A system being developed by Christopher Amato, a postdoc at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), can perform security-camera analysis to identify potential terrorists or illegal entry more accurately and in a fraction of the time it would take a human camera operator. "You can't have a person staring at every single screen, and even if you did the person might not know exactly what to look for," Amato says. "For example, a person is not going to be very good at searching through pages and pages of faces to try to match [an intruder] with a known criminal or terrorist." Existing computer vision systems designed to carry out this task automatically tend to be fairly slow, Amato says. "Sometimes it's important to come up with an alarm immediately, even if you are not yet positive exactly what it is happening," he says.

The great discovery of the twentieth century in art and physics alike, is a recoil from and transformation of the impersonal assembly-line of nineteenth century art and science. At a time like ours, in which mechanical skill has attained unsuspected perfection, the most famous works may be heard as easily as one may drink a glass of beer, and it only costs ten centimes, like the automatic weighing machines. Should we not fear this domestication of sound, this magic that anyone can bring from a disk at his will? Will it not bring to waste the mysterious force of an art which one might have thought indestructible? What is the difference between manipulation of the machine and collaboration with it? I have sometimes experienced a state of dynamic tension rising in me out of what would seem to be a state of mutual responsiveness between the machine and myself. Such a state could require hours of concentrated preparatory exploration, coaxing of machines, connecting, so to say, one's own sensibilities, one's own nerve endings to the totality of the tuned-up controls. And, suddenly, a window would open into a vast field of possibilities; the time limits would vanish, and the machines would seem to become humanized components of the interactive network now consisting of oneself and the machine, still obedient but full of suggestions to the master controls of the imagination. Everything seemed possible: one leaned on the horizon and pushed it away and forward until utter exhaustion would set in and, one by one, the nerve endings ceased to connect, the possibilities contracted, and an automatic reversal to routine solutions was a sure danger signal to quit. An affectionate pat on a control here and there was not to be resisted. If there is an unfinished bit of conversation between you and the machines, either take note of all the controls or leave them alone until tomorrow.

With the help of human instructors, a robot has learned to talk like a human infant, learning the names of simple shapes and colors, reports Wired Science. "Our work focuses on early stages analogous to some characteristics of a human child of about 6 to 14 months, the transition from babbling to first word forms," wrote computer scientists led by Caroline Lyon of the University of Hertfordshire. Named DeeChee, the robot is an iCub, a three-foot-tall open source humanoid machine designed to resemble a baby. The similarity isn't merely aesthetic, but has a functional purpose: many researchers think certain cognitive processes are shaped by the bodies in which they occur. A brain in a vat would think and learn very differently than a brain in a body.

A major European study in which robots attempt to replicate human behavior related to vision, gripping objects, and spatial perception has been developed by researchers at Robotic Intelligence Laboratory of the Universitat Jaume I (UJI) in Spain. A robot head with moving eyes was integrated into a torso with articulated arms, built using computer models computer models from animal and human biology. The robot head uses an advanced 3-D visual system synchronized with robotic arms that allows robots to observe and be aware of their surroundings and also remember the contents of those images in order to act accordingly. The research design process included recording monkey neurons engaged in visual-motor coordination. Saccadic eye movement, related to the dynamic change of attention, was the first feature implemented in the vision system.

Alaric Systems "Fractals" card fraud detection and prevention systems using proprietary inference techniques based on Bayesian methods. Analyst's Notebook 6, from IBM, conducts sophisticated link analysis, timeline analysis and data visualization for complex investigations. Aptelisense Compliance Automation Server, advanced real-time fraud prevention and data compliance that requires zero change to applications or systems. Business Data Miners builds highly effective data-driven models and rules to mitigate credit risk and fraud losses; saved its clients over $100 million in the past 2 years. Centrifuge, offers analysts and investigators an integrated suite of capabilities that can help them rapidly understand and glean insight from new data sources.

The development of artificial intelligence (AI) is rapidly advancing thanks to a machine learning process called "deep learning," raising expectations of radical changes and greater convenience in people's lives. The AI boom began early in the 2010s when major information technology companies such as U.S. companies Google Inc. and Facebook Inc. established research institutes, and the development of deep learning has added fuel to the fire. Deep learning is a branch of machine learning in which a computer system mimics human neural circuits and processes information in multiple processing layers. It is a "revolution" in the foundation of AI, said Yutaka Matsuo, an associate professor at the University of Tokyo and expert on information technology and AI. The AI in a computer system teaches itself by processing huge amounts of data. When, for example, AI processes input data and outputs them, it repeatedly learns the features of the data so as to bring out the same data as those entered.

Japan is set to accelerate its development of robots to secure a lead over rival nations, including the United States and Germany, as a new industrial revolution beckons. The world is "on the threshold of the fourth industrial revolution, a paradigm shift caused by robotics and artificial intelligence," said Takuro Morinaga, a professor at Dokkyo University. "A country that has a hold on the revolution will control the world." The first industrial revolution was propelled by steam engines, the second by electric power and the third by computers. There was considerable anticipation for the field at a symposium on the future of robotics, held in June at the Tokyo International Exhibition Center and attended by more than 1,000 people.

WASHINGTON – When robots play soccer, it looks like a game played by 5-year-olds: they swarm around the ball, kick haphazardly and fall down a lot. However, robot teams have made strides in recent years, and some researchers believe the humanoids could challenge the world's best players in a decade or two. "Maybe in 20 years we could develop a team of robots to play against the best World Cup teams," said Daniel Lee, who heads the University of Pennsylvania robotics lab, which is seeking a fourth consecutive RoboCup in Brazil this month, the premiere event for robotic soccer. Robotic soccer, says Lee, is more than fun and games. It involves artificial intelligence and complex algorithms that help provide a better understanding of human vision, cognition and mobility.

New Research Group The IUPR Research Group at the University of Kaiserslautern has been was succeeded by the Pattern Recognition (MADM) group, headed by Vertr.- Since April 2015 it became absorbed by Prof. Dr. Andreas Dengel, Knowledge Management Department. This is the home page of the Image Understanding and Pattern Recognition group at the University of Kaiserslautern. The group was headed from 2004-2014 by Prof. Dr. Thomas Breuel. Prof. Breuel started working at Google in 2014, but still supervising several students in the department.