The researchers, Emil Kirkegaard, Oliver Nordbjerg, and Julius Daugbjerg Bjerrekær, used software to automatically scrape profiles and then uploaded it in a set onto the Open Science Framework, a forum and repository for scientists to share data. The info is only slightly anonymous: While no real names are used, usernames are connected with location and answers to the litany of personal questions OkCupid uses to find compatibility. Some of these, like political leanings or feelings about homosexuality, are quite private. As Kirkegaard repeatedly stated on Twitter, the data was indeed publicly available, but the scraping violates the dating site's terms and a possible legal matter, an OkCupid spokesperson told Vox. And, as Vox points out, it's also a breach of ethics according to the American Psychological Association, which states that people involved in research studies have the right to consent.

In the presentation below, Dr. Demis Hassabis from Google DeepMind delivered a talk on "General Learning Algorithms" to the Royal Society in London on May 22, 2015. Hassabis is a neuroscientist and leading expert on the neural basis of memory and imagination. He was the co-founder and CEO of DeepMind, a neuroscience-inspired AI company, bought by Google in Jan 2014. He is now Vice President of Engineering at Google DeepMind and leads Google's general AI efforts. Demis is a former child chess prodigy, who finished his A-levels two years early before coding the multi-million selling simulation game Theme Park aged 17.

As much as we love to fawn over artificial intelligence (AI), it's still not great at recognizing and parsing natural language. That's why Google is open sourcing its new language parsing model for English, which it calls'Parsey McParseface.' Before you even ask, the name has no meaning. When Google was trying to figure out what to call its language parsing technology, someone suggested Parsey McParseface; it's a bit like Apple's Liam, which has no clever backstory either. The overall AI model model is called SyntaxNet (please make your SkyNet jokes now); 'ol Parsey is just for English. Our biggest ever edition of TNW Conference is fast approaching!

Robots and artificial intelligence have come a long way since a Roomba entered your home to vacuum your floor and Siri gave you advice on the best Italian restaurants in your parents' neighborhood. According to a 2013 University of Oxford study, half of American jobs could be automated within the next two decades. The study identified transportation, logistics and administrative jobs as the most vulnerable to automation. Others assert it is only a matter of time before robots replace teachers, travel agents, interpreters and a host of other professions. With the prospect of such jobs disappearing, many futurists and economists are considering the possibility of a jobless future.

One of the biggest obstacles still facing robotics is adaptability. A robot can be programmed to perform one repetitive task on an assembly line, but is easily confused when confronted with irregularity. This makes it especially difficult when it comes to using robots in agriculture, specifically picking and sorting fruit, since nature creates objects organically and not all fruits are created equal. But now, product design firm Cambridge Consultants has come up with a robot that can identify different types of fruit and sort them accordingly. I called up Chris Roberts, the head of industrial robotics at the UK-based company, to talk more about this impressive development and ask him how exactly the robot works.

Autodesk is already using this technology on a project with Airbus to reimagine and redesign a new airplane cabin partition that is stronger than the original yet half the weight. And the 3D-printed partition will be flying in the A320 later this year. Meanwhile, something else that machine learning will push forward is robotics. An example here is Autodesk's collaboration with the artist Joris Laarman and his team at MX3D to generatively design and robotically print the world's first autonomously manufactured bridge. This summer, we'll hit a button, and robots will print it--in stainless steel and without human intervention--over a canal in Amsterdam. To explore a more advanced Internet of Things, we've been collaborating with design-and-manufacturing research group Hack Rod and a film studio called Bandito Brothers to build a crazy car with a nervous system.

London's Science Museum has launched a Kickstarter campaign to fund the rebuilding of one of the first robots. Eric, as it was called, was originally built in 1928, and was the UK's first humanoid robot, impressing audiences with his movement and speech. He travelled the globe as a showcase for futuristic technology - but disappeared in the 1930s. Now, the museum is trying to raise 35,000 to rebuild him and has received more than 6,000 in four days. Eric was created by British duo Captain William H Richards and Alan Reffell.

Video Friday is your weekly selection of awesome robotics videos, collected by your dance-challenged 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. SNUMAX is a "multi-functional soft robot" developed by Seoul National University's Biorobotics Laboratory, which won the RoboSoft Grand Challenge this year. "Boomf is the noise a marshmallow makes when it falls through your letterbox and lands on your doormat."

There's a grey period that autonomous car developers don't often discuss between humans controlling cars and AI controlling cars, where humans in autonomous cars will need to stay on high alert to avoid accidents with terrible human drivers. Some suggestions have been put forward on how to tackle this intersection, like using visual or aural alerts. The Tesla Model S, which provides a highway self-driving system, alerts the driver through a series of beeps, warning them to take control of the car. However, according to the Technische Universität München in Munich, Germany, all of the current alerts systems are ineffective. A team of researchers said to Spectrum IEEE that vibrotactile display alerts are by far the best way to get the driver's attention, because they are hard to ignore.

Despite heightened tensions between the U.S. government and Silicon Valley in the aftermath of the FBI-Apple standoff, the Department of Defense is increasingly looking to Silicon Valley to help it develop artificial intelligence capabilities. Just this week, Secretary of Defense Ashton Carter made yet another trip to the Silicon Valley, the fourth such trip since he took the DoD helm last year. During this trip, Carter visited the Pentagon new Defense Innovation Unit Experimental, or DIUx, facility, reported the New York Times. During a speech there, Carter again discussed his Third Offset strategy, which looks to high-tech weapons to give the U.S. military an edge of China and Russia in the future. The first and second offset, in case you are wondering, refer to previous eras in which DoD used technology to compensate for a smaller military – the 1950s use of nuclear weapons to deter superior Warsaw Pact forces and the 1970s and 1980s when the Pentagon looked to improved conventional weapons technology, such as cruise missiles, to compensate for a smaller force posture.