When an unidentified object hit a British Airways A320 on the nose on its approach to Heathrow last month, the encounter was widely believed the fault of some dope who had flown his drone into busy airspace, endangering the lives of the 137 people aboard the jet. "It was bound to happen," the British Airline Pilots Association said. This time, the errant "drone" was actually a plastic bag, but the FAA isn't sitting around, waiting for a next time. This month, the Federal Aviation Administration announced it's expanding its Pathfinder Program, which it created to detect and identify drones flying too close to airports. To make that happen, the agency's conducting joint research with a number of companies to identify the technology that might be used to spot, block, and drop the unwanted unmanned aircraft systems.

At the 2010 Cannes Film Festival premiere of You Will Meet A Tall Dark Stranger, director Woody Allen was asked about aging. He replied with his characteristic, straight-faced pessimism. "I find it a lousy deal. There is no advantage in getting older. You don't get smarter, you don't get wiser ... Your back hurts more, you get more indigestion ... It's a bad business, getting old. I'd advise you not to do it if you can avoid it."

Machine Learning is not a new subject but is becoming an increasingly hotter topic. We have three speakers to each bring a different spin on the subject and therefore it should be a night where there will be something for everyone, whether you are Data Scientist, Analyst or Digital Marketer. Harvinder leads a team of analysts to deliver data-driven customer insight, marketing optimisation and predictive analytics for Moneysupermarket from one of the largest customer databases in the UK with records for 23 million unique individuals. Harvinder was previously Insight Director for Tesco Clubcard at Dunnhumby and Senior Manager for Customer Strategy and Insights at Lloyds Banking Group.He is passionately interested in Data Science, Machine Learning, Big Data technologies and how they can be used to improve Customer Experience. Harvinder will be showing some live models used at MoneySuperMarket.

Robots have transformed the lives of tradesmen and laborers, but lawyers, architects, and doctors tend to believe that their careers are safe from the advances of artificial intelligence. This belief is entirely wrong, according to the upcoming book, Future of the Professions: How Technology will Transform the Work of Human Experts. The authors, Richard Susskind, UK government advisor and visiting professor at Oxford Internet Institute, and his son Daniel Susskind, lecturer at Oxford University, have conducted a hundred interviews and drawn on economic and sociological theory to reach their challenging conclusion: AI will dramatically transform the middle-class working landscape. In the near-term, the Susskinds argue, artificial intelligence will simply accelerate the efficiency of professions. But then robots will start to take over more work, and humans will find the roles of "doctor" or "lawyer" replaced with such less glamorous-sounding titles as "empathizer," "knowledge engineer," or "system provider."

The German transport ministry says General Motors' Opel division has been asked to appear before a commission looking into diesel emissions controls after an environmental group claimed two of its models are able to reduce pollution controls. The environmental group, DUH, says it has tested Opel's Zafira and Astra models and claims they reduce pollution controls at some speeds and temperatures. DUH wants them taken off the road. Opel says DUH's tests weren't objective or scientifically grounded, saying "our software was never designed to cheat or deceive." Apparently referring to the computer expert who examined the software for DUH, the company said that "the isolated conclusions of a hacker do not reflect the complex interdependencies of a modern exhaust after-treatment system."

To call Didi Chuxing an Uber competitor would be selling it short. While it offers broadly the same service, Didi is far more successful than the American startup is in China. It currently has an 87 percent share of the market, while Uber has struggled to make a big impact. Didi has also made some small investments in Lyft, a US-based Uber rival. As Didi is valued at over 25 billion, this new investment isn't necessarily a game-changer for either company, but its secondary effects might be far stronger. Apple's focus on China is clear.

PDF: We made a fancy PDF of this post for printing and offline viewing. Note: The reason this post took three weeks to finish is that as I dug into research on Artificial Intelligence, I could not believe what I was reading. It hit me pretty quickly that what's happening in the world of AI is not just an important topic, but by far THE most important topic for our future. So I wanted to learn as much as I could about it, and once I did that, I wanted to make sure I wrote a post that really explained this whole situation and why it matters so much. Not shockingly, that became outrageously long, so I broke it into two parts. This is Part 1--Part 2 is here. We are on the edge of change comparable to the rise of human life on Earth. It seems like a pretty intense place to be standing--but then you have to remember something about what it's like to stand on a time graph: you can't see what's to your right. So here's how it actually feels to stand there: Imagine taking a time machine back to 1750--a time when the world was in a permanent power outage, long-distance communication meant either yelling loudly or firing a cannon in the air, and all transportation ran on hay. When you get there, you retrieve a dude, bring him to 2015, and then walk him around and watch him react to everything. It's impossible for us to understand what it would be like for him to see shiny capsules racing by on a highway, talk to people who had been on the other side of the ocean earlier in the day, watch sports that were being played 1,000 miles away, hear a musical performance that happened 50 years ago, and play with my magical wizard rectangle that he could use to capture a real-life image or record a living moment, generate a map with a paranormal moving blue dot that shows him where he is, look at someone's face and chat with them even though they're on the other side of the country, and worlds of other inconceivable sorcery.

In this presentation we will look at implant technology, both in terms of new forms of identification and also in bringing humans and technology together, particularly with regard to the security issues that this presents. We will also see how good the latest artificial intelligence is at posing as a human. The audience will be given the opportunity to try for themselves and see if they can tell the difference between human and machine. Kevin Warwick is Emeritus Professor at Reading and Coventry Universities. His research areas are artificial intelligence, biomedical systems and...

The project is using repurposed Ultra Pods, which are already in operation at London's Heathrow Airport. There, the electric four-wheelers run on tracks, shuttling passengers in relative safety. To help make them road-ready, TRL has teamed up with Westfield Sportscars, a classic car builder based in the West Midlands, and Oxbotica, a research-based offshoot from Oxford University's Mobile Robotics Group. The group's mission is to see how the public reacts to driverless vehicles, especially in urban environments where there are plenty of motorists and pedestrians. Successful applicants will be asked to give some feedback about their driverless adventure.

The amount of data produced every day grows tremendously in most real-life domains, including medical imaging, genomics, text categorisation, computational biology, and many others. Although it appears beneficial at the first glance (more data could mean more possibilities of extracting and revealing useful underlying knowledge), handling massively large datasets became a challenging issue and attracts research attention, especially in the era of big data. This big data revolution affected many research fields, including statistics, machine learning, parallel computing, and computer systems in general [1]. Storing and analysing the acquired historical information should allow predicting the label of an incoming (unseen) feature vector, containing some quantified features of a given data example. If the labels are categorical, then we are to tackle the classification task (it's regression otherwise).