results from your models more effectively. We will also show you how to use Plotly's API libraries in Domino Data Lab to build insightful graphs, charts and data visualizations in Python and in R. Chelsea is a core developer of Plotly, the data visualization platform, and plotly.js, the open-source Javascript library. She is also responsible for maintaining Plotly's interactive, browser-based charting libraries and documentation for R and Python.

Under reasonable circumstances, how much money can you expect to lose? The financial statistic value at risk (VaR) seeks to answer this question. Since its development on Wall Street soon after the stock market crash of 1987, VaR has been widely adopted across the financial services industry. Some organizations report the statistic to satisfy regulations, some use it to better understand the risk characteristics of large portfolios, and others compute it before executing trades to help make informed and immediate decisions. For reasons that we will delve into later, reaching an accurate estimate of VaR can be a computationally expensive process.

All of these are concepts aim to make human types of problems computable, whether it be a self-driving car, a health care-providing robot, or a walking and talking assistant robot for the home or office. R&D teams around the world are working to create a whole new world of machines more intelligent than humans. Designing systems as complex as the human brain -- which is still largely a mystery -- is no small task. For example, tomorrow's bleeding edge cars will be the ultimate in efficient system-level design sophistication given the complexity, integration, interdependencies, safety, convenience and comfort required on so many levels. "It fundamentally changes the paradigm and even what we expect of processors to be doing," said Chris Rowen, a Cadence fellow and CTO of the IP Group.