Artificial intelligence and robots aren't coming for your job anytime soon, the U.S. White House's chief economic adviser says. Some technology experts worry about the economic impact of A.I.-powered computers and robots, but Jason Furman, chairman of the White House Council of Economic Advisers, predicts that A.I. will grow the economy instead of taking jobs away. While some jobs may disappear, A.I. will create new jobs and consumer demand for new products and services, he said Wednesday at the Nvidia GPU Technology Conference in Washington, D.C. While technology critics believe "the robots are going to take all our jobs away from us," A.I. won't change the basic rules of economics, Furman said. A.I. will create some economic challenges, just as other technologies have, he said.

Austria based ANYLINE, the leading OCR Optical Character Recognition) technology provider for mobile devices, is solely focused on fast and accurate text recognition. Whether reading text across a room, a license plate on a car, or a gas meter in a manufacturing plant, the ANYLINE technology is able to deliver a fast and robust alternative to inputting data via voice recognition, typing, or button scrolling. This type of data import is still difficult to accomplish, as it requires a higher processor power and camera resolution. ANYLINE will now leverage the ... Read more

A startup bankrolled by Bill Gates is about to conduct the first public trials of high-speed body scanners powered by artificial intelligence (AI), the Guardian can reveal. According to documents filed with the US Federal Communications Commission (FCC), Boston-based Evolv Technology is planning to test its system at Union Station in Washington DC, in Los Angeles's Union Station metro and at Denver international airport. Evolv uses the same millimetre-wave radio frequencies as the controversial, and painfully slow, body scanners now found at many airport security checkpoints. However, the new device can complete its scan in a fraction of second, using computer vision and machine learning to spot guns and bombs. This means passengers can simply walk through a scanning gate without stopping or even slowing down – like the hi-tech scanners seen in the 1990 sci-fi film Total Recall.

When Bob Dylan won the 2016 Nobel Prize in Literature, it shocked the humanitarian world. What's more, Dylan himself hasn't behaved like a traditional Nobel winner: he hasn't commented on the honor and has yet to give an acceptance speech. At least one member of the Nobel panel has called Dylan's silence "rude and arrogant," and the public has been reminded that if he doesn't give a lecture within six months, he won't receive the $900,000 prize money. Selecting Dylan as a Nobel laureate may be contentious, but it's mostly a sign of growth for intellectual society -- at least in Literature, no one is off-limits, not even mumbling masters of wordplay and songwriting. Growing pains are expected as the world of mainstream politics, activism and academia is suddenly forced to consider the potential of new industries, and vice versa.

Artificial intelligence and robots aren't coming for your job anytime soon, the U.S. White House's chief economic advisor says. Some technology experts worry about the economic impact of AI-powered computers and robots, but Jason Furman, chairman of the White House Council of Economic Advisers, predicts that AI will grow the economy instead of take jobs away. While some jobs may disappear, AI will create new jobs and consumer demand for new products and services, he said Wednesday at the Nvidia GPU Technology Conference in Washington, D.C. Some studies have suggested that automation will replace half of all jobs in the coming years, but Furman questioned those predictions. While some jobs may disappear, AI will create new jobs and consumer demand for new products and services, he said Wednesday at the Nvidia GPU Technology Conference in Washington, D.C.

They meet people, go to work, even fall in love, all without leaving the comfort of their own home. Now, for the first time, three people with severe spinal injuries have taken the first steps towards that vision by controlling a robot thousands of kilometres away, using thought alone. The idea is that people with spinal injuries will be able to use robot bodies to interact with the world. It is part of the European Union-backed VERE project, which aims to dissolve the boundary between the human body and a surrogate, giving people the illusion that their surrogate is in fact their own body. In 2012, an international team went some way to achieving this by taking fMRI scans of the brains of volunteers while they thought about moving their hands or legs. The scanner measured changes in blood flow to the brain area responsible for such thoughts.

GETTING computers to recognise other cars is surprisingly difficult. Earlier this year, the first fatal autonomous car crash happened when a Tesla Model S failed to distinguish a white truck against a brightly lit sky. Now a study has shown that self-driving cars can be taught the rules of the road by studying virtual traffic on video games such as Grand Theft Auto V (GTA V). Although firms like Google and Uber are teaching their software by physically driving millions of miles in the real world, they also train their algorithms using pre-recorded footage of traffic. But there's a catch: computers need hundreds of thousands of laboriously labelled images, showing where vehicles begin and end, to make them expert vehicle recognisers.

This article is a part of an evolving theme. Here, I explain the basics of Deep Learning and how Deep learning algorithms could apply to IoT and Smart city domains. Specifically, as I discuss below, I am interested in complementing Deep learning algorithms using IoT datasets. I elaborate these ideas in the Data Science for Internet of Things program which enables you to work towards being a Data Scientist for the Internet of Things (modelled on the course I teach at Oxford University and UPM – Madrid).

Artificial intelligence programs have beaten chess masters and TV quiz show champions. Two exchange operators have announced plans to launch artificial intelligence tools for market surveillance in the coming months and officials at a Wall Street regulator say they are not far behind. Executives are hoping computers with humanoid wit can help mere mortals catch misbehaviour more quickly. The software could, for instance, scrub chat-room messages to detect dubious bragging or back slapping around the time of a big trade. It could also unravel complex issues more quickly, like "layering," where orders are rapidly sent to exchanges and then cancelled to move a stock price artificially.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start? For me, my first introduction is when I took an Artificial Intelligence class when I was studying abroad in Copenhagen. My lecturer is a full-time Applied Math and CS professor at the Technical University of Denmark, in which his research areas are logic and artificial, focusing primarily on the use of logic to model human-like planning, reasoning and problem solving.