The second annual Robot Competition and Exhibition sponsored by the Association for the Advancement of Artificial Intelligence was held in Washington D.C. on 13-15 July 1993 in conjunction with the Eleventh National Conference on Artificial Intelligence. This article describes the robots that placed first and second in each event and compares their strategies and their resulting successes and difficulties.
Wanting to find something different when it comes to sex is nothing new, but apparently the craze for sex robots could be risky. We've already reported on claims that teenagers could soon be losing their virginity to the mechanical love machines, with scientists also said to be working on robot sex brothel to cut the risk of STIs. But now comes the warning – according to a expert in the field, we'll need to be careful we don't get addicted to artificial intelligence love making. Joel Snell is an American Research Fellow from Kirkwood College, and he's told the Daily Star there's a real risk linked to the robots. There'll be no need to for a bond with the robot, plus it'll never be able to turn you down.
What happens when you imagine a robot? Most likely, you're picturing something with lots of nuts, bolts, gears and exposed metal. But an emerging field of robotics stands to change the way you think about these automated marvels. Experts in so-called "soft robotics" are designing new highly flexible robots that, in many cases, look more like sea creatures. The goal? Building machines that can accomplish tasks impossible with more rigid, traditionally-designed robots.
The results of the Robolearn-96 Workshop provide evidence that learning in modern robotics is distinct from traditional machine learning. The article examines the role of robotics in the social and natural sciences and the potential impact of learning on robotics, generating both a continuum of research issues and a description of the divergent terminology, target domains, and standards of proof associated with robot learning. The article argues that although robot learning is a new subfield, there is significant potential for synergy with traditional machine learning if the differences in research cultures can be overcome.