UBIQUITY :: Essays Papers

UBIQUITYAs many battalion have expected, We are surviving in an environment saturated with wired and wireless connections. This scientific explosion has become a part of our daily lives but we dont really realize, to what extent , our trivial behaviors rely on informatic systems and our int agection with them. While we are living in the era of pervasive computing, we may wonder about the change that pervasive computing has brought to our lives and our social and cultural responses to these fascinating technologies and increased change. Some people remain fearful of the impact of the brain machines on our humanity behavior, on the other hand, others are struggling to set our environment filled with intelligent machinery, care the air we breath, and to make our interactions with this machinery as smooth as possible.The story of creating smart machines equipped with the same reasoning capabilities of humans is very old but the era of computers makes it very realistic in the eyes o f scientists. Since we have machines that manage to do all these tasks, it is time for a new generation of machinery that can do on the button what we can do or better from assureing our behavior to making decisions on their own. The article A Bayesian Computer Vision System for molding Human Interactions, provides and excellent example of what people interested in artificial intelligence are trying to do. In fact, they focus on creating machines that understand human behavior and respond according to this interaction. It is stated in the article Our approach to modeling person-to-person interactions is to use supervised statistical machine learning techniques to inform the system to recognize normal single-person behaviors and common person-to-person interactions (Oliver, Rosario, Pentland 831). There are many limitations to accomplish this goal as any new technology or knowledge but the dream seems to be realistic for these people. according to the same article, if the model s are trained to recognize a limited number of human behavior, how to make them understand new patterns without limitations A major emphasis of our work, therefore, is on efficient Bayesian integration of both antecedent knowledge (by the use of synthetic prior models) with evidence from data (by situation-specific parameter tuning). our goal is to be able to successfully apply the system to any normal multiperson interaction situation without additional prepare.This article provides an example of what is going on in many laboratories spread throughout the world and how artificial intelligence focuses on creating smart practical machines that understand and interpret our behavior and probably surpasses our reasoning capabilities.