A researcher at Arizona State University has discovered how to control multiple robotic drones using the human brain. A controller wears a skull cap outfitted with 128 electrodes wired to a computer. If the controller moves a hand or thinks of something, certain areas light up. "I can see that activity from outside," said Panagiotis Artemiadis (pictured above), director of the Human-Oriented Robotics and Control Lab and an assistant professor of mechanical and aerospace engineering in the School for Engineering of Matter, Transport and Energy in the Ira A. Fulton Schools of Engineering. "Our goal is to decode that activity to control variables for the robots."

After decades of stagnation in research and development of artificial intelligence solutions, machine learning has blossomed again – and its seeds are spreading to financial services. Sofia Lotto Persio reports on how AI is improving the field. Almost 20 years later, in March 2016, Google's AlphaGo programme beat South Korean champion Lee Sedol at four matches of Go, a strategy game, in what represents another historic breakthrough for artificial intelligence (AI). In the two-decade span between these achievements, AI has progressed tremendously. Go is a much more complex game than chess, as there are more possible positions on the board than there are atoms in the universe.

A quick visit to the page of Boston Dynamics, a subsidiary of Google, reveals the typical, flowery PR flack pleasantry that is one of the cancers of our age. Our mission is to build the most advanced robots on Earth, with remarkable mobility, agility, dexterity and speed. Surely they're developing robots that will help mankind, right? But if you look at the videos of what they're actually developing, it's easy to see how this type of machinery could soon have frightening military and police applications. Imagine a line of these coming at you, armed with weapons.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

Machine intelligence is your firm's primary area of interest. Can you talk about how machine intelligence will make organizations "smarter" and what it'll do to the traditional employer-employee relationship? The intersection of machine intelligence and organizational life is a complex subject about which, today, we know very little. I generally try to avoid predictions, because I think they're mostly lullabies -- stories we tell ourselves to make ourselves feel better. I prefer to focus on the unknowns, so we can work to make them known.

As the country reels from the spasm of gun violence that killed two black men and five officers this week, a prominent digital vigilante is using an online tool he hacked together to keep an eye on hot spots that seem at risk of boiling over into bloodshed. The Web app, which is powered partly by artificial intelligence, analyzes posts on social media as well as police radio chatter and feeds of the local airspace in virtually any region. To detect rumblings of unrest and alert the public. On a recent night, the tool had its gaze trained on Baton Rouge, La., where protesters backed by the New Black Panther Party gathered for a rally. "I'm looking for any indication they are coordinating skirmishes. Using IBM's Watson AI, the tool not only examines large collections of tweets but -- somewhat eerily -- also can go through a single user's timeline and, with Watson's machine learning technology, offer an analysis of that user's "trustworthiness, propensity toward violence [and] openness," the Jester said. That information, he said, could hold clues to a criminal's intentions. If the Jester's name sounds familiar, that's because the hacker has appeared elsewhere -- on Time's list of most influential internet personalities, on CNN and, according to a recent blog post, on an upcoming episode of USA's "Mr.

She is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on her third class project - Web Scraping, due on the 6th week of the program. Oil prices have fallen sharply since the summer of 2014. Prices bottomed in February 2016, since then they have gradually increased. While the breakeven cost is a popular topic among investors, on the consumer side gasoline prices are very cheap.

Teachers are not ends-in-themselves, they are always a means to an end - improvements in the learner. Given this premise, could it be possible to eventually replace teachers with AI technology? This may not happen soon but let's, as a thought experiment, ask whether it could. Obvious points are that AI is 24/7, fast, scalable and cheaper. This gives it a head start.

He told the Cheltenham Science Festival that robot technology risked being hijacked for malign purposes in the way the internet has been for pornography unless governments take action. The former advisor to the United Nations on robotics said he knew of at least 14 companies in South Korea and Japan that were manufacturing and marketing "childcare" robots, and he warned that the growing capability of so-called sex robots means they are likely to enter mainstream use within years. Devices such as the Roxxxy or Rocky True Companion, which come with an optional "talking" feature, can currently be bought online for around 7,000. The cost of sex robots is expected to come down, however, as more manufacturers enter the market.

So Brexit turned out to be the non-event for markets we expected with asset prices booming to record highs while support for remaining inside the single currency free-trade zone has risen within other European Union countries. As is often the case, the trade was to "fade" – or bet against – the apocalyptic hyperbole both before and after the referendum. Remarkably one boutique Australian quant shop did exactly this by leveraging academic studies of "blue green algae", which helped it generate enormous 32 per cent returns on the day of the vote. Taaffeite Capital Management (TCM) claim their "artificial intelligence" (aka computer code operating autonomously of humans) figured out that there were massive financial market mispricings that warranted shorts on equities and long positions on government bonds without actually knowing that a referendum was being held. The intellectual property underlying this "systematic" – or automated – trading strategy belongs to Massachusetts Institute of Technology PhD Desmond Lun, who is a 36-year old Australian professor of computer science at Rutgers University in the US, and a Melbourne University alumnus.