We describe a variety of projects developed as part of a course in Artificial Intelligence at the University of Minnesota. The projects cover navigation of small mobile robots and learning to accomplish simple tasks, and require a variety of approaches from neural networks to genetic programming to reactive behaviors. The projects have all been implemented on real robots. We discuss how the combination of robotics with Artificial Intelligence adds value to the learning of AI concepts and how the fun of building and programming a robot is a highly motivating force for the learning process. 1 Introduction The major goal of this paper is to describe examples of integration of real robotics projects in a course in Artificial Intelligence. The examples presented here are some of the class projects done by students taking a course in Artificial Intelligence at the University of Minnesota.

Increasing globalization is driving a burgeoning demand on the language services market, which, according to statistics, is expected to reach $31.4 billion this year alone and is growing by a rapid rate of 7.4 percent annually. In response to this ever-growing need for language service providers and users of translation services to operate more efficiently, Science Applications International Corp. (SAIC (News - Alert)) has unveiled the industry's first-ever machine chat translation solution. Designed to enable tailored and adaptive contextual translation, this new integrated offering is meant for anyone that has to interact with another individual who speaks the same language or a different language, SAIC shared with TMC at the recent SpeechTEK (News - Alert) 2011 in New York City, where SAIC debuted the solution. "We've brought a single platform that does both text and speech and combined it with hybrid machine translation," Hassan Sawaf, chief scientist for SAIC, told TMC (News - Alert) during an interview at SpeechTEK. "It's highly customizable, tailorable and secure since it can reside on servers within a firewall." According to a press release, organizations using the machine translation technology will decrease the need for costly human translation, thus resulting in lower costs for businesses and boosted productivity for translation providers.

Using humanoid robots to study human behavior.

In his new book, Who Owns The Future?, computer scientist, Jaron Lanier, argues that as technology has become more advanced, so too has our dependency on information tools. Lanier believes that if we continue on our present path, where we think of computers as passive tools, instead of machines that real people create, our myopia will result in less understanding of both computers and human beings, which could cause the demise of democracy, mass unemployment, the erosion of the middle class, and social chaos. Lanier encourages human beings to take back control of their own economic destiny by creating a society that values the work of all industries, and not just those with the fastest networks. By monetizing information, he foresees a more egalitarian society, which can still adhere to the principles of free market capitalism. What will the future economy look like if technology keeps advancing the way it does and we do nothing?

Helping employees find the right information when they need it represents a major challenge for businesses. An information worker spends two hours a day just searching for information. Aside from the obvious potential frustration for the employee, there's also real business value at stake here: a recent study finds that employees could be up to 30% more efficient if they were armed with the knowledge needed to get the job done. Cognitive computing has the potential to make real impact here, say Carla O'Dell and Lauren Trees in an article in KM World: They point out that industries as diverse as healthcare, software, financial services and oil and gas exploration are already starting to see results from turning to cognitive technologies. Being able to process massive amounts of data, both structured and unstructured, to provide "personalized, intuitive responses" offers significant promise for the field of knowledge management.

Hybrid cars have long been hailed as a more eco-friendly vehicle option, and researchers are trying to make future hybrids even greener. The answer potentially lies in helping cars learn their own habits and letting them adjust fuel sources on their own. Engineers from the University of California, Riverside have developed an algorithm they believe can be used in the computers of plug-in hybrid electric cars to reduce their fuel consumption by one-third, according to a study published this week in IEEE Transactions on Intelligent Transportation Systems. The researchers used evolutionary algorithms based on flocking birds and swarming bees to help plug-in hybrid cars learn about the complexities of zipping around roads and highways. The idea is that the algorithm would allow the car to learn how to optimize energy efficiency based on individual driving history, as well as allow it to share that data with other cars online in its network.

Babies build knowledge about the language they hear even in the first few months of life, research shows. If you move countries and forget your birth language, you retain this hidden ability, according to a study. Dutch-speaking adults adopted from South Korea exceeded expectations at Korean pronunciation when retrained after losing their birth language. Scientists say parents should talk to babies as much as possible in early life. Dr Jiyoun Choi of Hanyang University in Seoul led the research.