Random Accesses

Can a computer fool expert gamers into believing it's one of them? That was the question posed at the second annual BotPrize, a three-month contest that concluded today at the IEEE Computational Symposium on Intelligence and Games in Milan.

The contest challenges programmers to create a software "bot" to control a game character that can pass for human, as judged by a panel of experts. The goal is not only to improve AI in entertainment, but also to fuel advances in non-gaming applications of AI. The BotPrize challenge is a variant of the Turing test, devised by Alan Turing, which challenges a machine to convince a panel of judges that it is a human in a text-only conversation.

Source: http://www.technologyreview.com/computing/23415/?a=f

EVER had the feeling something is missing? If so, you're in good company. Dmitri Mendeleev did in 1869 when he noticed four gaps in his periodic table. They turned out to be the undiscovered elements scandium, gallium, technetium and germanium. Paul Dirac did in 1929 when he looked deep into the quantum-mechanical equation he had formulated to describe the electron. Besides the electron, he saw something else that looked rather like it, but different. It was only in 1932, when the electron's antimatter sibling, the positron, was sighted in cosmic rays that such a thing was found to exist.

In 1971, Leon Chua had that feeling. A young electronics engineer with a penchant for mathematics at the University of California, Berkeley, he was fascinated by the fact that electronics had no rigorous mathematical foundation. So like any diligent scientist, he set about trying to derive one.

And he found something missing: a fourth basic circuit element besides the standard trio of resistor, capacitor and inductor. Chua dubbed it the "memristor". The only problem was that as far as Chua or anyone else could see, memristors did not actually exist.

Except that they do.
Source: http://www.newscientist.com/article/mg20327151.600-memristor-minds-the-future-of-artificial-intelligence.html

This week marks another incremental step forward in the field of robotics, specifically around gestural control. Brown University reports that their researchers have demonstrated how a robot can follow nonverbal commands from a person in a variety of environments — indoors as well as outside — all without adjusting for lighting. The modified iRobot PackBot can physically follow a person at a select distance without the person needing to wear special clothing, be in a special environment, or look backward at the robot, according to Chad Jenkins, assistant professor of computer science at Brown University and the team’s leader.

Jenkins and his team presented the achievement and a paper at the 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2009) in San Diego recently.

The team developed this capability with two key advances. The first involved visual recognition, which when applied to robots means helping them to orient themselves with respect to the objects in a room. The second advance was to provide the robot with a way to maintain a set distance from a human commander, and that involved a special depth-imaging camera called a CSEM Swiss Ranger.

Source: http://blogs.zdnet.com/emergingtech/?p=1338

Suppose you want to build a computer that operates like the brain of a mammal.

How hard could it be? After all, there are supercomputers that can decode the human genome, play chess and calculate prime numbers out to 13 million digits.

Scientists are studying complex wiring of the brain to build the computer of the future, one that combines the brain’s abilities for sensation, perception, action, interaction and cognition and its low power consumption and compact size.

Understanding the process behind these seemingly effortless feats of the human brain and creating a computational theory based on it remains one of the biggest challenges for computer scientists.

Source: http://www.news.wisc.edu/16085

The National Science Foundation (NSF) Office of Emerging Frontiers in Research and Innovation (EFRI) has announced 12 grants for fiscal year 2008, awarding a total of $23,779,056 over four years to 54 investigators representing 20 institutions.

Interdisciplinary teams will pursue transformative, fundamental research in two areas of great promise: understanding the brain and how its abilities may be used through cognitive optimization and prediction; and developing ways to make complex, interdependent infrastructure systems more resilient and sustainable.

What researchers learn from the brain may open many new paths of discovery, in areas such as computing, robotics, medicine and education. Understanding how the brain moves the hand, for example, could illuminate entirely novel ways to help people who are paralyzed or use prosthetic limbs. Understanding how the brain visually recognizes objects will enable advances in artificial vision systems, robotic intelligence and more.

Source: http://www.nsf.gov/news/news_summ.jsp?cntn_id=112330&govDel=USNSF_51%22