George Orwell's "1984" has been enjoying a rebirth since the inauguration of President Donald Trump and senior adviser Kellyanne Conway's use of the term "alternative facts." The 1949 novel is a dystopian view of British society when it's taken over by a totalitarian regime that uses "doublethink" and "newspeak" -- yes means no and no means yes -- to control the population. Conway, complaining on Jan. 22 about how Trump has been treated by the press, denied on NBC's "Meet the Press" that the administration was offering falsehoods when press secretary Sean Spicer insisted more people had witnessed the Trump inauguration than any other inauguration in history. Instead, she said, the administration was offering "alternative facts." The San Francisco Chronicle reported Friday a "mysterious benefactor" bought 59 copies of the novel at Booksmith in the Haight-Ashbury neighborhood to be given away for free.

The Defense Advanced Research Projects Agency (DARPA) has made a system that can catch drones mid-flight. Instead of risking damage when drones need to land in battlefields or on US Navy Ships, the DARPA SideArm capture system can retrieve drones up to 1100 pounds (500 kg) in weight. The system can fit in a shipping container and can be set up and operated by two to four people, enabling the SideArm to be portable. In December 2016, the system was tested with a 400-pound (181 kg) Lockheed Martin Fury Unmanned Aerial System (UAS) drone. Aurora Flight Sciences, who tested the SideArm, accelerated the drone to speeds that it would fly at using an external catapult.

Machine learning classifiers are known to be vulnerable to inputs maliciously constructed by adversaries to force misclassification. Such adversarial examples have been extensively studied in the context of computer vision applications. In this work, we show adversarial attacks are also effective when targeting neural network policies in reinforcement learning. Specifically, we show existing adversarial example crafting techniques can be used to significantly degrade test-time performance of trained policies. Our threat model considers adversaries capable of introducing small perturbations to the raw input of the policy. We characterize the degree of vulnerability across tasks and training algorithms, for a subclass of adversarial-example attacks in white-box and black-box settings. Regardless of the learned task or training algorithm, we observe a significant drop in performance, even with small adversarial perturbations that do not interfere with human perception. Videos are available at http://rll.berkeley.edu/adversarial.

The past couple of years have been a real cringe-y time to be an AI researcher. Just imagine a whole bunch of famous technologists and top-serious science authorities all suddenly taking aim at your field of research as a clear and present threat to the very survival of the species. All you want to do is predict appropriate emoji use based on textual analyses and here's Elon Musk saying this thing he doesn't really seem to know much about is the actual apocalypse. It's not that computer scientists haven't argued against AI hype, but an academic you've never heard of (all of them?) pitching the headline "AI is hard" is at a disadvantage to the famous person whose job description largely centers around making big public pronouncements. This month that academic is Alan Bundy, a professor of automated reasoning at the University of Edinburgh in Scotland, who argues in the Communications of the ACM that there is a real AI threat, but it's not human-like machine intelligence gone amok.

Former NASA engineer Mark Moore will now be working on Uber's flying car project, Uber Elevate. SAN FRANCISCO -- George Jetson, your ride is on its way. Uber has just hired a NASA expert to build out its vision for flying cars Monday. Mark Moore, a 30-year veteran of the space agency with expertise in using electric motors to get a vehicle airborne, will help the ride-hailing giant execute on an expansive white paper it released last fall on developing VTOL (vertical take-off and landing) vehicles. "Uber continues to see its role as a catalyst to the growing developing VTOL ecosystem," Nikhil Goel, Uber's head of product for advanced programs, said in a statement.

In the race to make a commercially available flying car, Uber has hired Mark Moore, a talented Nasa aircraft engineer. Moore inspired Google's co-founder, Larry Page, to get involved in flying car projects. Uber now hopes that with Moore's help, it will be able to have flying cars ready in'one to three years.' In the race to make a commercially available flying car, Uber has hired Mark Moore, a talented Nasa aircraft engineer. Moore predicts it wont be long before we see several well-engineered flying cars, estimating it will only be'one to three years' Uber has a plan to launch a fleet of electric aircraft for on-demand aviation. The plan, called Uber Elevate, is set to design these'cars' to take off and land vertically, travel 100 miles on a single charge and has set 2021 as the ready date - although Mr Moore predicts it could be even sooner.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. Samsung is edging closer to its final foldable phone design according to recently submitted patents. The designs, dated by the US Patents Office as the 31st January 2017 and spotted by PhoneArena, reveal a flexible display device that folds in the middle.

Today, Mark takes on that ongoing tension of artificial intelligence and jobs, looking at how things are looking for jobs in Government administration, healthcare, and education. Public sector jobs could be under threat by robots in the next 15 years, according to a new report by The Reform think-tank. As technology is advancing at an unprecedented rate, the report explains, there is a growing opportunity to improve efficiency to the tune of billions of pounds by engaging robots to undertake certain tasks. The tasks that these bots can undertake, however, may have ramifications for civil servants' jobs. The co-author of the report, Alexander Hitchcock, has put this caveat on The Reform's think-tank: "Such a rapid advance in the use of technology may seem controversial, and any job losses must be handled sensitively. But the result will be public services that are better, safer, smarter, and more affordable."

The Cambridge Centre for Risk Studies in collaboration with the United Nations programme on Journalism and Public Information (UNICRI) present a workshop on the Risks and Benefits of Artificial Intelligence and Robotics. From sensing, finance, medicine, transportation and security, a technological revolution is taking place. Artificial Intelligence (AI) has been a feature of science fiction for almost a century, but it is only in more recent years that the prospect of autonomous robotics and artificially intelligent systems has really become viable. While this will potentially provide great opportunities, these developments are likely to have significant impacts upon the very functioning of society, posing practical, ethical, legal and security challenges – much of which is as of yet not fully appreciated or understood. The media and other sources of public information are central in ensuring that citizens and institutions have a realistic and balanced understanding of such technologies.

Writing in the Economist newspaper on 8 October 2016, US President Barack Obama called out artificial intelligence (AI) as one of several areas where'in recent years we have seen incredible technological advances'.2 Long a backroom area of computer science, AI has captured the popular imagination over the last two years as the range and impact of practical AI applications have expanded at a dizzying pace: a quick search on ft.com for'artificial intelligence and robotics' returned 4 stories from September and October 2014, 16 for the same period in 2015 and 54 in 2016. AI is one of several areas of digital innovation that are all both developing increasingly rapidly and interacting with each other in ways whose consequences are challenging to foresee. A useful portmanteau for these changes is the'fourth industrial revolution'. After steam, electricity and computing, this is the term coined3 by Davos founder Klaus Schwab for the deep digital transformation now upon us.