Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Japan recently announced a major robotics event for next year. The World Robot Summit will feature a series of competitions, talks, and exhibits.

While millions of people fearing a robot run world, it is Americans who should worry the most. A new report has found that 38 percent of US jobs will be replaced by robots and artificial intelligence by the early 2030s. The analysis, by accountancy giant PwC, has also revealed that it is financials service jobs that are at most risk of a robot takeover - 61 percent could be replaced by machines. While millions of people fearing a robot run world – it is Americans that should worry the most. PwC found that 4 in 10 jobs in the US are at risk of being replaced by robots.

This paper introduces a method for efficiently inferring a high-dimensional distributed quantity from a few observations. The quantity of interest (QoI) is approximated in a basis (dictionary) learned from a training set. The coefficients associated with the approximation of the QoI in the basis are determined by minimizing the misfit with the observations. To obtain a probabilistic estimate of the quantity of interest, a Bayesian approach is employed. The QoI is treated as a random field endowed with a hierarchical prior distribution so that closed-form expressions can be obtained for the posterior distribution. The main contribution of the present work lies in the derivation of \emph{a representation basis consistent with the observation chain} used to infer the associated coefficients. The resulting dictionary is then tailored to be both observable by the sensors and accurate in approximating the posterior mean. An algorithm for deriving such an observable dictionary is presented. The method is illustrated with the estimation of the velocity field of an open cavity flow from a handful of wall-mounted point sensors. Comparison with standard estimation approaches relying on Principal Component Analysis and K-SVD dictionaries is provided and illustrates the superior performance of the present approach.

We've been losing the war on cybercrime for some time. Research firm Forrester reports over a billion accounts stolen in 2016 alone, and these data breaches are going up, not down. We are having to wade through more incident data, and people cannot keep up. Could machine learning help solve the problem? For years, researchers hoped that artificial intelligence would produce human-like machines.

AI is one the 2017's big buzzwords. The new technology is exciting and offers a plethora of possibilities that were once reserved solely for our wildest dreams and cinema screens. However, with the advancements in AI also comes fear. People are worried about how many jobs will be lost to artificial intelligence. PwC has released a new study centred on the future of the UK's economy.

The world population is expected to reach 9.7 billion by 2050. China and India, the two largest countries in the world, have populations totalling around one billion. In four years, by 2022, India is predicted to have the largest population in the world, surpassing China. "My best employees are leaving," Daniel told me, "and I can't seem to figure out why." p Daniel (not his real name) was a VP human resource manager at a Fortune 500 company. I asked him whether he had collected any data that could provide him with insights into systematic patterns.

A French and an American astronaut floated outside the International Space Station Friday on a successful spacewalk to upgrade the orbiting outpost for the arrival of future space crews. Outfitted in bulky white spacesuits, helmets and gloves, France's Thomas Pesquet, 39, and American Shane Kimbrough, 49, completed their work right on schedule, after six hours and 34 minutes in the vacuum of space. "Another great example of international collaboration and the work that we can do when we get a great team like this together," said Jessica Meir, a NASA astronaut who coordinated the spacewalk from mission control in Houston. The goal for Friday's outing was to prepare for the installation of the second of two parking spots for space taxis, known as the International Docking Adapters. New crew spaceships, being designed by SpaceX and Boeing, will use them when they begin flying astronauts to the station in the coming years, as early as 2018.

Like other major hyperscale web companies, China's Tencent, which operates a massive network of ad, social, business, and media platforms, is increasingly reliant on two trends to keep pace. The first is not surprising--efficient, scalable cloud computing to serve internal and user demand. The second is more recent and includes a wide breadth of deep learning applications, including the company's own internally developed Mariana platform, which powers many user-facing services. When the company introduced its deep learning platform back in 2014 (at a time when companies like Baidu, Google, and others were expanding their GPU counts for speech and image recognition applications) they noted their main challenges were in providing adequate compute power and parallelism for fast model training. "For example," Mariana's creators explain, "the acoustic model of automatic speech recognition for Chinese and English in Tencent WeChat adopts a deep neural network with more than 50 million parameters, more than 15,000 senones (tied triphone model represented by one output node in a DNN output layer) and tens of billions of samples, so it would take years to train this model by a single CPU server or off-the-shelf GPU."

Seven million years ago, the first ancestors of mankind appeared in Africa and seven million years later, as we speak, mankind's existence is being traced by archaeologists in South Africa, where they believe they are finding several missing links in our history. A history traced back to the first hominid forms. What is a hominid, I hear you say, and when did it exist? Well, way back when scientists believe that the Eurasian and American tectonic plates collided and then settled, creating a massive flat area in Africa, after the Ice Age. This new massive field was flat for hundreds of miles, as far as the eye could see, and the apes that inhabited this land suddenly found there were no trees to climb. This meant that the apes found it hard going thundering over hundreds of miles on their hands and feet, so they started to stand up to make it easier to move over the land. This resulted in a change in the wiring of the brain, which, over thousands of years, led to the early forms of what is now recognized as human. The first link to understanding this chain was the discovery of Lucy. Lucy--named after the Beatles song "Lucy in the Sky with Diamonds"--is the first skeleton that could be pieced together to show how these early human forms appeared on the African plains in the post-Ice Age world. The skeleton was found in the early 1970s in Ethiopia by paleoanthropologist Donald Johanson and is an early example of the hominid australopithecine, dating back to about 3.2 million years ago. The skeleton presents a small skull akin to that of most apes, plus evidence of a walking gait that was bipedal and upright, similar to that of humans and other hominids. This combination supports the view of human evolution that bipedalism preceded an increase in brain size. Since Lucy was found, there have been many other astonishing discoveries in what is now called the "Cradle of Humankind" in South Africa, a Unesco World Heritage site.

Artificial intelligence is impacting areas as disparate as the automotive industry, health care, finance, aerospace and the banking industry, according to a recent report by Frost & Sullivan TechVision. AI has the ability to break down data patterns to create highly detailed simulations and predictions. Frost & Sullivan found that thought-managed interaction with machines is spreading exponentially throughout the business world, regardless of the brand or product, thanks to AI. Technologists' attempts to give AI the ability to function with cognitive behavior is beginning to succeed, the study says. This cognitive ability includes things like self-correction, planning, problem-solving, learning and reasoning. AI is also amenable to deep learning and neural networking.