Artificial intelligence (AI) is a branch of computer science that is developing machines capable of intelligent behaviour. This involves building machines that can learn from example and complete tasks that would normally require human intelligence, such as speech recognition, language translation, decision-making and visual perception. Artificial intelligence uses machine learning, including deep learning (i.e. Artificial intelligence is the science, whilst machine learning is the enabler for AI. Companies like Google and Nvidia are at the forefront of AI development, conducting research and applying the science to work in areas such as visual processing (e.g.

What would be your legal rights when coming up against a robot? Who would you sue if artificial intelligence denied you promotion, or even a job in the first place? What if your neighbour's future house-cleaning robot blew a fuse and crashed through your hedge or front window? A legal team from Otago University is going to try to find the answers to these questions. Robot'Nao' addresses the opening ceremony of the 2016 RoboCup China Open in Hefei, China.

Somewhere around 1973, I watched the movie, Westworld; a science fiction story set in 1983 (that was the future then), where a robot malfunction creates havoc and terror for unsuspecting vacationers at a futuristic, adult-themed amusement park. It was one of the earlier films dealing with the issue of where you draw the line between what is real and what is not, and what could possibly go wrong. In this case, one robot (played by Yul Brynner) becomes independent of the controls embedded in the technology, which turns out to be the equivalent of a virus that ultimate affects the entire robot population, and complete mayhem breaks out. If you watch any of the HBO series, a newer version of Westworld is now playing, expanding on the idea from the original movie, but taking it even further into the area of artificial intelligence by empowering the robots with an ability to understand, reason, learn, and engage with humans as though they too are human -- making it almost impossible to tell the difference. Let's jump into our reality and think about the prospect of a work-related version of Westworld, where computers armed with artificial intelligence or machine learning, take over the human role; because that's a real fear in the mind of many people, "when will they replace me with a computer?"

What if machines could think like us -- comprehending social cues, visual prompts and spoken words just like a human would? For Computer Science and Artificial Intelligence Laboratory (CSAIL) Professor Patrick Winston, the Ford Professor of Artificial Intelligence and Computer Science and leader of the Genesis Group at CSAIL, uncovering the true nature of human intelligence is the next grand challenge. To solve the puzzle of how humans think, Winston is employing classic engineering methodology to build systems that think and comprehend as people do using computational methods. Motivated by a desire to advance artificial intelligence and create systems that operate in a manner consistent with high-level human thinking, Winston feels there is a substantial difference between machines that actually display human-like intelligence and those that possess superb computational powers such as IBM's Watson system. For Winston, understanding what makes us different leads to questioning our uniquely symbolic nature, our ability to build descriptions using an inner language, and especially our ability to construct and tell stories, from fairy tales to case studies.

With a souped-up reproducing piano and some ingenious learning machines, AI maestro Gerhard Widmer is discovering how performers unlock the art in Mozart. A gray-blue dusk is settling over the Gothic cathedrals, palatial opera houses, and labyrinthine streets of Vienna's First District. Here in the Austrian capital, music is an almost elemental force. It's a place where very old and very new musical traditions collide and intermingle – the perfect setting for a computer scientist obsessed with examining the blips and fault lines, deviations and inventions, that transform music into something more than code and just slightly less than magic. This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. It's Friday evening, and most of his fellow teachers at the University of Vienna have already gone home, but associate professor Gerhard Widmer is bounding up the stairs of a peach-colored Baroque building and into the offices of the Austrian Research Institute for Artificial Intelligence. He waves hello to his team scientists – Simon Dixon, Emilios Cambouropoulos, and Werner Goebl – and makes for a computer monitor marked EUROPA, which is jacked into an electric piano. Widmer eagerly begins to trigger several audio files.

This is WEEKEND EDITION from NPR News. Imagine a world where the combination of faster computers, networks, and amplified human intelligence could bring about a change so radical that those who follow will no longer be human. Some futurists and science fiction writers envision that world coming to pass, not hundreds of years from now but in the next generation. And they call this event the Technological Singularity. From member station KUSP, Rick Kleffel tries to get a glimpse of an un-seeable future.

How do you tell just how smart your robot is? Simple: give it a universal IQ test. Traditional measures of human intelligence often won't be appropriate for systems that have senses, environments and cognitive capacities very different from our own. So Shane Legg and Marcus Hutter at the Swiss Institute for Artificial Intelligence in Manno-Lugano have drafted an alternative test that will allow the intelligence of vision systems, robots, natural language processing programs or trading agents to be compared and contrasted despite their broad and disparate functions. Although there is no consensus on what exactly human intelligence is, most views appear to cluster around the idea that it hinges on a general ability to achieve goals in a wide range of environments, says Legg. The same can be applied to an AI system, by measuring its ability to carry out complex tasks within its particular environment, compared with all other environments.

How do you tell just how smart your robot is? Give it a universal IQ test, researchers suggest. Traditional measures of human intelligence would often be inappropriate for systems that have senses, environments, and cognitive capacities very different from our own. So Shane Legg and Marcus Hutter at the Swiss Institute for Artificial Intelligence in Manno-Lugano, have drafted an idea for an alternative test which will allow the intelligence of vision systems, robots, natural-language processing programs or trading agents to be compared and contrasted despite their broad and disparate functions. Although there is no consensus on exactly what human intelligence is, most views cluster around the idea that it hinges on a general ability to achieve goals in a wide range of environments, says Legg. The same concept can be applied to an AI system, by measuring its ability to carry out complex tasks within its particular environment and then comparing the complexity of its environment with those of a wide range of other AI systems. "But there is a problem," he says.

Perhaps one way of addressing the measurement of machine intelligence would be to mimic the way we measure human intelligence. Although the debate around what "intelligence" actually means has by no means been resolved, most psychologists would agree that the standard IQ tests measure "something" that has predictive power when comparing cognitive results across a human population, or predicting an individual's future performance in a range of cognitive tasks. Perhaps then one could devise a test that explores a number of agreed areas of cognition - for example knowledge, memory, comprehension, vocabulary, etc. - then draw a set of questions that measure "machine IQ". But there are several problems with this approach. Firstly, it is too anthropocentric. Secondly, an IQ test is a snapshot of a subject's cognitive ability.

The mission of the Center for Discovery Science and Health Informatics is to research computational methods to improve healthcare cost, quality, safety and effectiveness. Specifically, it conducts basic and applied research on developing computational theories, analytic methods, and software applications that support decision making and discovery of knowledge from healthcare data. This includes data mining, artificial intelligence and other knowledge discovery methods and tools tailored towards the meaningful use of health data, health services research, evidenced based practice, and decision support for a variety of health system stakeholders and end-users (clinicians, managers, researchers, policy makers, and consumers) from all sectors of the health system.