A "hi-tech robot" shown on Russian state television turns out to be a man in a suit. While airing footage of a technology forum aimed at kids, a Russian state TV reporter proclaimed that Boris the robot "has already learned to dance and he's not that bad." Gizmodo reports: This "robot" actually retails for 250,000 rubles (about $3,770), as first reported by the Guardian, and is made by a company called Show Robots. "Boris" features glowing eyes, and plastic parts -- and shockingly human-like movements. Probably because he needs a human inside to operate properly. This faux-robot (fauxbot?) mystery was actually first unraveled when some eagled-eyed Russian viewers on the internet noticed that a suspiciously human-like neck was showing in the video. The report notes that "there's no indication" that there was intent to deceive anyone. Instead, it "appears to be a case of a TV presenter getting confused with what he believed to be 'modern robots.'" You can watch the broadcast on Russia-24's YouTube channel.

Flippy, a burger-flipping robot that's been trialed in a number of restaurants this year, is coming to Walmart's headquarters in Bentonville, Arkansas, to see whether or not it's the right fit for its in-store delis. Yahoo News reports: Flippy is the world's first autonomous robotic kitchen assistant powered by artificial intelligence from Miso Robotics, a two-year-old startup. Flippy got a gig at Dodger Stadium in Los Angeles with vending food service company Levy Restaurants, part of Compass Group, to fry up chicken tenders and tater tots. Through the World Series, Flippy churned out 17,000 pounds worth of the fried foods. It's able to fry up to eight baskets of food simultaneously. "Walmart saw what we were doing and said, 'Could you bring Flippy from Dodgers Stadium to our Culinary Institute?'" Miso Robotics CEO David Zito told Yahoo Finance.

In practice, a Walmart associate would place a frozen product on the rack. Using visual recognition technology, Flippy identifies the food in the basket and sets it in the cooking oil. The machine then "agitates" the basket by shaking it to make sure the product cooks evenly. When the food is finished cooking, Flippy moves the basket to the drip rack. An associate then tests the food's internal temperature. A few minutes later, the associate can season the food before it hits the hot display case. The reason Walmart is looking at the robot is so it can do some of the more mundane and repetitive tasks at the deli. The robot is supposed to serve as an "extra set of hands," letting the associate spend less time putting potato wedges and chicken tenders in fryers and more time on other services like taking customer orders and prepping other foods.

Joe_Dragon shares a report from ABC News: Twenty-four Amazon workers in New Jersey have been hospitalized after a robot accidentally tore a can of bear repellent spray in a warehouse, officials said. The two dozen workers were treated at five local hospitals, Robbinsville Township communications and public information officer John Nalbone told ABC News. One remains in critical condition and 30 additional workers were treated at the scene. The official investigation revealed "an automated machine accidentally punctured a 9-ounce bear repellent can, releasing concentrated Capsaican," Nalbone said. Capsaican is the major ingredient in pepper spray. The fulfillment center was given the all clear by Wednesday evening. "All of the impacted employees have been or are expected to be released from hospital within the next 24 hours. The safety of our employees is always our top priority and a full investigation is already underway. We'd like to thank all of the first responders who helped with today's incident," Amazon said in a statement Wednesday night.

An anonymous reader quotes a report from Bloomberg: The world's largest retailer is rolling out 360 autonomous floor-scrubbing robots in some of its stores in the U.S. by the end of the January, it said in a joint statement with Brain Corp., which makes the machines. The autonomous janitors can clean floors on their own even when customers are around, according to the San Diego-based startup. Brain's robots are equipped with an array of sensors that let them gather and upload data.

Brain doesn't make its own hardware, focusing instead on developing software -- BrainOS -- that endows machines with autonomy in closed environments. At first, the machines were need to be operated by humans, who "teach" the layout of the space that needs cleaning. After that the robots can perform the task autonomously. The robots, which look like a cross between a miniature Zamboni and a motorized wheel chair, already scrub floors at airports in Seattle, San Diego, Boston and Miami, Brain Chief Executive Office Eugene Izhikevich said. Brain last month unveiled a smaller version of the machine developed jointly with SoftBank's robotics arm and aimed at the Japanese market.

A logistics division of DHL announced today that it will invest $300 million to modernize 60 percent of its warehouses in North America with more IoT sensors and robots. Robotic process automation and software made to reduce workflow interruptions will also play a role. VentureBeat reports: Such technology is already in operation in 85 DHL facilities, or roughly 20 percent of warehouses across North America. Funding announced today will bring emerging technology to 350 of DHL Supply Chain's 430 operating sites. The company has more than 35,000 employees in North America. Conversations are ongoing with more than 25 robotics and process automation industry leaders, DHL Supply Chain president of retail Jim Gehr said. DHL Supply Chain warehouse robots will work primarily with unit-picking operations and will be able to complete a range of tasks, from collaborative piece picking to shuttling items across a factory to following human packers.

An anonymous reader shares an article: I don't use the phrase "Will do!" much in daily conversation, but lately it has been creeping into more and more of my e-mails. An editor asks me to get a draft back to her tomorrow? Will do! A friend heading back to Los Angeles from New York sends me a quick note telling me to enjoy living in the "best city in the world." Will do! The hosts of a panel I'm moderating need me to send over a three-line bio? Will do! "Will do!" is just one of many Smart Replies that Google now provides as a default feature in Gmail, there to assist you in your message composition unless you choose to manually turn them off. In October, the e-mail service, which one analytics firm suggests hosts about a quarter of all the e-mails sent worldwide, made this feature standard on its 1.4 billion active accounts, along with a menu of other innovations.

These include Smart Compose, a feature that finishes your sentences for you with the help of robot intelligence, and Nudges, a feature that bumps unanswered e-mails to the top of your in-box, making you feel increasingly guilty with every sign-in. As with many technological updates that are suddenly imposed on unsuspecting users, the new Gmail interface has been met with much annoyance. When my in-box started offering me Smart Replies, I felt a little offended. How dare it guess what I want to say, I thought. I -- a professional writer! -- have more to offer than just "Got it!" or "Love it!" or "Thanks for letting me know!" (Smart Replies are big on exclamation points.) I started to resent the A.I., which seemed to be learning my speech patterns faster than I could outsmart it. Just as I decided that I'd thwart the machine mind by answering my messages with "Cool!", the service started offering me several "Cool" varietals. Suddenly, I could answer with "Sounds cool" or "Cool, thanks" or the dreaded "Cool, I'll check it out!"

A small group of Pixel owners in "select" U.S. cities are able to use Google's new Duplex feature to automatically make voice calls to restaurants and other businesses on their behalf. Referencing a demo from VentureBeat, The Verge notes that "the exchange between Duplex and a restaurant on the other side of the call is raising some early concerns about transparency." From the report: [Y]ou'll notice that Duplex never identifies itself as a robot. It never tells the person taking the call that they're interacting with an automated system. "Hi, I'm calling to make a reservation for a client. I'm calling from Google, so the call may be recorded," is what Duplex says to begin the conversation. And that little bit -- about the call coming "from Google" and potentially being recorded -- is the only disclosure that it ever provides. From then on, Duplex handles the requested dinner reservation smoothly.

This disclosure doesn't match up with a promotional video for Duplex that Google posted to YouTube back in June. In that example (embedded below), Duplex makes it very clear that it's a bot. "Hi, I'm the Google Assistant calling to make a reservation for a client. This automated call will be recorded." That's a much better approach. You're talking to the Google Assistant. It's an automated call, and it is being recorded; no maybes about it. The report notes that some Duplex calls -- such as the one VentureBeat included in their demo -- are actually handled by a human. "When a human operator at Google places a Duplex call, they don't necessarily disclose anything about Google Assistant or note it's an automated call," reports The Verge. "Because it's not. Not entirely, anyway. Google's Duplex tests involve a mix of the two; some are led by Googlers, while others let the AI steer. The majority of calls are the latter and automated, from what I'm told."

Amazon is launching AWS RoboMaker, a cloud-based service that utilizes the open-source software Robot Operating System (ROS) to offer developers a place to develop and test robotics applications. TechCrunch reports: RoboMaker essentially serves as a platform to help speed up the time-consuming robotics development process. Among the tools offered by the service are Amazon's machine learning technologies and analytics that help create a simulation for real-world robotics development. The system can also be used to help manage fleet deployment for warehouse-style robotics designed to work in tandem. "AWS RoboMaker automatically provisions the underlying infrastructure and it downloads, compiles, and configures the operating system, development software, and ROS," the company writes. "AWS RoboMaker's robotics simulation makes it easy to set up large-scale and parallel simulations with pre-built worlds, such as indoor rooms, retail stores, and racing tracks, so developers can test their applications on-demand and run multiple simulations in parallel."

Some of Amazon's workers in Europe are protesting against what they call unfair work conditions, in a move meant to disrupt operations on Black Friday. From a report: They've timed the latest protest for Black Friday, one of the busiest annual shopping days online as retailers slash prices and heavily promote deals to try to spark a seasonal buying rush. In the UK, the GMB Union says it's expecting "hundreds" to attend protests timed for early morning and afternoon at Amazon warehouses in Rugeley, Milton Keynes, Warrington, Peterborough and Swansea. At the time of writing the union had not provided details of turnout so far.

Protests are also reported to be taking place in Spain, France and Italy today. Although, when asked about strikes at its facilities in these countries, Amazon claimed: "Our European Fulfilment Network is fully operational and we continue to focus on delivering for our customers. Any reports to the contrary are simply wrong." The demonstrations look intended to not only apply pressure on Amazon to accept collective bargaining but encourage users of its website to think about the wider costs involved in packing and despatching the discounted products they're trying to grab. In a statement on Wednesday announcing the Black Friday protest, Tim Roache, the GMB's general secretary, said: "The conditions our members at Amazon are working under are frankly inhuman. They are breaking bones, being knocked unconscious and being taken away in ambulances. We're standing up and saying enough is enough, these are people making Amazon its money. People with kids, homes, bills to pay -- they're not robots."

CV Compiler is a new web app that uses machine learning to analyze and repair your technical resume, "allowing you to shine to recruiters at Google, Yahoo and Facebook," reports TechCrunch. "The app essentially checks your resume and tells you what to fix and where to submit it," reports TechCrunch. "It's been completely bootstrapped thus far and they're working on new and improved machine learning algorithms while maintaining a library of common CV fixes." From the report: "There are lots of online resume analysis tools, but these services are too generic, meaning they can be used by multiple professionals and the results are poor and very general. After the feedback is received, users are often forced to buy some extra services," said Andrew Stetsenko. "In contrast, the CV Compiler is designed exclusively for tech professionals. The online review technology scans for keywords from the world of programming and how they are used in the resume, relative to the best practices in the industry."

The product was born out of Stetsenko's work at GlossaryTech, a Chrome extension that helps users understand tech terms. He used a great deal of natural language processing and keyword taxonomy in that product and, in turn, moved some of that to his CV service. "We found that many job applications were being rejected without even an interview, because of the resumes. Apparently, 10 seconds is long enough for a recruiter to eliminate many candidates," he said.

wiredmikey shares a report from SecurityWeek: BlackBerry on Friday announced that it has agreed to acquire endpoint security firm Cylance for $1.4 billion in cash. "We plan on immediately expanding the capabilities across BlackBerry's 'chip-to-edge' portfolio, including QNX, our safety-certified embedded OS that is deployed in more than 120 million vehicles, robot dogs, medical devices, and more," a BlackBerry company spokesperson told SecurityWeek. "Over time, we plan to integrate Cylance technology with our Spark platform, which is at the center of our strategy to ensure data flowing between endpoints (in a car, business, or smart city) is secured, private, and trusted." Cylance has raised roughly $300 million in funding [prior being acquired]. BlackBerry describes the "Spark platform" as a secure chip-to-edge communications platform "designed for ultra-security and industry-specific safety-certifications, such as ISO 26262 in automobiles."

Google's parent company Alphabet is closing down Schaft, its secretive unit that develops bipedal robots aimed at helping out in disaster efforts. The news was first reported by Nikkei, but Alphabet confirmed to TechCrunch that the business will be shuttered. It said it is helping staff find new roles, most of which will likely be outside of Google and its Alphabet parent. TechCrunch reports: The company was scheduled to be sold to SoftBank alongside Boston Dynamics -- another of Alphabet's robotics ventures -- through a deal that was announced last year. Boston Dynamics made the transition but Schaft didn't. Softbank never shouted that omission from the rooftops, but a source with knowledge of the deal told us that certain conditions agreed for the deal were not fulfilled, hence Schaft remained with Alphabet. Our source explained that Alphabet's robotics focused shifted away from Schaft and instead to non-humanoid robots and industry-led solutions such as robotic arms.

The departure of Andy Rubin, the controversial robotics evangelist who reportedly got a $90 million payout to leave amid sexual misconduct allegations, seemed to speed up its demise inside the organization. Alphabet shopped the Schaft business fairly widely -- since 2016 and after the SoftBank deal collapsed -- but to no avail, we understand. That left closing it down as the last remaining option.

The British Army is testing out over 70 new technologies, including unmanned vehicles and surveillance drones, in a four-week experiment on one of its biggest training grounds. From a report: What sort of stuff? The department isn't giving out specifics but said the focus will be on "surveillance, long-range, and precision targeting, enhanced mobility and the re-supply of forces, urban warfare and enhanced situational awareness." The development is part of a $1030 million "innovation fund" launched in 2016. The aim? Primarily it's about reducing the danger to troops during combat, according to the UK's Ministry of Defense (MoD). One of the main areas it'll test is "last mile" supply of fuel, food, and ammunition. The exercise will culminate in a simulated battle involving over 200 soldiers to test out the ideas and products.

An anonymous reader shares an analysis: Last month, AI-generated art arrived on the world auction stage under the auspices of Christie's, proving that artificial intelligence can not only be creative but also produce world class works of art -- another profound AI milestone blurring the line between human and machine. Naturally, the news sparked debates about whether the work produced by Paris-based art collective Obvious could really be called art at all. Popular opinion among creatives is that art is a process by which human beings express some idea or emotion, filter it through personal experience and set it against a broader cultural context -- suggesting then that what AI generates at the behest of computer scientists is definitely not art, or at all creative.

The story raised additional questions about ownership. In this circumstance, who can really be named as author? The algorithm itself or the team behind it? Given that AI is taught and programmed by humans, has the human creative process really been identically replicated or are we still the ultimate masters? At GumGum, an AI company that focuses on computer vision, we wanted to explore the intersection of AI and art by devising a Turing Test of our own in association with Rutgers University's Art and Artificial Intelligence Lab and Cloudpainter, an artificially intelligent painting robot. We were keen to see whether AI can, in fact, replicate the intent and imagination of traditional artists, and we wanted to explore the potential impact of AI on the creative sector.

[...] Intriguingly, while at face value the AI artwork was indistinguishable from that of the more traditional artists, the test highlighted that the creative spark and ultimate agency behind creating a work of art is still very much human. Even though the Cloudpainter machine has evolved over time to become a highly intelligent system capable of making creative decisions of its own accord, the final piece of work could only be described as a collaboration between human and machine. Van Arman served as more of an "art director" for the painting. Although Cloudpainter made all of the aesthetic decisions independently, the machine was given parameters to meet and was programed to refine its results in order to deliver the desired outcome. This was not too dissimilar to the process used by Obvious and their GAN AI tool.

An anonymous reader quotes a report from MIT Technology Review: In a laboratory that overlooks a busy shopping street in Cambridge, Massachusetts, a robot is attempting to create new materials. A robot arm dips a pipette into a dish and transfers a tiny amount of bright liquid into one of many receptacles sitting in front of another machine. When all the samples are ready, the second machine tests their optical properties, and the results are fed to a computer that controls the arm. Software analyzes the results of these experiments, formulates a few hypotheses, and then starts the process over again. Humans are barely required.

The setup, developed by a startup called Kebotix, hints at how machine learning and robotic automation may be poised to revolutionize materials science in coming years. The company believes it may find new compounds that could, among other things, absorb pollution, combat drug-resistant fungal infections, and serve as more efficient optoelectronic components. The company's software learns from 3-D models of molecules with known properties. Kebotix uses several machine-learning methods to design novel chemical compounds. The company feeds molecular models of compounds with desirable properties into a type of neural network that learns a statistical representation of those properties. This algorithm can then come up with new examples that fit the same model. To strain out potentially useless materials, Kebotix uses another neural network and "then the company's robotic system tests the remaining chemical structures," reports MIT Technology Review. "The results of those experiments can be fed back into the machine-learning pipeline, helping it get closer to the desired chemical properties. The company dubs the overall system a 'self-driving lab.'"

Amazon is hiring around 100,000 additional employees this holiday season, which is fewer than the company added in either the 2016 or 2017 holiday seasons, when it brought in 120,000 additional workers. "Citi analyst Mark May says he thinks the reduction in seasonal hiring is strong evidence that Amazon is succeeding with plans to automate operations in its warehouses," reports Quartz. From the report: "We've seen an acceleration in the use of robots within their fulfillment centers, and that has corresponded with fewer and fewer workers that they're hiring around the holidays," May told CNBC. He added that 2018 is the "first time on record" Amazon plans to hire fewer holiday workers than it did the previous year. "Since the last holiday season, we've focused on more ongoing full-time hiring in our fulfillment centers and other facilities," Amazon spokesperson Ashley Robinson said in an email, adding that the company has "created over 130,000 jobs" in the last year. "We are proud to have created over 130,000 new jobs in the last year alone."

Amazon bought robotics company Kiva Systems for $775 million in 2012, and began using its orange robots in warehouses in late 2014. By mid-2016, it had become clear just how big a difference those robots were making. The little orange guys could handle in 15 minutes the sorting, picking, packing, and shipping that used to take human workers an hour or more to complete. In June 2016, Deutsche Bank predicted Kiva automation could save Amazon nearly $2.5 billion (those savings dropped to $880 million after accounting for the costs of installing robots in every warehouse).

The world's largest neuromorphic supercomputer, the Spiking Neural Network Architecture (SpiNNaker), was just switched on for the first time yesterday, boasting one million processor cores and the ability to perform 200 trillion actions per second. HotHardware reports: SpiNNaker has been twenty years and nearly $19.5 million in the making. The project was originally supported by the Engineering and Physical Sciences Research Council (EPSRC), but has been most recently funded by the European Human Brain Project. The supercomputer was designed and built by the University of Manchester's School of Computer Science. Construction began in 2006 and the supercomputer was finally turned on yesterday.

SpiNNaker is not the first supercomputer to incorporate one million processor cores, but it is still incredibly unique since it is designed to mimic the human brain. Most computers send information from one point to another through a standard network. SpiNNaker sends small bits of information to thousands of points, similar to how the neurons pass chemicals and electrical signals through the brain. SpiNNaker uses electronic circuits to imitate neurons. SpiNNaker has so far been used to mimic the processing of more isolated brain networks like the cortex. It has also been used to control SpOmnibot, a robot that processes visual information and navigates towards its targets.

MIT researchers have devised a way to train semantic parsers by mimicking the way a child learns language. "The system observes captioned videos and associates the words with recorded actions and objects," ZDNet reports, citing the paper presented this week. "It could make it easier to train parsers, and it could potentially improve human interactions with robots." From the report: To train their parser, the researchers combined a semantic parser with a computer vision component trained in object, human and activity recognition in video. Next, they compiled a dataset of about 400 videos depicting people carrying out actions such as picking up an object or walking toward an object. Participants on the crowdsourcing platform Mechanical Turk to wrote 1,200 captions for those videos, 840 of which were set aside for training and tuning. The rest were used for testing. By associating the words with the actions and objects in a video, the parser learns how sentences are structured. With that training, it can accurately predict the meaning of a sentence without a video.

Engineers are building a prototype of a robotic factory that will create water, oxygen, and fuel on the surface of Mars. From a report: The year is 2038. After 18 months living and working on the surface of Mars, a crew of six explorers boards a deep-space transport rocket and leaves for Earth. No humans are staying behind, but work goes on without them: Autonomous robots will keep running a mining and chemical-synthesis plant they'd started years before this first crewed mission ever set foot on the planet. The plant produces water, oxygen, and rocket fuel using local resources, and it will methodically build up all the necessary supplies for the next Mars mission, set to arrive in another two years. This robot factory isn't science fiction: It's being developed jointly by multiple teams across NASA. One of them is the Swamp Works Lab at NASA's John F. Kennedy Space Center, in Florida, where I am a team lead. Officially, it's known as an in situ resource utilization (ISRU) system, but we like to call it a dust-to-thrust factory, because it turns simple dust into rocket fuel. This technology will one day allow humans to live and work on Mars -- and return to Earth to tell the story.

But why synthesize stuff on Mars instead of just shipping it there from Earth? NASA invokes the "gear-ratio problem." By some estimates, to ship a single kilogram of fuel from Earth to Mars, today's rockets need to burn 225 kilograms of fuel in transit -- launching into low Earth orbit, shooting off toward Mars, slowing down to get into Mars orbit, and finally slowing to a safe landing on the surface of Mars. We'd start with 226 kg and end with 1 kg, which makes for a 226:1 gear ratio. And the ratio stays the same no matter what we ship. We would need 225 tons of fuel to send a ton of water, a ton of oxygen, or a ton of machinery. The only way to get around that harsh arithmetic is by making our water, oxygen, and fuel on-site. Different research and engineering groups at NASA have been working on different parts of this problem. More recently, our Swamp Works team began integrating many separate working modules in order to demonstrate the entire closed-loop system. It's still just a prototype, but it shows all the pieces that are necessary to make our dust-to-thrust factory a reality. And although the long-term plan is going to Mars, as an intermediate step NASA is focusing its attention on the moon. Most of the equipment will be tried out and fine-tuned on the lunar surface first, helping to reduce the risk over sending it all straight to Mars.

In what is referred to as the "Moral Machine Experiment", a survey of more than two million people from nearly every country on the planet, people preferred to save humans over animals, young over old, and more people over fewer. From a report: Since 2016, scientists have posed this scenario to folks around the world through the "Moral Machine," an online platform hosted by the Massachusetts Institute of Technology that gauges how humans respond to ethical decisions made by artificial intelligence. On Wednesday, the team behind the Moral Machine released responses from more than two million people spanning 233 countries, dependencies and territories. They found a few universal decisions -- for instance, respondents preferred to save a person over an animal, and young people over older people -- but other responses differed by regional cultures and economic status.

The study's findings offer clues on how to ethically program driverless vehicles based on regional preferences, but the study also highlights underlying diversity issues in the tech industry -- namely that it leaves out voices in the developing world. The Moral Machine uses a quiz to give participants randomly generated sets of 13 questions. Each scenario has two choices: You save the car's passengers or you save the pedestrians. However, the characteristics of the passengers and pedestrians varied randomly -- including by gender, age, social status and physical fitness. What they found: The researchers identified three relatively universal preferences. On average, people wanted: to spare human lives over animals, save more lives over fewer, prioritize young people over old ones. When respondents' preferences did differ, they were highly correlated to cultural and economic differences between countries. For instance, people who were more tolerant of illegal jaywalking tended to be from countries with weaker governance, nations who had a large cultural distance from the U.S. and places that do not value individualism as highly. These distinct cultural preferences could dictate whether a jaywalking pedestrian deserves the same protection as pedestrians crossing the road legally in the event they're hit by a self-driving car. Further reading: The study; and MIT Technology Review.