TWC NEWS VIDEO: In this Tech Talk report, Time Warner Cable News' Adam Balkin looks at how NYU Tandon School of Engineering is teaming up with ff Venture Capital to create what is believed to be the very first U.S. coupling of a university and a venture fund to help accelerate startups working on artificial intelligence. Inside what'll be called the AI NexusLab, five chosen companies, for four months, will get all sorts of AI support, funding, legal advice, whatever they need in order to accelerate their growth to more quickly enter your life.

Some economists are also worried future economies will consist of low-skilled jobs that are not profitable to automate and high-skilled jobs that complement new technologies. The losers will be a widening swathe of middle-skilled workers. Because the trajectory of future technology is unpredictable, the exact impact on jobs is rather unclear. A much cited study by researchers at Oxford University found that 47pc of jobs in the US could become automated in the next 20 years. Yet a recent OECD paper* found (more plausibly, in this columnist's view) that 9pc of jobs at highrisk of being automated. The figure for Ireland was even lower, at 8pc.

A search program that has a word embedding algorithm plugged into it can bring resumes that contain more of these related words up to the top of the search pile, hopefully helping you to find the most qualified candidates without having to read through every single document. Word embeddings do similar work in computer programs that we interact with every day -- programs that target ads at us, decide what we see on social media, or work to improve Internet search results. But here's the problem: These word embeddings learn the relationships between words by studying human writing -- like the hundreds of thousands of articles on Wikipedia or Google News. For Kalai, the problem is not that people sometimes use word embedding algorithms that differentiate between gender or race, or even algorithms that reflect human bias.

Whether or not it's a realistic or practical or good idea, urban commercial drone delivery is grinding remorselessly toward a thing that is going to happen. For many companies, "grind" is the right word, especially if they're trying to do research and development in the United States, where regulations tend to be overly cumbersome and inflexible. To help move things along a bit, Amazon has decided to take its next phase of delivery drone testing to the United Kingdom. Here's the stuff worth caring about from the press release, which amounts to about a third of the press release. In other words, it's relatively informative, as press releases go: Amazon has today announced a partnership with the UK Government to explore the steps needed to make the delivery of parcels by small drones a reality, allowing Amazon to trial new methods of testing its delivery systems.

After a chatbot pretending to be a 13-year-old named Eugene Goostman "passed" a Turing test a few years ago, experts in artificial intelligence got together and decided that a traditional Turing test might not be all that effective in measuring the intelligence of a computer program after all. Instead, they came up with (among many other things) the Winograd Schema Challenge, which is intended to determine how well an artificial intelligence system handles commonsense reasoning: understanding the basics about how the world works, and implementing that knowledge in useful and accurate ways. A few weeks ago, the very first Winograd Schema Challenge took place at the International Joint Conference on Artificial Intelligence in New York City. We spoke with Charlie Ortiz, director of the Laboratory for AI and Natural Language Processing at Nuance Communications and one of the organizers of the Winograd Schema Challenge, about how things went, why the challenge is important, and what it means for the future of AI. The Winograd Schema Challenge tasks computer programs with answering a specific type of simple, commonsense question called a pronoun disambiguation problem (PDP).

Video Friday is your weekly selection of awesome robotics videos, collected by your soft-bodied 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. He is currently a visiting researcher in the Morphology, Evolution & Cognition Lab (Vermont Complex Systems Center, University of Vermont, USA) under the supervision of Prof. Josh Bongard. He wrote in to share some of his latest publications and videos, and it's fascinating.

Airships, which are distinct from blimps by being much more rigid and sounding much less silly, are one of those unusual technologies that has been undergoing a resurgence recently after falling out of favor half a century ago. Airships have potential to be a very practical and cost effective way to move massive amounts of stuff from one place to another place, especially if the another place is low on infrastructure and has a reasonable amount of patience. Lockheed Martin's Skunk Works has been developing a particular kind of airship called a hybrid airship, which uses a combination of aerodynamics and lifting gas to get airborne, for the last decade or so. The P-791 technology demonstrator first flew in 2006, and a company called Hybrid Enterprises is taking Lockheed's airship technology to commercialization. Their LMH-1 will be able to carry over 20,000 kilograms of whatever you want, along with 19 passengers, up to 2,500 kilometers, and it's going to be a real thing: Hybrid Airships recently closed a US 480 million contract to built 12 of them for cargo delivery.

Creating a successful robot company based around providing commercial services is not easy, although as of just the last few years, advances in robotics technology has at least made it possible. Companies like Savioke have shown that robotics has reached a point where autonomous platforms can operate in semi-structured environments, doing useful tasks reliably and cost effectively enough to make a compelling business case. Luvozo, a startup founded in 2013 and based in College Park, Md., is bringing autonomous robots to semi-structured environments with an enormous amount of potential: skilled nursing facilities for seniors. They're introducing a "robot concierge" called SAM, designed to "provide frequent check-ins and non-medical care for residents in long-term care settings" through autonomous navigation, telepresence, and an innovative fall hazard detection system. The potential market here is enormous, and to find out more, we stopped by Luvozo and spoke with CEO and co-founder David Pietrocola.

Every chance we get, we post videos highlighting the adventures of MARLO, the University of Michigan's blissfully unaware bipedal robot. MARLO is totally "blind," without cameras, lidar, or anything else to show it where it's going. But the robot is still able to walk dynamically over a range of terrain that I think would be appropriate to call staggering. Varied terrain does indeed stagger MARLO on a regular basis, and it's probably fallen over more times on video than any robot we've ever seen. Professor Jessy Grizzle and his students have been challenging MARLO with increasingly difficult terrain, most recently at a location on the beautiful Ann Arbor campus called the "Wave Field," an "earth sculpture" created by artist Maya Lin.

This is a guest post. The views expressed here are solely those of the authors and do not represent positions of IEEE Spectrum or the IEEE. Light detection and ranging, or lidar, is a sensing technology based on laser light. It's similar to radar, but can have a higher resolution, since the wavelength of light is about 100,000 times smaller than radio wavelengths. For robots, this is very important: Since radar cannot accurately image small features, a robot equipped with only a radar module would have a hard time grasping a complex object.