If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Alves-Oliveira, Patrícia (Instituto Universitário de Lisboa) | Freedman, Richard G. (University of Massachusetts Amherst) | Grollman, Dan (Sphero, Inc.) | Herlant, Laura (arnegie Mellon University) | Humphrey, Laura (Air Force Research Laboratory) | Liu, Fei (University of Central Florida) | Mead, Ross (Semio) | Stein, Frank (IBM) | Williams, Tom (Tufts University) | Wilson, Shomir (University of Cincinnati)
Asking effective questions is a powerful social skill. In this paper we seek to build computational models that learn to discriminate effective questions from ineffective ones. Armed with such a capability, future advanced systems can evaluate the quality of questions and provide suggestions for effective question wording. We create a large-scale, real-world dataset that contains over 400,000 questions collected from Reddit "Ask Me Anything" threads. Each thread resembles an online press conference where questions compete with each other for attention from the host. This dataset enables the development of a class of computational models for predicting whether a question will be answered. We develop a new convolutional neural network architecture with variable-length context and demonstrate the efficacy of the model by comparing it with state-of-the-art baselines and human judges.