Drone Guard can detect, identify and jam small USAVs using 3D radar and electro-optical sensors. "The jamming disrupts the drone's flight and either cause it to return to its point-of-origin or to shut down and make a crash landing," according to the AIA's press release. Nice shot of the improvised release mechanism ISIL is using to drop grenades from commercial off the shelf UAVs https://t.co/Lj8Ltx0arQ Recent images out of Iraq show that ISIS has used off-the-shelf drones from DJI and others not just for surveillance, but also bombing and one-time "suicide" explosive missions. According to Kurdish media outlet Rudaw, drones have used explosives and bombs to kills civilians and damage equipment.

A quick, hassle-free way to stay on top of robotics news, our robotics digest is released on the first Monday of every month. Sign up to get it in your inbox. February is only just gone, and already 2017 is shaping up to be a year full of big ideas and ambitions. The Future of Life Institute, for example, just published the Asilomar AI principles: 23 guidelines to ensure AI developments are beneficial to humanity. They are calling for shared responsibility and caution against an AI arms race.

The creator of a chatbot which overturned more than 160,000 parking fines and helped vulnerable people apply for emergency housing is now turning the bot to helping refugees claim asylum. The original DoNotPay, created by Stanford student Joshua Browder, describes itself as "the world's first robot lawyer", giving free legal aid to users through a simple-to-use chat interface. The chatbot, using Facebook Messenger, can now help refugees fill in an immigration application in the US and Canada. For those in the UK, it helps them apply for asylum support. The London-born developer worked with lawyers in each country, as well as speaking to asylum seekers whose applications have been successful.

Google is facing accusations of spreading fake news, after being repeatedly discovered sharing falsehoods and conspiracy theories through its "featured snippets in search" functionality. The feature automatically pulls in short answers to common queries from popular websites. It can show them in the search results directly, and is also the basis for the quick answers provided through Google's smart speaker device, the Google Home. When it works, it leads to the search engine helpfully answering questions like "who is the richest man in the world" without requiring the user to click a further link – in this case, pulling eight names from a listicle on the Indian Express. But when it doesn't, it pulls from sites sharing fake news, propaganda and simple lies. Worse, it can result in the Google Home reading the same statements as fact, without even the presence of the other search results to provide much needed contextual clues that the answers might be misleading.

Machine Intelligence (AI, ML and Deep Learning) requires a certain calibre of computer science talent. Today, this kind of talent is at the "top of the stack" of computer science. These cutting-edge capabilities used to be found at universities, and work on publicly-funded blue sky research; today, companies have the talent, and use it for private, applied purposes. The Economist touched on this in "Million Dollar Babies": That race for talent, is catalysing acquisitions by corporates interested in adding AI to their products and services. As an example, Ex-Googler Sebastian Thurn estimated that the going rate for self-driving engineering talent is $10 million per person.

A new era of AI began around 2010. Computer power capacity significantly increased and neural networks could be integrated into a GPU chip that enabled calculations to speed up experiments. Also, the rise of smartphones and cloud storage services allowed for the consolidation of enormous amount of big data. Those factors significantly impacted the growth of artificial intelligence. Those significant changes in the tech industry influenced the cybersecurity industry and led to a dramatic shift in the field.

U.K. Chancellor of the Exchequer Philip Hammond will use Wednesday's budget to allocate more than 550 million pounds ($676 million) from the National Productivity Fund to boost innovation and technology. The funds will support work in areas including electric vehicles, robotics and artificial intelligence, the Treasury said in a briefing note. Hammond will also set out details on work to boost 5G mobile phone coverage in Britain. The plan for the series of targeted investments comes as Hammond on Sunday pledged to set aside money to cushion the economy from Brexit, and warned the budget would not include any spending commitments funded by borrowing as he seeks to balance the books in the next Parliament. The innovation fund would invest 270 million pounds to benefit projects including cutting-edge artificial intelligence and robots for offshore and nuclear energy, space and deep mining, the development of batteries for the next generation of electric cars, and new ways of manufacturing medicine.

Peter Shulman, an associate history professor at Case Western Reserve University in Ohio, was lecturing on the reemergence of the Ku Klux Klan in the 1920s when a student asked an odd question: Was President Warren Harding a member of the KKK? He confessed that he was not aware of that allegation, but that Harding had been in favor of anti-lynching legislation, so it seemed unlikely. But then a second student pulled out his phone and announced that yes, Harding had been a Klan member, and so had four other presidents. For most of its history, Google did not answer questions. Users typed in what they were looking for and got a list of web pages that might contain the desired information.

Without a doubt, cognitive computing systems are a hot topic around boardrooms, executive suites, and conference tables at major technology firms, which are investing both financial and human resources to bring these systems to fruition. At the same time, government offices throughout the world are holding similar discussions, and these efforts are starting to come to fruition as well. Cognitive computing systems mine both structured and unstructured data to offer hypotheses and solutions for consideration by humans. They thrive on massive amounts of data: greater availability yields better analysis. In addition, cognitive computing systems rely on humans to train them through supervised learning.

The secret to Donald Trump's win: a masterful combination of big data-based manipulation of hapless users, combined with "weaponized" artificial intelligence (AI) which the Trump campaign used to mount a relentless misinformation machine. Or depending on your perspective, Trump's people simply leveraged the latest generation of software tools better than the Clinton campaign was able to manage, a carefully crafted turnabout after Obama's two campaigns successfully gained advantage on the McCain and Romney campaigns respectively by using the latest software of the day. Regardless of how you look at the situation, influencing public opinion is what political campaigns are all about, and successful ones leverage all the tools at their disposal. Increasingly, such tools are software-based – and where political campaigns forge the way, enterprises are sure to follow. While the inside story of the Trump campaign's use of cutting-edge technology may have nefarious overtones for some, the reality is that it set the bar for both progressives as well as conservatives in the future – as well as anyone else seeking to gain a competitive advantage using AI and big data.