German researchers have designed a robot that can "feel pain" such as intense heat or pressure and then retract from the danger, a capability intended to protect the robot from harm just like the pain response in humans. I always thought BattleBots could use higher emotional stakes." "Wait, so does this make them harder or easier to kill?"

Artificial Intelligence: A Modern Approach (AIMA) is a university textbook on artificial intelligence, written by Stuart J. Russell and Peter Norvig. The third edition of the book was released 11 December 2009. It is used in over 1100 universities worldwide[1] and has been called "the most popular artificial intelligence textbook in the world".[2] The book is intended for an undergraduate audience but can also be used for graduate-level studies with the suggestion of adding some of the primary sources listed in the extensive bibliography. Artificial Intelligence: A Modern Approach is divided into seven parts with a total of 27 chapters.[3]

A pair of riddles used during job interviews for Google and Goldman Sachs may have many applicants perplexed, but it's no problem for artificial intelligence. Google's deep neural network was put through the tests of the'hats riddle' and the'switch riddle' both which require complex-problem solving to determine the fates of hypothetical prisoners. The answers to these riddles are based upon coordinated strategy, and the researchers say the AI's ability to master such tasks reveals a step in the direction of collaborative systems. The prisoners can see the hats of the people lined up in from of them, but they cannot look at the hats behind them, or at their own. The executioner asks the last prisoner to state the colour of his hat.

It's a beautiful introduction ... Try not to drool too much! Read "A Few Useful Things to Know about Machine Learning" by Prof. Pedro Domingos. It's densely packed with valuable information, but not opaque. The author understands that there's a lot of "black art" and folk wisdom, and they invite you in. Take your time with this one.

Lecture Title: Machines that learn: big data or explanatory models? Abstract: A leading question about machines that learn concerns two distinct styles of learning. Will they turn out to depend more on probabilistic models that explain the data, or on networks that react to data and are trained on data at ever greater scale? In machine vision systems, for instance, this boils down to the comparative roles of two paradigms: analysis-by-synthesis versus empirical recognisers. Each approach has its strengths, and empirical recognisers especially have made great strides in performance in the last few years, through deep learning.

When our robot overlords launch the nukes and seize control of the planet, chances are they'll rise up first in the United States. And they definitely won't deliver evil speeches when they're running the place. Those are the conclusions a technophobe might draw from a new study identifying a possible flaw in the Turing Test, which is considered a means for evaluating artificial intelligence. The study found that a machine can successfully masquerade as a thinking entity during a blind conversation, if it is allowed to remain silent whenever it chooses (i.e. The Turing test, or imitation game, was developed by famed mathematician Alan Turing to evaluate whether a machine can present itself as a thinking entity by simulating the quirks, imperfections and thought processes that people demonstrate in conversation.

For a team of Norwegian researchers, a tiny labyrinth modeled on the 1980s arcade game "Pac-Man" provides the ideal environment to study a real-life cat and mouse game involving microorganisms. In a video produced by the researchers at the University College of Southeast Norway, single-celled euglena and ciliates take on the role of Pac-Man as they are chased through a liquid-filled, 3D maze by multi-celled rotifers, much like the original game's hungry ghosts. The researchers say recreating a tiny version of the game – less than a millimeter in diameter – offers both scientific benefits and the additional bonus of being able to better communicate their research to the public. Created with the help of filmmaker Adam Bartley, it's also "tremendous fun," they note in a blog post (translation via Google Translate). The maze's neon blue top-light and lens flare effects make for an attractive visual package, but scientists who create these kinds of publicity-friendly contrivances run the risk of alienating their funders, particularly in the United States, where scientists frequently face skepticism from Congress when it comes to explaining the utility of their research.

Coding will join this list in time, however, where it differs wildly from the afore mentioned examples is it is unlikely to be lovingly preserved for future generations to admire, fiddle with or better still, reactivate. Its essence will not be reified for one specific reason – it can't be touched and humans value tactility. We touch immediately, both inside and outside the womb. Today, we find ourselves at a pivotal moment in our existence and about to experience an exponential period of rapid technological growth the likes of which is quite probably beyond our comprehension and at a base level, will have serious implications for coding. We rather arrogantly think that because we have a good grasp of our own technological advancement so far, we can somehow predict the mass cultural and behavioural shift about to happen as we question our own skills in the world. Us techies hold on to the notion that we are the masters of code, and we will be forever commanding line by line, the computers to do our bidding.

The skies above are growing increasingly crowded with satellites zipping across Earth's upper atmosphere, relaying signals for everything from the picture on your television to the map on your phone. While this constant communication makes the world go round, all of that orbiting technology brings with it a problem, in the form of space junk – the debris from rocket launches and defunct satellites which hangs on in space. Lapping the Earth at thousands of miles per hour means even smallest chunks of metal or flecks of paint can cause significant damage if they run into the path of a satellite. But scientists at the University of Surrey are gearing up to test technologies which could target potentially hazardous space junk and remove it from orbit before it can cause any damage. The first experiment will use a net to capture a target in the form of a small CubeSat launched from the main satellite.

A serious problem in the Turing test for computer intelligence is exposed in a study published in the Journal of Experimental and Theoretical Artificial Intelligence. If a machine were to'take the Fifth Amendment' – that is, exercise the right to remain silent throughout the test – it could, potentially, pass the test and thus be regarded as a thinking entity, authors Kevin Warwick and Huma Shah of Coventry University argue. However, if this is the case, any silent entity could pass the test, even if it were clearly incapable of thought. The test, devised in 1950 by pioneering computer scientist Alan Turing, assesses a machine's ability to exhibit intelligent behaviour indistinguishable from that of a human. Also known as the'imitation game', it requires a human judge to converse with two hidden entities, a human and a machine, and then determine which is which.