AI services like Apple's Siri and others operate by sending your queries to faraway data centers, which send back responses. The reason they rely on cloud-based computing is that today's electronics don't come with enough computing power to run the processing-heavy algorithms needed for machine learning. The typical CPUs most smartphones use could never handle a system like Siri on the device. But Dr. Chris Eliasmith, a theoretical neuroscientist and co-CEO of Canadian AI startup Applied Brain Research, is confident that a new type of chip is about to change that. "Many have suggested Moore's law is ending and that means we won't get'more compute' cheaper using the same methods," Eliasmith says.
Two students have built an AI that could be the basis of future killer robots. In a controversial move, the pair trained an AI bot to kill human players within the classic video game Doom. Critics have expressed concern over the AI technology and the risk it could pose to humans in future. Devendra Chaplot and Guillaume Lample, from Carnegie Mellon University in Pittsburgh trained an AI bot - nicknamed Arnold - using'deep reinforcement learning' techniques. While Google's AI software had previously been shown to tackle vintage 2D Atari games such as Space Invaders, the students wanted to expand the technology to tackle three-dimensional first-person shooter games like Doom.
Recently, the federal office of Science and Technology Policy issued a request for public feedback on "overarching questions in [Artificial Intelligence], including AI research and the tools, technologies, and training that are needed to answer these questions." OSTP is in the process of co-hosting four public workshops in 2016 on topics in AI in order to spur public dialogue on these topics and to identify challenges and opportunities related to this emerging technology. These topics include the legal and governance issues for AI, AI for public good, safety and control for AI, and the social and economic implications of AI. The Request for Information lists 10 specific topics on which the government would appreciate feedback, including "the use of AI for public good" and "the most pressing, fundamental questions in AI research, common to most or all scientific fields." One of the academics who answered the request for information is Shannon Vallor, who is the William J. Rewak Professor at Santa Clara University, and one of the Markkula Center for Applied Ethics' faculty scholars.
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.
After decades of experiencing a slow burn, artificial intelligence innovation has caught fire to become the hottest item on the agendas of the world's top technology firms. "Faced with a constant onslaught of data, we needed a new type of system that learns and adapts, and we now have that with AI," says Arvind Krishna, Senior Vice President of Hybrid Cloud and Director of IBM Research. "What was deemed impossible a few years ago is not only becoming possible, it's very quickly becoming necessary and expected." As a result, leading tech companies, as well as scores of startups and researchers, have been racing to develop AI solutions that can provide competitive advantage by augmenting human intelligence. Today's flurry of AI advances wouldn't have been possible without the confluence of three factors that combined to create the right equation for AI growth: the rise of big data combined with the emergence of powerful graphics processing units (GPUs) for complex computations and the re-emergence of a decades-old AI computation model--deep learning.