Almost a year after it came out in the US, Facebook is releasing its facial recognition-powered photo app Moments in Europe. Except the new version won't actually include any facial recognition technology, thanks to the company's long-running fight with the Irish data protection commissioner over whether the technology is actually legal in the EU. Launched in June, Moments is Facebook's answer to dedicated photo management applications like Google Photos and Apple's Photos. The app bundles pictures together by the event they're taken at, and applies facial recognition technology to identify who's in each picture. Facebook takes the offering a step further than Apple or Google, by leveraging its social network: once you've created your "moments", you can share them with other people at the same event, to ensure that they have the photos of them, and you have the photos of you.

In a collaboration between Japan's Softbank Robotics and French-based Aldebaran Robotics, Pepper was officially put on the market for domestic use in June of 2015. Priced at about 1,600 with 200 in monthly data and insurance fees, the first thousand models available for launch sold out in under a minute. The company has stated that they aim to keep Pepper affordable, comparing the cost of the robot to that of a pet dog in Japan. Outside of personal ownership, the android has been used to assist Japanese citizens in banks and shops, including the promotion of Nescafe coffee machine sales. And in a limited run, large-scale experiment, Softbank opened a phone shop staffed exclusively by Pepper robots.

The future is closer than we think, said Kevin Ho -- and it's not going to be terrifying at all, he claims. Life today would be unimaginable for people from a few decades or a few centuries ago, explained Ho, President of Huawei's handset line, speaking Wednesday morning at the CES Asia 2016 event in Shanghai, China. Just imagine trying to explain ships and trains and even airplanes, all of which would have been terrifying to someone from 10,000 years ago. Then imagine bringing that same person to the modern world. "What if coming to today's society, somebody showed you a black box -- a smartphone -- with video phone functionality? What would people from ancient society think knowing that we can fly?" he asked the crowd.

There are some adverse conditions, such as heat and fog, and the urban roads can be heavily trafficked. But by and large, it's a very car-friendly place: The streets are relatively well-paved and marked, and they aren't as clogged with unpredictable bicycle, pedestrian, or rickshaw traffic as those of many other big cities around the world. Oh, and the government is an absolute monarchy that can more or less impose its will on the populace.

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.

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.

In March, a computer achieved what many thought impossible when it won a best of five series against world-class go champion Lee Sedol. The victory by the DeepMind computer was the most significant milestone in artificial intelligence (AI) since Deep Blue beat chess Grandmaster Garry Kasparov in 1997, and once again sparked many predictable headlines about humans being knocked off our IQ perch. The question is, what do such human versus computer matches tell us about AI? Is it the harbinger of a machine-led future or are computers just very good at playing board games? To see how this might play out, we first need to look to the past. Despite being extremely bad at playing board games as complicated as chess and go for decades, there was almost a sense of inevitability to computers eventually surpassing the abilities of their human creators in this area.

Last week, the White House released a report chronicling the Obama administration's concerns over Big Data and artificial intelligence. Many prominent thinkers and scientists have come out recently with warnings about the dangers of unchecked artificial intelligence. However, the A.I. the White House report refers to is not of the Terminator ilk -- rather, Obama has concerns over algorithmic artificial intelligence operating without human oversight. The report, "Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights," catalogs the growing sphere of influence represented by Big Data in society, including employment, higher education, and criminal justice. "As data-driven services become increasingly ubiquitous, and as we come to depend on them more and more, we must address concerns about intentional or implicit biases that may emerge from both the data and the algorithms used as well as the impact they may have on the user and society. Questions of transparency arise when companies, institutions, and organizations use algorithmic systems and automated processes to inform decisions that affect our lives, such as whether or not we qualify for credit or employment opportunities, or which financial, employment and housing advertisements we see." "If feedback loops are not thoughtfully constructed, a predictive algorithmic system built in this manner could perpetuate policing practices that are not sufficiently attuned to community needs and potentially impede efforts to improve community trust and safety. For example, machine learning systems that take into account past arrests could indicate that certain communities require more policing and oversight, when in fact the communities may be changing for the better over time."

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.

In a conference on Monday, U.S. Deputy Defense Secretary Bob Work outlined a key component of modern warfare strategy called Third Offset. The military intends to take advantage of cutting-edge R&D to incorporate AI-human teams to overcome an enemy's network. At the 2016 Global Strategy forum on Monday, Mr. Work noted that products with potential military applications are fast-tracked to enter the global market. "R&D is going down in the public sector, but up in the private sector. Most things that have to do with AI [artificial intelligence] and autonomy are happening in the private sector. And so all competitors are going to have access to it, it's going to be a world of fast-followers. You're going to have an instance where you're not going to have a lasting advantage."