Machine translation of human languages (for example, Japanese, English, Spanish) was one of the earliest goals of computer science research, and it remains an elusive one. Like many AI tasks, translation requires an immense amount of knowledge about language and the world. Recent approaches to machine translation frequently make use of text-based learning algorithms to fully or partially automate the acquisition of knowledge. This article illustrates these approaches. Anyone who has taken a graduate-level course in AI knows the answer.

Are you a veteran of L.A.'s current dating scene? Even in the New Los Angeles, with Lyft and Uber giving us cheaper rides and two-thirds of voters passing Measure M, dating without a car is still playing the game with a serious handicap. "I don't mind that you don't drive," a woman I'd been dating for six months told me last year as she drove us to dinner at Broken Spanish for my birthday. L.A. Affairs chronicles the current dating scene in and around Los Angeles.

Traditionally focused on good old-fashioned AI and robotics, the Spanish AI community holds a vigorous computational intelligence substrate. Neuromorphic, evolutionary, or fuzzylike systems have been developed by many research groups in the Spanish computer sciences. It is no surprise, then, that these nature-grounded efforts start to emerge, enriching the AI catalogue of research projects and publications and, eventually, leading to new directions of basic or applied research. In this article, we review the contribution of Melomics in computational creativity.